efi_paper.bib

@misc{16,
  title = {Before {{Penalizing Hospitals}}, {{Account}} for the {{Social Determinants}} of {{Health}}},
  year = {2016},
  month = oct,
  abstract = {Focus on Hospitals is the first U.S. website with hospital readmission data formally adjusted to account for patients' social determinants of health.},
  howpublished = {https://catalyst.nejm.org/penalizing-hospitals-account-social-determinants-of-health/},
  journal = {NEJM Catalyst}
}

@article{aaldriks13,
  title = {Frailty and Malnutrition Predictive of Mortality Risk in Older Patients with Advanced Colorectal Cancer Receiving Chemotherapy},
  author = {Aaldriks, Ab A. and {van der Geest}, Lydia G.M. and Giltay, Erik J. and {le Cessie}, Saskia and Portielje, Johanneke E.A. and Tanis, Bea C. and Nortier, Johan W.R. and Maartense, Ed},
  year = {2013},
  month = jul,
  volume = {4},
  pages = {218--226},
  issn = {18794068},
  doi = {10.1016/j.jgo.2013.04.001},
  journal = {Journal of Geriatric Oncology},
  language = {en},
  number = {3}
}

@article{adams13,
  title = {Frailty as a Predictor of Morbidity and Mortality in Inpatient Head and Neck Surgery},
  author = {Adams, Peter and Ghanem, Tamer and Stachler, Robert and Hall, Francis and Velanovich, Vic and Rubinfeld, Ilan},
  year = {2013},
  month = aug,
  volume = {139},
  pages = {783--789},
  issn = {2168-619X},
  doi = {10.1001/jamaoto.2013.3969},
  abstract = {IMPORTANCE: The increasing number of elderly and comorbid patients undergoing surgical procedures raises interest in better identifying patients at increased risk of morbidity and mortality, independent of age. Frailty has been identified as a predictor of surgical complications.
OBJECTIVE: To establish the implications of frailty as a predictor of morbidity and mortality in inpatient otolaryngologic operations.
DESIGN: Retrospective review of medical records.
SETTING: National Surgical Quality Improvement Program (NSQIP) participating hospitals.
PATIENTS: NSQIP participant use files were used to identify 6727 inpatients who underwent operations performed by surgeons specializing in otolaryngology between 2005 and 2010. The study sample was 50.3\% male and 10.2\% African American, with a mean (range) age of 54.7 (16-90) years.
MAIN OUTCOMES AND MEASURES: A previously described modified frailty index (mFI) was calculated on the basis of NSQIP variables. The effect of increasing frailty on morbidity and mortality was evaluated using univariate analysis. Multivariate logistic regression was used to compare mFI with age, ASA, and wound classification. RESULTS The mean (range) mFI was 0.07 (0-0.73). As the mFI increased from 0 (no frailty-associated variables) to 0.45 (5 of 11) or higher, mortality risk increased from 0.2\% to 11.9\%. The risk of Clavien-Dindo grade IV complications increased from 1.2\% to 26.2\%. The risk of all complications increased from 9.5\% to 40.5\%. All results were significant at P {$<$}\,.001. In a multivariate logistic regression model to predict mortality or serious complication, mFI became the dominant significant predictor.
CONCLUSIONS AND RELEVANCE: The mFI is significantly associated with morbidity and mortality in this retrospective survey. Additional study with prospective analysis and external validation is needed. The mFI may provide an improved understanding of preoperative risk, which would facilitate perioperative optimization, risk stratification, and counseling related to outcomes.},
  journal = {JAMA Otolaryngology\textendash Head \& Neck Surgery},
  keywords = {Adult,Aged,Aged; 80 and over,Databases; Factual,Female,Frail Elderly,Geriatric Assessment,Head and Neck Neoplasms,Humans,Inpatients,Logistic Models,Male,Middle Aged,Multivariate Analysis,Neck Dissection,Otorhinolaryngologic Surgical Procedures,Outpatients,Predictive Value of Tests,Retrospective Studies,Risk Assessment,Survival Analysis},
  language = {eng},
  number = {8},
  pmid = {23949353}
}

@article{amrock14,
  title = {Can {{Routine Preoperative Data Predict Adverse Outcomes}} in the {{Elderly}}? {{Development}} and {{Validation}} of a {{Simple Risk Model Incorporating}} a {{Chart}}-{{Derived Frailty Score}}},
  shorttitle = {Can {{Routine Preoperative Data Predict Adverse Outcomes}} in the {{Elderly}}?},
  author = {Amrock, Levana G. and Neuman, Mark D. and Lin, Hung-Mo and Deiner, Stacie},
  year = {2014},
  month = oct,
  volume = {219},
  pages = {684--694},
  issn = {10727515},
  doi = {10.1016/j.jamcollsurg.2014.04.018},
  journal = {Journal of the American College of Surgeons},
  language = {en},
  number = {4}
}

@article{bakker15,
  title = {Hospital {{Care}} for {{Frail Elderly Adults}}: {{From Specialized Geriatric Units}} to {{Hospital}}-{{Wide Interventions}}},
  shorttitle = {Hospital {{Care}} for {{Frail Elderly Adults}}},
  author = {Bakker, Franka C. and Olde Rikkert, Marcel G. M.},
  year = {2015},
  volume = {41},
  pages = {95--106},
  issn = {2297-3486},
  doi = {10.1159/000381171},
  abstract = {Much of the acute care provided in hospitals is for elderly people. Frailty is a common clinical condition among these patients. Frail patients are vulnerable to undergoing adverse events, to developing geriatric syndromes and to experiencing functional decline during or due to hospitalization. The strategy for providing specialized geriatric care to these hospitalized frail elderly patients currently consists of care provision either by specialized departments or by specialized teams who adopt comprehensive geriatric assessment. Even so, financial and human resources are insufficient to meet the needs of all hospitalized frail elderly patients who require comprehensive geriatric assessment. New innovative and more efficient geriatric interventions, in which the priorities of the patients themselves should be the main focus, should be developed and implemented, and professionals in all specialties should be educated in applying the fundamentals of geriatric medicine to their frail elderly patients. In the evaluation of such interventions, patient-reported outcomes should play a major role, in addition to the more traditional outcome measures of effectiveness, quality of care and cost-effectiveness.},
  journal = {Interdisciplinary Topics in Gerontology and Geriatrics},
  keywords = {Activities of Daily Living,Adaptation; Psychological,Aged,Aged; 80 and over,Female,Frail Elderly,Geriatrics,Hospital Units,Hospitalization,Humans,Length of Stay,Male,Patient Care Team,Prognosis,Referral and Consultation,Risk Assessment,Vulnerable Populations},
  language = {ENG},
  pmid = {26301983}
}

@article{bandeen-roche15,
  title = {Frailty in {{Older Adults}}: {{A Nationally Representative Profile}} in the {{United States}}},
  shorttitle = {Frailty in {{Older Adults}}},
  author = {{Bandeen-Roche}, Karen and Seplaki, Christopher L. and Huang, Jin and Buta, Brian and Kalyani, Rita R. and Varadhan, Ravi and Xue, Qian-Li and Walston, Jeremy D. and Kasper, Judith D.},
  year = {2015},
  month = nov,
  volume = {70},
  pages = {1427--1434},
  issn = {1079-5006},
  doi = {10.1093/gerona/glv133},
  abstract = {Background.
Frailty assessment provides a means of identifying older adults most vulnerable to adverse outcomes. Attention to frailty in clinical practice is more likely with better understanding of its prevalence and associations with patient characteristics. We sought to provide national estimates of frailty in older people.

Methods.
A popular, validated frailty phenotype proposed by Fried and colleagues was applied to 7,439 participants in the 2011 baseline of the National Health and Aging Trends Study, a national longitudinal study of persons aged 65 and older. All measures drew on a 2-hour in-person interview. Weighted estimates of frailty prevalence were obtained.

Results.
Fifteen percent (95\% CI: 14\%, 16\%) of the older non-nursing home population is frail, and 45\% is prefrail (95\% CI: 44\%, 47\%). Frailty is more prevalent at older ages, among women, racial and ethnic minorities, those in supportive residential settings, and persons of lower income. Independently of these characteristics, frailty prevalence varies substantially across geographic regions. Chronic disease and disability prevalence increase steeply with frailty. Among the frail, 42\% were hospitalized in the previous year, compared to 22\% of the prefrail and 11\% of persons considered robust. Hip, back, and heart surgery in the last year were associated with frailty. Over half of frail persons had a fall in the previous year.

Conclusions.
Our findings support the importance of frailty in late-life health etiology and potential value of frailty as a marker of risk for adverse health outcomes and as a means of identifying opportunities for intervention in clinical practice and public health policy.},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  number = {11},
  pmcid = {PMC4723664},
  pmid = {26297656}
}

@article{bastos-barbosa12,
  title = {Association of {{Frailty Syndrome}} in the {{Elderly With Higher Blood Pressure}} and {{Other Cardiovascular Risk Factors}}},
  author = {{Bastos-Barbosa}, R. G. and Ferriolli, E. and Coelho, E. B. and Moriguti, J. C. and Nobre, F. and {da Costa Lima}, N. K.},
  year = {2012},
  month = nov,
  volume = {25},
  pages = {1156--1161},
  issn = {0895-7061, 1941-7225},
  doi = {10.1038/ajh.2012.99},
  journal = {American Journal of Hypertension},
  language = {en},
  number = {11}
}

@article{bellamy17,
  title = {Modified {{Frailty Index Is}} an {{Effective Risk Assessment Tool}} in {{Primary Total Hip Arthroplasty}}},
  author = {Bellamy, Jaime L. and Runner, Robert P. and Vu, CatPhuong Cathy L. and Schenker, Mara L. and Bradbury, Thomas L. and Roberson, James R.},
  year = {2017},
  month = may,
  issn = {08835403},
  doi = {10.1016/j.arth.2017.04.056},
  journal = {The Journal of Arthroplasty},
  language = {en}
}

@article{bellamy17a,
  title = {Modified {{Frailty Index Is}} an {{Effective Risk Assessment Tool}} in {{Primary Total Hip Arthroplasty}}},
  author = {Bellamy, Jaime L. and Runner, Robert P. and Vu, CatPhuong Cathy L. and Schenker, Mara L. and Bradbury, Thomas L. and Roberson, James R.},
  year = {2017},
  month = may,
  issn = {08835403},
  doi = {10.1016/j.arth.2017.04.056},
  journal = {The Journal of Arthroplasty},
  language = {en}
}

@article{bernheim16,
  title = {Accounting {{For Patients}}' {{Socioeconomic Status Does Not Change Hospital Readmission Rates}}},
  author = {Bernheim, Susannah M. and Parzynski, Craig S. and Horwitz, Leora and Lin, Zhenqiu and Araas, Michael J. and Ross, Joseph S. and Drye, Elizabeth E. and Suter, Lisa G. and Normand, Sharon-Lise T. and Krumholz, Harlan M.},
  year = {2016},
  month = aug,
  volume = {35},
  pages = {1461--1470},
  issn = {1544-5208},
  doi = {10.1377/hlthaff.2015.0394},
  abstract = {There is an active public debate about whether patients' socioeconomic status should be included in the readmission measures used to determine penalties in Medicare's Hospital Readmissions Reduction Program (HRRP). Using the current Centers for Medicare and Medicaid Services methodology, we compared risk-standardized readmission rates for hospitals caring for high and low proportions of patients of low socioeconomic status (as defined by their Medicaid status or neighborhood income). We then calculated risk-standardized readmission rates after additionally adjusting for patients' socioeconomic status. Our results demonstrate that hospitals caring for large proportions of patients of low socioeconomic status have readmission rates similar to those of other hospitals. Moreover, readmission rates calculated with and without adjustment for patients' socioeconomic status are highly correlated. Readmission rates of hospitals caring for patients of low socioeconomic status changed by approximately 0.1~percent with adjustment for patients' socioeconomic status, and only 3-4~percent fewer such hospitals reached the threshold for payment penalty in Medicare's HRRP. Overall, adjustment for socioeconomic status does not change hospital results in meaningful ways.},
  journal = {Health Affairs (Project Hope)},
  keywords = {Disparities,Quality Of Care,Safety-Net Systems},
  language = {eng},
  number = {8},
  pmid = {27503972}
}

@article{blum14,
  title = {{{THE IMPACT OF MEASURES OF SOCIOECONOMIC STATUS ON HOSPITAL PROFILING IN NEW YORK CITY}}},
  author = {Blum, Alexander B. and Egorova, Natalia N. and Sosunov, Eugene A. and Gelijns, Annetine C. and DuPree, Erin and Moskowitz, Alan J. and Federman, Alex D. and Ascheim, Deborah D. and Keyhani, Salomeh},
  year = {2014},
  month = may,
  volume = {7},
  pages = {391--397},
  issn = {1941-7713},
  doi = {10.1161/CIRCOUTCOMES.113.000520},
  abstract = {Background
Current 30-day readmission models used by the Center for Medicare and Medicaid Services for the purpose of hospital-level comparisons lack measures of socioeconomic status (SES). We examined whether the inclusion of a SES measure in 30-day congestive heart failure (CHF) readmission models changed hospital risk standardized readmission rates (RSRR) in New York City (NYC) hospitals.

Methods and Results
Using a Centers for Medicare \& Medicaid Services (CMS)-like model we estimated 30-day hospital-level RSRR by adjusting for age, gender and comorbid conditions. Next, we examined how hospital RSRRs changed relative to the New York City mean with inclusion of the Agency for Healthcare Research and Quality (AHRQ) validated SES index score. In a secondary analysis, we examined whether inclusion of the AHRQ SES Index score in 30-day readmission models disproportionately impacted the RSRR of minority-serving hospitals., Higher AHRQ SES scores, indicators of higher socioeconomic status, were associated with lower odds, 0.99, of 30-day readmission (p{$<$} 0.019). The addition of the AHRQ SES index did not change the model's C statistic (0.63). After adjustment for the AHRQ SES index, one hospital changed status from ``worse than the NYC average'' to ``no different than the NYC average''. After adjustment for the AHRQ SES index, one NYC minority-serving hospital was re-classified from ``worse'' to ``no different than average''.

Conclusions
While patients with higher SES were less likely to be admitted, the impact of SES on readmission was very small. In NYC, inclusion of the AHRQ SES score in a CMS based model did not impact hospital-level profiling based on 30-day readmission.},
  journal = {Circulation. Cardiovascular quality and outcomes},
  number = {3},
  pmcid = {PMC4072036},
  pmid = {24823956}
}

@misc{bokov20,
  title = {Bokov/{{FreeFI}}: {{First Release}}},
  shorttitle = {Bokov/{{FreeFI}}},
  author = {Bokov, Alex},
  year = {2020},
  month = sep,
  doi = {10.5281/ZENODO.4053088},
  abstract = {Open Frailty Index: Rockwood methodology applied to EMR data},
  copyright = {Open Access},
  howpublished = {Zenodo}
}

@article{brahmbhatt16,
  title = {Gender and Frailty Predict Poor Outcomes in Infrainguinal Vascular Surgery},
  author = {Brahmbhatt, Reshma and Brewster, Luke P. and Shafii, Susan and Rajani, Ravi R. and Veeraswamy, Ravi and Salam, Atef and Dodson, Thomas F. and Arya, Shipra},
  year = {2016},
  month = mar,
  volume = {201},
  pages = {156--165},
  issn = {1095-8673},
  doi = {10.1016/j.jss.2015.10.026},
  abstract = {BACKGROUND: Women have poorer outcomes after vascular surgery as compared to men as shown by studies recently. Frailty is also an independent risk factor for postoperative morbidity and mortality. This study examines the interplay of gender and frailty on outcomes after infrainguinal vascular procedures.
MATERIALS AND METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was used to identify all patients who underwent infrainguinal vascular procedures from 2005-2012. Frailty was measured using a modified frailty index (mFI; derived from the Canadian Study of Health and Aging). Univariate and multivariate analysis were performed to investigate the association of preoperative frailty and gender, on postoperative outcomes.
RESULTS: Of 24,645 patients (92\% open, 8\% endovascular), there were 533 deaths (2.2\%) and 6198 (25.1\%) major complications within 30 d postoperatively. Women were more frail (mean mFI = 0.269) than men (mean mFI = 0.259; P {$<$} 0.001). Women and frail patients (mFI{$>$}0.25) were more likely to have a major morbidity (P {$<$} 0.001) or mortality (P {$<$} 0.001) with the highest risk in frail women. On multivariate logistic regression analysis, female gender and increasing mFI were independently significantly associated with mortality (P {$<$} 0.05) as well as major complications. The interaction of gender and frailty in multivariate analysis showed the highest adjusted 30-d mortality and morbidity in frail females at 2.8\% and 30.1\%, respectively and that was significantly higher (P {$<$} 0.001) than nonfrail males, nonfrail females and frail males.
CONCLUSIONS: Female gender and frailty are both associated with increased risk of complications and death following infrainguinal vascular procedures with the highest risk in frail females. Further studies are needed to explore the mechanisms of interaction of gender and frailty and its effect on long-term outcomes for peripheral vascular disease.},
  journal = {The Journal of Surgical Research},
  keywords = {Aged,Aged; 80 and over,Canada,Complications,Female,Frail Elderly,Frailty,Gender,Humans,Infrainguinal bypass,Lower Extremity,Male,Middle Aged,Outcomes,Postoperative Complications,Retrospective Studies,Revascularization,Sex Factors,United States,Vascular Surgical Procedures},
  language = {eng},
  number = {1},
  pmid = {26850197}
}

@article{braveman11,
  title = {The Social Determinants of Health: Coming of Age},
  shorttitle = {The Social Determinants of Health},
  author = {Braveman, Paula and Egerter, Susan and Williams, David R.},
  year = {2011},
  volume = {32},
  pages = {381--398},
  issn = {1545-2093},
  doi = {10.1146/annurev-publhealth-031210-101218},
  abstract = {In the United States, awareness is increasing that medical care alone cannot adequately improve health overall or reduce health disparities without also addressing where and how people live. A critical mass of relevant knowledge has accumulated, documenting associations, exploring pathways and biological mechanisms, and providing a previously unavailable scientific foundation for appreciating the role of social factors in health. We review current knowledge about health effects of social (including economic) factors, knowledge gaps, and research priorities, focusing on upstream social determinants-including economic resources, education, and racial discrimination-that fundamentally shape the downstream determinants, such as behaviors, targeted by most interventions. Research priorities include measuring social factors better, monitoring social factors and health relative to policies, examining health effects of social factors across lifetimes and generations, incrementally elucidating pathways through knowledge linkage, testing multidimensional interventions, and addressing political will as a key barrier to translating knowledge into action.},
  journal = {Annual Review of Public Health},
  keywords = {Health Policy,Health Status Disparities,Healthcare Disparities,Humans,Politics,Socioeconomic Factors,United States},
  language = {eng},
  pmid = {21091195}
}

@article{buckinx15,
  title = {Burden of Frailty in the Elderly Population: Perspectives for a Public Health Challenge},
  shorttitle = {Burden of Frailty in the Elderly Population},
  author = {Buckinx, Fanny and Rolland, Yves and Reginster, Jean-Yves and Ricour, C{\'e}line and Petermans, Jean and Bruy{\`e}re, Olivier},
  year = {2015},
  month = apr,
  volume = {73},
  issn = {0778-7367},
  doi = {10.1186/s13690-015-0068-x},
  abstract = {Frailty is a major health condition associated with ageing. Although the concept is almost universally accepted, its operational definition remains controversial. Anyway, this geriatric condition represents a huge potential public health issue at both the patient and the societal levels because of its multiple clinical, societal consequences and its dynamic nature. Here, we review existing definitions and assessment tools for frailty, we highlight consequences of this geriatric condition and we discuss the importance of its screening and prevention to limit its public health burden.},
  journal = {Archives of Public Health},
  number = {1},
  pmcid = {PMC4392630},
  pmid = {25866625}
}

@article{buigues15,
  title = {Frailty Syndrome and Pre-Operative Risk Evaluation: {{A}} Systematic Review},
  shorttitle = {Frailty Syndrome and Pre-Operative Risk Evaluation},
  author = {Buigues, Cristina and {Juarros-Folgado}, Pilar and {Fern{\'a}ndez-Garrido}, Julio and {Navarro-Mart{\'i}nez}, Rut and Cauli, Omar},
  year = {2015},
  month = nov,
  volume = {61},
  pages = {309--321},
  issn = {0167-4943},
  doi = {10.1016/j.archger.2015.08.002},
  abstract = {Frailty is a geriatric syndrome characterized by the clinical presentation of identifiable physical alterations and decreased physiological reserve. The assessment of frailty syndrome has been recently related with post-surgical outcomes and overall mortality in older individuals. We performed searches in Pubmed, Embase, Scopus, SCIELO and IME (Spanish medical index) databases from their start dates to February 2014 for original papers about the identification of the relationship between frailty and pre-operative risk evaluation in people aged 65 and over. We followed criteria of systematic PRISMA guidelines. Two independent reviewers extracted descriptive information on frailty criteria and outcomes from the selected papers: of the 77 articles retrieved from the searches, 32 met the study inclusion criteria. Severity of frailty syndrome significantly correlated with post-surgical mortality rates and with many although not all post-surgical complications. These relationships emerge in different type of surgical procedures and patients' features. The comparison of diagnostic tools to assess frailty in pre-operative risk evaluation are very few and to date, no recommendation can be made about the best scale to measure it. Assessment of frailty syndrome should be added in the pre-operative risk assessment in older individuals.},
  journal = {Archives of Gerontology and Geriatrics},
  keywords = {Ageing,Frailty,Mortality,Surgery risk},
  number = {3}
}

@misc{bureau00,
  title = {2014 {{National Population Projections Tables}}},
  author = {Bureau, US Census},
  abstract = {These tables feature 2014 National Population Projections by age, sex, race, Hispanic origin, and nativity. Table 3:  Projections of the Population by Sex and Selected Age Groups for the United States: 2015 to 2060},
  howpublished = {https://www2.census.gov/programs-surveys/popproj/tables/2014/2014-summary-tables/np2014-t3.xls},
  language = {EN-US}
}

@article{cesari14,
  title = {The Frailty Phenotype and the Frailty Index: Different Instruments for Different Purposes},
  shorttitle = {The Frailty Phenotype and the Frailty Index},
  author = {Cesari, M. and Gambassi, G. and {Abellan van Kan}, G. and Vellas, B.},
  year = {2014},
  month = jan,
  volume = {43},
  pages = {10--12},
  issn = {0002-0729, 1468-2834},
  doi = {10.1093/ageing/aft160},
  journal = {Age and Ageing},
  language = {en},
  number = {1}
}

@article{chamberlain16,
  title = {Frailty {{Trajectories}} in an {{Elderly Population}}-{{Based Cohort}}},
  author = {Chamberlain, Alanna M. and Finney Rutten, Lila J. and Manemann, Sheila M. and Yawn, Barbara P. and Jacobson, Debra J. and Fan, Chun and Grossardt, Brandon R. and Roger, V{\'e}ronique L. and St. Sauver, Jennifer L.},
  year = {2016},
  month = feb,
  volume = {64},
  pages = {285--292},
  issn = {00028614},
  doi = {10.1111/jgs.13944},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {2}
}

@article{charlson87,
  title = {A New Method of Classifying Prognostic Comorbidity in Longitudinal Studies: Development and Validation},
  shorttitle = {A New Method of Classifying Prognostic Comorbidity in Longitudinal Studies},
  author = {Charlson, M. E. and Pompei, P. and Ales, K. L. and MacKenzie, C. R.},
  year = {1987},
  volume = {40},
  pages = {373--383},
  issn = {0021-9681},
  abstract = {The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12\% (181); "1-2", 26\% (225); "3-4", 52\% (71); and "greater than or equal to 5", 85\% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8\% (588); "1", 25\% (54); "2", 48\% (25); "greater than or equal to 3", 59\% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.},
  journal = {Journal of Chronic Diseases},
  keywords = {Actuarial Analysis,Age Factors,Breast Neoplasms,Epidemiologic Methods,Female,Follow-Up Studies,Humans,Longitudinal Studies,Morbidity,New York City,Prognosis,Prospective Studies,Risk},
  language = {ENG},
  number = {5},
  pmid = {3558716}
}

@article{chee16,
  title = {Current {{State}} of {{Value}}-{{Based Purchasing Programs}}},
  author = {Chee, Tingyin T. and Ryan, Andrew M. and Wasfy, Jason H. and Borden, William B.},
  year = {2016},
  month = may,
  volume = {133},
  pages = {2197--2205},
  issn = {0009-7322},
  doi = {10.1161/CIRCULATIONAHA.115.010268},
  abstract = {The United States healthcare system is rapidly moving toward rewarding value. Recent legislation, such as the Affordable Care Act and the Medicare Access and CHIP Reauthorization Act (MACRA), solidified the role of value-based payment in Medicare. Many private insurers are following Medicare's lead. Much of the policy attention has been on programs such as accountable care organizations and bundled payments; yet, value-based purchasing (VBP) or pay-for-performance, defined as providers being paid fee-for-service with payment adjustments up or down based on value metrics, remains a core element of value payment in MACRA and will likely remain so for the foreseeable future. This review article summarizes the current state of VBP programs and provides analysis of the strengths, weaknesses, and opportunities for the future. Multiple inpatient and outpatient VBP programs have been implemented and evaluated, with the impact of those programs being marginal. Opportunities to enhance the performance of VBP programs include improving the quality measurement science, strengthening both the size and design of incentives, reducing health disparities, establishing broad outcome measurement, choosing appropriate comparison targets, and determining the optimal role of VBP relative to alternative payment models. VBP programs will play a significant role in healthcare delivery for years to come, and they serve as an opportunity for providers to build the infrastructure needed for value-oriented care.},
  journal = {Circulation},
  number = {22},
  pmcid = {PMC5378385},
  pmid = {27245648}
}

@article{clegg13a,
  title = {Frailty in Elderly People},
  author = {Clegg, Andrew and Young, John and Iliffe, Steve and Rikkert, Marcel Olde and Rockwood, Kenneth},
  year = {2013},
  month = mar,
  volume = {381},
  pages = {752--762},
  issn = {01406736},
  doi = {10.1016/S0140-6736(12)62167-9},
  journal = {The Lancet},
  language = {en},
  number = {9868}
}

@article{clegg16a,
  title = {Development and Validation of an Electronic Frailty Index Using Routine Primary Care Electronic Health Record Data},
  author = {Clegg, Andrew and Bates, Chris and Young, John and Ryan, Ronan and Nichols, Linda and Ann Teale, Elizabeth and Mohammed, Mohammed A. and Parry, John and Marshall, Tom},
  year = {2016},
  month = may,
  volume = {45},
  pages = {353--360},
  issn = {0002-0729, 1468-2834},
  doi = {10.1093/ageing/afw039},
  journal = {Age and Ageing},
  language = {en},
  number = {3}
}

@article{collard12,
  title = {Prevalence of {{Frailty}} in {{Community}}-{{Dwelling Older Persons}}: {{A Systematic Review}}},
  shorttitle = {Prevalence of {{Frailty}} in {{Community}}-{{Dwelling Older Persons}}},
  author = {Collard, Rose M. and Boter, Han and Schoevers, Robert A. and Oude Voshaar, Richard C.},
  year = {2012},
  month = aug,
  volume = {60},
  pages = {1487--1492},
  issn = {00028614},
  doi = {10.1111/j.1532-5415.2012.04054.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {8}
}

@book{committeeonthelong-runmacroeconomiceffectsoftheagingu.s.population--phaseii15,
  title = {The {{Growing Gap}} in {{Life Expectancy}} by {{Income}}: {{Implications}} for {{Federal Programs}} and {{Policy Responses}}},
  shorttitle = {The {{Growing Gap}} in {{Life Expectancy}} by {{Income}}},
  author = {{Committee on the Long-Run Macroeconomic Effects of the Aging U.S. Population\textemdash Phase II} and {Committee on Population} and {Division of Behavioral and Social Sciences and Education} and {Board on Mathematical Sciences and Their Applications} and {Division on Engineering and Physical Sciences} and {The National Academies of Sciences, Engineering, and Medicine}},
  year = {2015},
  publisher = {{National Academies Press (US)}},
  address = {{Washington (DC)}},
  abstract = {The U.S. population is aging. Social Security projections suggest that between 2013 and 2050, the population aged 65 and over will almost double, from 45 million to 86 million. One key driver of population aging is ongoing increases in life expectancy. Average U.S. life expectancy was 67 years for males and 73 years for females five decades ago; the averages are now 76 and 81, respectively. It has long been the case that better-educated, higher-income people enjoy longer life expectancies than less-educated, lower-income people. The causes include early life conditions, behavioral factors (such as nutrition, exercise, and smoking behaviors), stress, and access to health care services, all of which can vary across education and income. Our major entitlement programs \textendash{} Medicare, Medicaid, Social Security, and Supplemental Security Income \textendash{} have come to deliver disproportionately larger lifetime benefits to higher-income people because, on average, they are increasingly collecting those benefits over more years than others. This report studies the impact the growing gap in life expectancy has on the present value of lifetime benefits that people with higher or lower earnings will receive from major entitlement programs. The analysis presented in The Growing Gap in Life Expectancy by Income goes beyond an examination of the existing literature by providing the first comprehensive estimates of how lifetime benefits are affected by the changing distribution of life expectancy. The report also explores, from a lifetime benefit perspective, how the growing gap in longevity affects traditional policy analyses of reforms to the nation's leading entitlement programs. This in-depth analysis of the economic impacts of the longevity gap will inform debate and assist decision makers, economists, and researchers.},
  copyright = {Copyright 2015 by the National Academy of Sciences. All rights reserved.},
  isbn = {978-0-309-31707-8},
  language = {eng},
  lccn = {NBK321312},
  pmid = {26468563}
}

@article{daley97,
  title = {Validating Risk-Adjusted Surgical Outcomes: Site Visit Assessment of Process and Structure. {{National VA Surgical Risk Study}}},
  shorttitle = {Validating Risk-Adjusted Surgical Outcomes},
  author = {Daley, J. and Forbes, M. G. and Young, G. J. and Charns, M. P. and Gibbs, J. O. and Hur, K. and Henderson, W. and Khuri, S. F.},
  year = {1997},
  month = oct,
  volume = {185},
  pages = {341--351},
  issn = {1072-7515},
  abstract = {BACKGROUND: Risk-adjusted mortality and morbidity rates are often used as measures of the quality of surgical care. This study was conducted to determine the validity of risk-adjusted surgical morbidity and mortality rates as measures of quality of care by assessing the process and structure of care in surgical services with higher-than-expected and lower-than-expected risk-adjusted 30-day mortality and morbidity rates.
STUDY DESIGN: A structural survey of 44 Veterans Affairs Medical Center surgical services and site visits to 20 surgical services with higher-than-expected and lower-than-expected risk-adjusted outcomes were conducted. Main outcome measures included assessment of technology and equipment, technical competence of staff, leadership, relationship with other services, monitoring of quality of care, coordination of work, relationship with affiliated institutions, and overall quality of care.
RESULTS: Surgical services with lower-than-expected risk-adjusted surgical morbidity and mortality rates had significantly more equipment available in surgical intensive care units than did services with higher-than-expected outcomes (4.3 versus 2.9, p {$<$} 0.05). Site-visitor ratings of overall quality of care were significantly higher for surgical services with lower-than-expected morbidity and mortality rates (6.1 versus 4.5 for high outliers, p {$<$} 0.05); technology and equipment were rated significantly better among low-outlier services (7.1 versus 4.8 for high outliers, p {$<$} 0.001). Masked site-visit teams correctly predicted the outlier status (high versus low) of 17 of the 20 surgical services visited (p {$<$} 0.001).
CONCLUSIONS: Significant differences in several dimensions of process and structure of the delivery of surgical care are associated with differences in risk-adjusted surgical morbidity and mortality rates among 44 Veterans Affairs Medical Centers.},
  journal = {Journal of the American College of Surgeons},
  keywords = {Hospital Mortality,Hospitals; Veterans,Humans,Logistic Models,Outcome Assessment (Health Care),Quality Indicators; Health Care,Reproducibility of Results,Risk Assessment,Surgical Procedures; Operative,United States,United States Department of Veterans Affairs},
  language = {eng},
  number = {4},
  pmid = {9328382}
}

@article{deyo92,
  title = {Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Databases},
  author = {Deyo, R. A. and Cherkin, D. C. and Ciol, M. A.},
  year = {1992},
  month = jun,
  volume = {45},
  pages = {613--619},
  issn = {0895-4356},
  abstract = {Administrative databases are increasingly used for studying outcomes of medical care. Valid inferences from such data require the ability to account for disease severity and comorbid conditions. We adapted a clinical comorbidity index, designed for use with medical records, for research relying on International Classification of Diseases (ICD-9-CM) diagnosis and procedure codes. The association of this adapted index with health outcomes and resource use was then examined with a sample of Medicare beneficiaries who underwent lumbar spine surgery in 1985 (n = 27,111). The index was associated in the expected direction with postoperative complications, mortality, blood transfusion, discharge to nursing home, length of hospital stay, and hospital charges. These associations were observed whether the index incorporated data from multiple hospitalizations over a year's time, or just from the index surgical admission. They also persisted after controlling for patient age. We conclude that the adapted comorbidity index will be useful in studies of disease outcome and resource use employing administrative databases.},
  journal = {Journal of Clinical Epidemiology},
  keywords = {Aged,Comorbidity,Databases; Factual,Female,Humans,Lumbar Vertebrae,Male,Medical Records,Medicare,Spinal Diseases,Treatment Outcome,United States},
  language = {eng},
  number = {6},
  pmid = {1607900}
}

@article{deyo92a,
  title = {Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Databases},
  author = {Deyo, R},
  year = {1992},
  month = jun,
  volume = {45},
  pages = {613--619},
  issn = {08954356},
  doi = {10.1016/0895-4356(92)90133-8},
  journal = {Journal of Clinical Epidemiology},
  language = {en},
  number = {6}
}

@article{dindo04,
  title = {Classification of {{Surgical Complications}}},
  author = {Dindo, Daniel and Demartines, Nicolas and Clavien, Pierre-Alain},
  year = {2004},
  month = aug,
  volume = {240},
  pages = {205--213},
  issn = {0003-4932},
  doi = {10.1097/01.sla.0000133083.54934.ae},
  abstract = {The lack of a uniform way of reporting complications hampers interpretation of surgical outcome data and quality assessment. The authors revisited a previously reported classification of complications and propose a new grading system. The new classification was tested in a cohort of 6336 patients undergoing general surgery and through an international survey.},
  journal = {Annals of Surgery},
  number = {2},
  pmcid = {PMC1360123},
  pmid = {15273542}
}

@article{doran17,
  title = {Impact of {{Provider Incentives}} on {{Quality}} and {{Value}} of {{Health Care}}},
  author = {Doran, Tim and Maurer, Kristin A. and Ryan, Andrew M.},
  year = {2017},
  month = mar,
  volume = {38},
  pages = {449--465},
  issn = {1545-2093},
  doi = {10.1146/annurev-publhealth-032315-021457},
  abstract = {The use of financial incentives to improve quality in health care has become widespread. Yet evidence on the effectiveness of incentives suggests that they have generally had limited impact on the value of care and have not led to better patient outcomes. Lessons from social psychology and behavioral economics indicate that incentive programs in health care have not been effectively designed to achieve their intended impact. In the United States, Medicare's Hospital Readmission Reduction Program and Hospital Value-Based Purchasing Program, created under the Affordable Care Act (ACA), provide evidence on how variations in the design of incentive programs correspond with differences in effect. As financial incentives continue to be used as a tool to increase the value and quality of health care, improving the design of programs will be crucial to ensure their success.},
  journal = {Annual Review of Public Health},
  keywords = {health care,pay-for-performance,quality,value,value-based purchasing},
  language = {eng},
  pmid = {27992731}
}

@article{duan08,
  title = {Disparities in {{Defining Disparities}}: {{Statistical Conceptual Frameworks}}},
  shorttitle = {Disparities in {{Defining Disparities}}},
  author = {Duan, Naihua and Meng, Xiao-Li and Lin, Julia Y. and Chen, Chih-nan and Alegria, Margarita},
  year = {2008},
  month = sep,
  volume = {27},
  pages = {3941--3956},
  issn = {0277-6715},
  doi = {10.1002/sim.3283},
  abstract = {Motivated by the need to meaningfully implement the Institute of Medicine's (IOM's) definition of health care disparity, this paper proposes statistical frameworks that lay out explicitly the needed causal assumptions for defining disparity measures. Our key emphasis is that a scientifically defensible disparity measure must take into account the direction of the causal relationship between allowable covariates that are not considered to be contributors to disparity and non-allowable covariates that are considered to be contributors to disparity, to avoid flawed disparity measures based on implausible populations that are not relevant for clinical or policy decisions. However, these causal relationships are usually unknown and undetectable from observed data. Consequently, we must make strong causal assumptions in order to proceed. Two frameworks are proposed in this paper, one is the conditional disparity framework under the assumption that allowable covariates impact non-allowable covariates but not vice versa. The other is the marginal disparity framework under the assumption that non-allowable covariates impact allowable ones but not vice versa. We establish theoretical conditions under which the two disparity measures are the same, and present a theoretical example showing that the difference between the two disparity measures can be arbitrarily large. Using data from the Collaborative Psychiatric Epidemiology Survey, we also provide an example where the conditional disparity is misled by Simpson's paradox, while the marginal disparity approach handles it correctly.},
  journal = {Statistics in medicine},
  number = {20},
  pmcid = {PMC2715701},
  pmid = {18626925}
}

@article{dwyer-lindgren17,
  title = {Inequalities in {{Life Expectancy Among US Counties}}, 1980 to 2014: {{Temporal Trends}} and {{Key Drivers}}},
  shorttitle = {Inequalities in {{Life Expectancy Among US Counties}}, 1980 to 2014},
  author = {{Dwyer-Lindgren}, Laura and {Bertozzi-Villa}, Amelia and Stubbs, Rebecca W. and Morozoff, Chloe and Mackenbach, Johan P. and van Lenthe, Frank J. and Mokdad, Ali H. and Murray, Christopher J. L.},
  year = {2017},
  month = jul,
  volume = {177},
  pages = {1003--1011},
  issn = {2168-6106},
  doi = {10.1001/jamainternmed.2017.0918},
  abstract = {{$<$}h3{$>$}Importance{$<$}/h3{$><$}p{$>$}Examining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policy makers, clinicians, and researchers seeking to reduce disparities and increase longevity.{$<$}/p{$><$}h3{$>$}Objective{$<$}/h3{$><$}p{$>$}To estimate annual life tables by county from 1980 to 2014; describe trends in geographic inequalities in life expectancy and age-specific risk of death; and assess the proportion of variation in life expectancy explained by variation in socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.{$<$}/p{$><$}h3{$>$}Design, Setting, and Participants{$<$}/h3{$><$}p{$>$}Annual county-level life tables were constructed using small area estimation methods from deidentified death records from the National Center for Health Statistics (NCHS), and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. Measures of geographic inequality in life expectancy and age-specific mortality risk were calculated. Principal component analysis and ordinary least squares regression were used to examine the county-level association between life expectancy and socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.{$<$}/p{$><$}h3{$>$}Exposures{$<$}/h3{$><$}p{$>$}County of residence.{$<$}/p{$><$}h3{$>$}Main Outcomes and Measures{$<$}/h3{$><$}p{$>$}Life expectancy at birth and age-specific mortality risk.{$<$}/p{$><$}h3{$>$}Results{$<$}/h3{$><$}p{$>$}Counties were combined as needed to create stable units of analysis over the period 1980 to 2014, reducing the number of areas analyzed from 3142 to 3110. In 2014, life expectancy at birth for both sexes combined was 79.1 (95\% uncertainty interval [UI], 79.0-79.1) years overall, but differed by 20.1 (95\% UI, 19.1-21.3) years between the counties with the lowest and highest life expectancy. Absolute geographic inequality in life expectancy increased between 1980 and 2014. Over the same period, absolute geographic inequality in the risk of death decreased among children and adolescents, but increased among older adults. Socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors explained 60\%, 74\%, and 27\% of county-level variation in life expectancy, respectively. Combined, these factors explained 74\% of this variation. Most of the association between socioeconomic and race/ethnicity factors and life expectancy was mediated through behavioral and metabolic risk factors.{$<$}/p{$><$}h3{$>$}Conclusions and Relevance{$<$}/h3{$><$}p{$>$}Geographic disparities in life expectancy among US counties are large and increasing. Much of the variation in life expectancy among counties can be explained by a combination of socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors. Policy action targeting socioeconomic factors and behavioral and metabolic risk factors may help reverse the trend of increasing disparities in life expectancy in the United States.{$<$}/p{$>$}},
  journal = {JAMA Internal Medicine},
  number = {7}
}

@article{eapen15,
  title = {Utility of {{Socioeconomic Status}} in {{Predicting}} 30-{{Day Outcomes After Heart Failure Hospitalization}}},
  author = {Eapen, Zubin J. and McCoy, Lisa A. and Fonarow, Gregg C. and Yancy, Clyde W. and Miranda, Marie Lynn and Peterson, Eric D. and Califf, Robert M. and Hernandez, Adrian F.},
  year = {2015},
  month = may,
  volume = {8},
  pages = {473--480},
  issn = {1941-3289},
  doi = {10.1161/CIRCHEARTFAILURE.114.001879},
  abstract = {Background
An individual's socioeconomic status (SES) is associated with health outcomes and mortality, yet it is unknown whether accounting for SES can improve risk-adjustment models for 30-day outcomes among Centers for Medicare \& Medicaid Services (CMS) beneficiaries hospitalized with heart failure (HF).

Methods and Results
We linked clinical data on hospitalized HF patients in the Get With The Guidelines\textregistered -HF\texttrademark{} database (01/2005\textendash 12/2011) with CMS claims and county-level SES data from the 2012 Area Health Resources Files. We compared the discriminatory capabilities of multivariable models that adjusted for SES, patient, and/or hospital characteristics to determine whether county-level SES data improved prediction or changed hospital rankings for 30-day all-cause mortality and rehospitalization. After adjusting for patient and hospital characteristics, median household income (per \$5,000 increase) was inversely associated with odds of 30-day mortality (OR 0.97, 95\% CI 0.95\textendash 1.00, p=0.032), and the percentage of persons with at least a high school diploma (per 5 unit increase) was associated with lower odds of 30-day rehospitalization (OR 0.95, 95\% CI 0.91\textendash 0.99).After adjustment for county-level SES data, relative to whites, Hispanic ethnicity (OR 0.70, 95\% CI 0.58, 0.83) and black race (OR 0.57, 95\% CI: 0.50\textendash 0.65) remained significantly associated with lower 30-day mortality, but had similar 30-day rehospitalization. County-level SES did not improve risk adjustment or change hospital rankings for 30-day mortality or rehospitalization.

Conclusions
County-level SES data are modestly associated with 30-day outcomes for CMS beneficiaries hospitalized with HF, but do not improve risk adjustment models based on patient characteristics alone.},
  journal = {Circulation. Heart failure},
  number = {3},
  pmcid = {PMC4439274},
  pmid = {25747700}
}

@article{elixhauser98,
  title = {Comorbidity {{Measures}} for {{Use}} with {{Administrative Data}}},
  author = {Elixhauser, Anne and Steiner, Claudia and Harris, D Robert and Coffey, Rosanna M},
  year = {1998},
  pages = {8--27},
  journal = {Medical Care}
}

@techreport{enticott20,
  title = {Leadership {{Perspectives}} on {{Learning Health Systems}}: A Qualitative Study},
  shorttitle = {Leadership {{Perspectives}} on {{Learning Health Systems}}},
  author = {Enticott, Joanne and Braaf, Sandy and Johnson, Alison and Jones, Angela and Teede, Helena},
  year = {2020},
  month = jun,
  institution = {{In Review}},
  doi = {10.21203/rs.3.rs-35988/v1},
  abstract = {Abstract                        Background:             Integrated utilisation of digital health data has the power to transform healthcare to deliver more efficient and effective services, and the learning health system (LHS) is emerging as a model to achieve this. The LHS uses routine data from service delivery and patient care to generate knowledge to continuously improve healthcare. The aim of this project was to explore key features of a successful and sustainable LHS to inform implementation in an Academic Health Science Centre context.             Methods:             We purposively identified and conducted semi-structured qualitative interviews with leaders, experienced in supporting or developing data driven innovations in healthcare. A thematic analysis using NVivo was undertaken.             Results:             Analysis of 26 interviews revealed five themes thought to be integral in an effective, sustainable LHS: (1) Systematic approaches and iterative, continuous learning with implementation into healthcare contributing to new best-practice care; (2) Broad stakeholder, clinician and academic engagement, with collective vision, leadership, governance and a culture of trust, transparency and co-design; (3) Skilled workforce, capability and capacity building; (4) Resources with sustained investment over time and; (5) Data access, systems and processes being integral to a sustainable LHS.             Conclusions:             This qualitative study provides insights into the elements of a sustainable LHS across a range of leaders in data-driven healthcare improvement. Fundamentally, an LHS requires continuous learning with implementation of new evidence back into frontline care to improve outcomes. Structure, governance, trust, culture, vision and leadership were all seen as important along with a skilled workforce and sustained investment. Processes and systems to optimise access to quality data were also seen as vital in an effective, sustainable LHS. These findings will inform a co-designed framework for implementing a sustainable LHS within the Australian healthcare and Academic Health Science Centre context. It is anticipated that application of these findings will assist to embed and accelerate the use of routine health data to continuously generate new knowledge and ongoing improvement in healthcare delivery and health outcomes.},
  file = {/home/a/Zotero/storage/SL7WN53S/Enticott et al. - 2020 - Leadership Perspectives on Learning Health Systems.pdf},
  type = {Preprint}
}

@article{ernst14,
  title = {Surgical {{Palliative Care Consultations Over Time}} in {{Relationship}} to {{Systemwide Frailty Screening}}},
  author = {Ernst, Katherine F. and Hall, Daniel E. and Schmid, Kendra K. and Seever, Georgia and Lavedan, Pierre and Lynch, Thomas G. and Johanning, Jason Michael},
  year = {2014},
  month = nov,
  volume = {149},
  pages = {1121},
  issn = {2168-6254},
  doi = {10.1001/jamasurg.2014.1393},
  journal = {JAMA Surgery},
  language = {en},
  number = {11}
}

@article{ernst14a,
  title = {Surgical {{Palliative Care Consultations Over Time}} in {{Relationship}} to {{Systemwide Frailty Screening}}},
  author = {Ernst, Katherine F. and Hall, Daniel E. and Schmid, Kendra K. and Seever, Georgia and Lavedan, Pierre and Lynch, Thomas G. and Johanning, Jason Michael},
  year = {2014},
  month = nov,
  volume = {149},
  pages = {1121--1126},
  issn = {2168-6254},
  doi = {10.1001/jamasurg.2014.1393},
  abstract = {IMPORTANCE
The need for integrating palliative care into surgical services has been established within the surgical literature. The ability to effectively screen, obtain an appropriately timed consultation, and determine the effect of consultation remains problematic.

OBJECTIVE
To examine surgical palliative care consultations over time and their relationship to the initiation and implementation of a systemwide frailty-screening program.

DESIGN, SETTING, AND PARTICIPANTS
We reviewed all surgical palliative care consultations performed between January 1, 2006, and August 31, 2013, and abstracted the referring service (medicine/surgery), date of surgery (if any), date of death (if any), and all variables required to calculate a frailty score using the risk analysis index. We examined changes in mortality and referral patterns before and after implementation of the frailty-screening program using multivariable logistic regression.

EXPOSURES
Surgical palliative care consultations, including frailty screening.

MAIN OUTCOMES AND MEASURES
The primary study outcomes were 30-, 180-, and 360-day mortality.

RESULTS
From 2006 to 2013, a total of 310 palliative care consultations were ordered for surgical patients: 160 before initiation of frailty screening (January 1, 2011) and 150 after initiation of the program. The groups had similar demographics, comorbidities, and frailty scores. After initiation, we observed dramatically decreased mortality at 30, 180, and 360 days (21.3\% vs 31.9\%, 44.0\% vs 70.6\%, and 66.0\% vs 78.8\%, respectively; all P {$<$} .05). This coincided with an increased rate of palliative care consultations from 32 per year to 56 per year. After initiation of the program, consultations were more likely to be requested by surgeons (56.7\% vs 24.4\%; P {$<$} .05) and were more likely to occur before the index operation (52.0\% vs 26.3\%; P {$<$} .05). Implementation of the screening program was associated with a 33\% reduction in 180-day mortality (odds ratio [OR], 0.37; 95\% CI, 0.22\textendash 0.62; P {$<$} .001) even after controlling for age, frailty, and whether the patients had surgery. Modeled mortality was also reduced when the palliative care consultation was ordered by a surgeon (OR, 0.50; CI, 0.30\textendash 0.83; P = .007) or ordered before the operation (OR, 0.52; CI, 0.30\textendash 0.90; P = .02).

CONCLUSIONS AND RELEVANCE
Our data suggest that a systematic frailty-screening program effectively identifies at-risk surgical patients and is associated with a significant reduction in mortality for patients undergoing palliative care consultation. Analysis also suggests that preoperative palliative care consultations ordered by surgeons are associated with reduced mortality rates.},
  journal = {JAMA surgery},
  number = {11},
  pmcid = {PMC4603652},
  pmid = {25207603}
}

@article{espinoza05,
  title = {Frailty in Older Adults: Insights and Interventions},
  shorttitle = {Frailty in Older Adults},
  author = {Espinoza, Sara and Walston, Jeremy D.},
  year = {2005},
  month = dec,
  volume = {72},
  pages = {1105--1112},
  issn = {0891-1150},
  abstract = {Frailty is a state of vulnerability that carries an increased risk of poor outcomes in older adults. Common signs and symptoms are fatigue, weight loss, muscle weakness, and progressive decline in function. Frail older adults are among the most challenging for medical management. However, awareness of this syndrome and its risks can help us care for these patients more confidently and decrease their risk for adverse outcomes.},
  journal = {Cleveland Clinic Journal of Medicine},
  keywords = {Activities of Daily Living,Aged,Fatigue,Frail Elderly,Humans,Muscle Weakness,Syndrome,Weight Loss},
  language = {eng},
  number = {12},
  pmid = {16392724}
}

@article{espinoza08,
  title = {Frailty in {{Older Mexican}}-{{American}} and {{European}}-{{American Adults}}: {{Is There}} an {{Ethnic Disparity}}?: {{ETHNIC DISPARITIES IN FRAILTY}}},
  shorttitle = {Frailty in {{Older Mexican}}-{{American}} and {{European}}-{{American Adults}}},
  author = {Espinoza, Sara E. and Hazuda, Helen P.},
  year = {2008},
  month = sep,
  volume = {56},
  pages = {1744--1749},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2008.01845.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {9}
}

@article{farhat12,
  title = {Are the Frail Destined to Fail? {{Frailty}} Index as Predictor of Surgical Morbidity and Mortality in the Elderly:},
  shorttitle = {Are the Frail Destined to Fail?},
  author = {Farhat, Joseph S. and Velanovich, Vic and Falvo, Anthony J. and Horst, H. Mathilda and Swartz, Andrew and Patton, Joe H. and Rubinfeld, Ilan S.},
  year = {2012},
  month = jun,
  volume = {72},
  pages = {1526--1531},
  issn = {2163-0755},
  doi = {10.1097/TA.0b013e3182542fab},
  journal = {Journal of Trauma and Acute Care Surgery},
  language = {en},
  number = {6}
}

@article{favini17,
  title = {Comparative {{Trends}} in {{Payment Adjustments Between Safety}}-{{Net}} and {{Other Hospitals Since}} the {{Introduction}} of the {{Hospital Readmission Reduction Program}} and {{Value}}-{{Based Purchasing}}},
  author = {Favini, Nathan and Hockenberry, Jason M. and Gilman, Matlin and Jain, Sanjula and Ong, Michael K. and Adams, E. Kathleen and Becker, Edmund R.},
  year = {2017},
  month = apr,
  volume = {317},
  pages = {1578--1580},
  issn = {0098-7484},
  doi = {10.1001/jama.2017.1469},
  abstract = {This study compares trends in Medicare payment adjustments to safety-net vs non\textendash safety-net hospitals under Hospital Readmission Reduction Program (HRRP) and Value-Based Purchasing programs, intended to incentivize higher-quality health care.},
  journal = {JAMA},
  number = {15}
}

@article{figueroa16,
  title = {Characteristics of Hospitals Receiving the Largest Penalties by {{US}} Pay-for-Performance Programmes},
  author = {Figueroa, Jose F and Wang, David E and Jha, Ashish K},
  year = {2016},
  month = oct,
  volume = {25},
  pages = {898},
  doi = {10.1136/bmjqs-2015-005040},
  abstract = {Healthcare systems around the world are striving to deliver high quality care while controlling costs. One compelling strategy is the use of penalties for low-value care.1 ,2 The US federal government has made significant efforts to shift towards value-based payments for hospitals by introducing three national pay-for-performance (P4P) schemes which employ penalties: Hospital Readmission Reduction Program (HRRP), Hospital Value-Based-Purchasing (VBP) and, more recently, Hospital-Acquired Condition Reduction (HACR) Program. HRRP penalises hospitals with higher-than-expected readmissions; VBP adjusts hospital payments (either a bonus or penalty) based on performance on clinical measures and patient experience and HACR penalises the worst quartile of hospitals on HAC metrics.3 Fiscal year 2015 marks the first time hospitals may be penalised by all three programmes, with Medicare reimbursement rates potentially cut by 5.5\%. Although prior work has raised concerns that hospitals serving medically complex or socioeconomically vulnerable populations are at higher risk for penalties by individual programmes,4\textendash 7 to our knowledge, there is no study that has examined the characteristics of hospitals that received the most substantial penalties across all three programmes. As \ldots},
  journal = {BMJ Quality \&amp; Safety},
  number = {11}
}

@article{figueroa16a,
  title = {Association between the {{Value}}-{{Based Purchasing}} Pay for Performance Program and Patient Mortality in {{US}} Hospitals: Observational Study},
  shorttitle = {Association between the {{Value}}-{{Based Purchasing}} Pay for Performance Program and Patient Mortality in {{US}} Hospitals},
  author = {Figueroa, Jose F and Tsugawa, Yusuke and Zheng, Jie and Orav, E John and Jha, Ashish K},
  year = {2016},
  month = may,
  volume = {353},
  issn = {0959-8138},
  doi = {10.1136/bmj.i2214},
  abstract = {Objective~To determine the impact of the Hospital Value-Based Purchasing (HVBP) program\textemdash the US pay for performance program introduced by Medicare to incentivize higher quality care\textemdash on 30 day mortality for three incentivized conditions: acute myocardial infarction, heart failure, and pneumonia., Design~Observational study., Setting~4267 acute care hospitals in the United States: 2919 participated in the HVBP program and 1348 were ineligible and used as controls (44 in general hospitals in Maryland and 1304 critical access hospitals across the United States)., Participants~2\,430\,618 patients admitted to US hospitals from 2008 through 2013., Main outcome measures~30 day risk adjusted mortality for acute myocardial infarction, heart failure, and pneumonia using a patient level linear spline analysis to examine the association between the introduction of the HVBP program and 30 day mortality. Non-incentivized, medical conditions were the comparators. A secondary outcome measure was to determine whether the introduction of the HVBP program was particularly beneficial for a subgroup of hospital\textemdash poor performers at baseline\textemdash that may benefit the most., Results~Mortality rates of incentivized conditions in hospitals participating in the HVBP program declined at -0.13\% for each quarter during the preintervention period and -0.03\% point difference for each quarter during the post-intervention period. For non-HVBP hospitals, mortality rates declined at -0.14\% point difference for each quarter during the preintervention period and -0.01\% point difference for each quarter during the post-intervention period. The difference in the mortality trends between the two groups was small and non-significant (difference in difference in trends -0.03\% point difference for each quarter, 95\% confidence interval -0.08\% to 0.13\% point difference, P=0.35). In no subgroups of hospitals was HVBP associated with better outcomes, including poor performers at baseline., Conclusions~Evidence that HVBP has led to lower mortality rates is lacking. Nations considering similar pay for performance programs may want to consider alternative models to achieve improved patient outcomes.},
  journal = {The BMJ},
  pmcid = {PMC4861084},
  pmid = {27160187}
}

@article{fisher05,
  title = {Just {{What Defines Frailty}}?: {{EDITORIALS}}},
  shorttitle = {Just {{What Defines Frailty}}?},
  author = {Fisher, Alfred L.},
  year = {2005},
  month = dec,
  volume = {53},
  pages = {2229--2230},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2005.00510.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {12}
}

@article{flodgren11,
  title = {An Overview of Reviews Evaluating the Effectiveness of Financial Incentives in Changing Healthcare Professional Behaviours and Patient Outcomes},
  author = {Flodgren, Gerd and Eccles, Martin P and Shepperd, Sasha and Scott, Anthony and Parmelli, Elena and Beyer, Fiona R},
  year = {2011},
  month = jul,
  pages = {CD009255},
  issn = {1469-493X},
  doi = {10.1002/14651858.CD009255},
  abstract = {Background
There is considerable interest in the effectiveness of financial incentives in the delivery of health care. Incentives may be used in an attempt to increase the use of evidence-based treatments among healthcare professionals or to stimulate health professionals to change their clinical behaviour with respect to preventive, diagnostic and treatment decisions, or both. Financial incentives are an extrinsic source of motivation and exist when an individual can expect a monetary transfer which is made conditional on acting in a particular way. Since there are numerous reviews performed within the healthcare area describing the effects of various types of financial incentives, it is important to summarise the effectiveness of these in an overview to discern which are most effective in changing health professionals' behaviour and patient outcomes.

Objectives
To conduct an overview of systematic reviews that evaluates the impact of financial incentives on healthcare professional behaviour and patient outcomes.

Methods
We searched the Cochrane Database of Systematic Reviews (CDSR) (The Cochrane Library); Database of Abstracts of Reviews of Effectiveness (DARE); TRIP; MEDLINE; EMBASE; Science Citation Index; Social Science Citation Index; NHS EED; HEED; EconLit; and Program in Policy Decision-Making (PPd) (from their inception dates up to January 2010). We searched the reference lists of all included reviews and carried out a citation search of those papers which cited studies included in the review. We included both Cochrane and non-Cochrane reviews of randomised controlled trials (RCTs), controlled clinical trials (CCTs), interrupted time series (ITSs) and controlled before and after studies (CBAs) that evaluated the effects of financial incentives on professional practice and patient outcomes, and that reported numerical results of the included individual studies. Two review authors independently extracted data and assessed the methodological quality of each review according to the AMSTAR criteria. We included systematic reviews of studies evaluating the effectiveness of any type of financial incentive. We grouped financial incentives into five groups: payment for working for a specified time period; payment for each service, episode or visit; payment for providing care for a patient or specific population; payment for providing a pre-specified level or providing a change in activity or quality of care; and mixed or other systems. We summarised data using vote counting.

Main results
We identified four reviews reporting on 32 studies. Two reviews scored 7 on the AMSTAR criteria (moderate, score 5 to 7, quality) and two scored 9 (high, score 8 to 11, quality). The reported quality of the included studies was, by a variety of methods, low to moderate. Payment for working for a specified time period was generally ineffective, improving 3/11 outcomes from one study reported in one review. Payment for each service, episode or visit was generally effective, improving 7/10 outcomes from five studies reported in three reviews; payment for providing care for a patient or specific population was generally effective, improving 48/69 outcomes from 13 studies reported in two reviews; payment for providing a pre-specified level or providing a change in activity or quality of care was generally effective, improving 17/20 reported outcomes from 10 studies reported in two reviews; and mixed and other systems were of mixed effectiveness, improving 20/31 reported outcomes from seven studies reported in three reviews. When looking at the effect of financial incentives overall across categories of outcomes, they were of mixed effectiveness on consultation or visit rates (improving 10/17 outcomes from three studies in two reviews); generally effective in improving processes of care (improving 41/57 outcomes from 19 studies in three reviews); generally effective in improving referrals and admissions (improving 11/16 outcomes from 11 studies in four reviews); generally ineffective in improving compliance with guidelines outcomes (improving 5/17 outcomes from five studies in two reviews); and generally effective in improving prescribing costs outcomes (improving 28/34 outcomes from 10 studies in one review).

Authors' conclusions
Financial incentives may be effective in changing healthcare professional practice. The evidence has serious methodological limitations and is also very limited in its completeness and generalisability. We found no evidence from reviews that examined the effect of financial incentives on patient outcomes.},
  journal = {The Cochrane database of systematic reviews},
  number = {7},
  pmcid = {PMC4204491},
  pmid = {21735443}
}

@book{smith13a,
  title = {Best Care at Lower Cost: The Path to Continuously Learning Health Care in {{America}}},
  shorttitle = {Best Care at Lower Cost},
  editor = {Smith, Mark D. and {Institute of Medicine (U.S.)}},
  year = {2013},
  publisher = {{National Academies Press}},
  address = {{Washington, D.C}},
  isbn = {978-0-309-26073-2 978-0-309-26074-9},
  keywords = {Costs and Cost Analysis,Delivery of Health Care,economics,Efficiency; Organizational,Quality of Health Care,United States},
  lccn = {RA395.A3 B475 2013}
}

@article{friedman14,
  title = {Toward a Science of Learning Systems: A Research Agenda for the High-Functioning {{Learning Health System}}},
  shorttitle = {Toward a Science of Learning Systems},
  author = {Friedman, C. and Rubin, J. and Brown, J. and Buntin, M. and Corn, M. and Etheredge, L. and Gunter, C. and Musen, M. and Platt, R. and Stead, W. and Sullivan, K. and Van Houweling, D.},
  year = {2014},
  month = oct,
  pages = {amiajnl-2014-002977},
  issn = {1067-5027, 1527-974X},
  doi = {10.1136/amiajnl-2014-002977},
  file = {/home/a/Zotero/storage/92LQ9LFC/Friedman et al. - 2014 - Toward a science of learning systems a research a.pdf},
  journal = {Journal of the American Medical Informatics Association},
  language = {en}
}

@article{friebel16,
  title = {The Multiple Aims of Pay-for-Performance and the Risk of Unintended Consequences},
  author = {Friebel, Rocco and Steventon, Adam},
  year = {2016},
  month = nov,
  volume = {25},
  pages = {827--831},
  issn = {2044-5415, 2044-5423},
  doi = {10.1136/bmjqs-2016-005392},
  abstract = {Since the Affordable Care Act introduced financial penalties on hospitals for excess readmission rates in the USA, an intense debate has ensued regarding the value of readmissions as a marker of quality. Under the Hospital Readmission Reduction Program (HRRP), hospitals face penalties of up to 3\% of base operating payment from Medicare, the federally funded health insurance system for people aged over 65. Penalties totalled \$428 million in 2015,1 and similar policies are in place in Denmark, Germany and England.2

HRRP aimed to `reward hospitals that are successful in reducing avoidable readmissions'3 and indeed Medicare has seen a decline in 30-day, all-cause readmission rates since the policy was introduced in 2012.4 More specific declines have been observed for the three conditions initially targeted, namely acute myocardial infarction, heart failure and pneumonia (figure 1).1 ,5 The HRRP was expanded to cover chronic obstructive pulmonary disease, total hip arthroplasty and total knee arthroplasty from 2015.

Figure~1
Trend in national Medicare 30-day readmission rates for index admissions for heart failure, heart attack, pneumonia and all-cause Medicare readmissions.1 ,4

While no study has been able to test causality against a counterfactual, on the face of it HRRP has contributed to a sustained focus on readmissions and potentially, improved patient care nationally. But what aspects of quality do readmission rates measure? And what are we to make of the findings reported in this issue of BMJ Quality and Safety ,6 which indicate that, like other pay-for-performance programmes, readmission penalties have disproportionately affected safety-net hospitals (ie, hospitals that serve a high number of patients of lower socioeconomic status (SES), often uninsured).

In theory, readmissions are related to the quality and safety of the initial hospital stay, the transitional care services and access to care and support following \ldots},
  copyright = {Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/},
  journal = {BMJ Qual Saf},
  keywords = {Accreditation,Adverse events; epidemiology and detection,Ambulatory care},
  language = {en},
  number = {11},
  pmid = {27048595}
}

@article{fried01a,
  title = {Frailty in Older Adults: Evidence for a Phenotype},
  shorttitle = {Frailty in Older Adults},
  author = {Fried, L. P. and Tangen, C. M. and Walston, J. and Newman, A. B. and Hirsch, C. and Gottdiener, J. and Seeman, T. and Tracy, R. and Kop, W. J. and Burke, G. and McBurnie, M. A.},
  year = {2001},
  month = mar,
  volume = {56},
  pages = {M146-M157},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/56.3.M146},
  abstract = {BACKGROUND: Frailty is considered highly prevalent in old age and to confer high risk for falls, disability, hospitalization, and mortality. Frailty has been considered synonymous with disability, comorbidity, and other characteristics, but it is recognized that it may have a biologic basis and be a distinct clinical syndrome. A standardized definition has not yet been established.
METHODS: To develop and operationalize a phenotype of frailty in older adults and assess concurrent and predictive validity, the study used data from the Cardiovascular Health Study. Participants were 5,317 men and women 65 years and older (4,735 from an original cohort recruited in 1989-90 and 582 from an African American cohort recruited in 1992-93). Both cohorts received almost identical baseline evaluations and 7 and 4 years of follow-up, respectively, with annual examinations and surveillance for outcomes including incident disease, hospitalization, falls, disability, and mortality.
RESULTS: Frailty was defined as a clinical syndrome in which three or more of the following criteria were present: unintentional weight loss (10 lbs in past year), self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. The overall prevalence of frailty in this community-dwelling population was 6.9\%; it increased with age and was greater in women than men. Four-year incidence was 7.2\%. Frailty was associated with being African American, having lower education and income, poorer health, and having higher rates of comorbid chronic diseases and disability. There was overlap, but not concordance, in the cooccurrence of frailty, comorbidity, and disability. This frailty phenotype was independently predictive (over 3 years) of incident falls, worsening mobility or ADL disability, hospitalization, and death, with hazard ratios ranging from 1.82 to 4.46, unadjusted, and 1.29-2.24, adjusted for a number of health, disease, and social characteristics predictive of 5-year mortality. Intermediate frailty status, as indicated by the presence of one or two criteria, showed intermediate risk of these outcomes as well as increased risk of becoming frail over 3-4 years of follow-up (odds ratios for incident frailty = 4.51 unadjusted and 2.63 adjusted for covariates, compared to those with no frailty criteria at baseline).
CONCLUSIONS: This study provides a potential standardized definition for frailty in community-dwelling older adults and offers concurrent and predictive validity for the definition. It also finds that there is an intermediate stage identifying those at high risk of frailty. Finally, it provides evidence that frailty is not synonymous with either comorbidity or disability, but comorbidity is an etiologic risk factor for, and disability is an outcome of, frailty. This provides a potential basis for clinical assessment for those who are frail or at risk, and for future research to develop interventions for frailty based on a standardized ascertainment of frailty.},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  keywords = {Aged,Aged; 80 and over,Cohort Studies,Disabled Persons,Fatigue,Female,Frail Elderly,Humans,Incidence,Male,Muscle Weakness,Phenotype,Prevalence,Sex Distribution,United States,Weight Loss},
  language = {en},
  number = {3},
  pmid = {11253156}
}

@article{geissler00,
  title = {Risk Stratification in Heart Surgery: Comparison of Six Score Systems},
  shorttitle = {Risk Stratification in Heart Surgery},
  author = {Geissler, H. J. and H{\"o}lzl, P. and Marohl, S. and {Kuhn-R{\'e}gnier}, F. and Mehlhorn, U. and S{\"u}dkamp, M. and {de Vivie}, E. R.},
  year = {2000},
  month = apr,
  volume = {17},
  pages = {400--406},
  issn = {1010-7940},
  abstract = {OBJECTIVE: Risk scores have become an important tool in patient assessment, as age, severity of heart disease, and comorbidity in patients undergoing heart surgery have considerably increased. Various risk scores have been developed to predict mortality after heart surgery. However, there are significant differences between scores with regard to score design and the initial patient population on which score development was based. It was the purpose of our study to compare six commonly used risk scores with regard to their validity in our patient population.
METHODS: Between September 1, 1998 and February 28, 1999, all adult patients undergoing heart surgery with cardiopulmonary bypass in our institution were preoperatively scored using the initial Parsonnet, Cleveland Clinic, French, Euro, Pons, and Ontario Province Risk (OPR) scores. Postoperatively, we registered 30-day mortality, use of mechanical assist devices, renal failure requiring hemodialysis or hemofiltration, stroke, myocardial infarction, and duration of ventilation and intensive care stay. Score validity was assessed by calculating the area under the ROC curve. Odds ratios were calculated to investigate the predictive relevance of risk factors.
RESULTS: Follow-up was able to be completed in 504 prospectively scored patients. Receiver operating characteristics (ROC) curve analysis for mortality showed the best predictive value for the Euro score. Predictive values for morbidity were considerably lower than predictive values for mortality in all of the investigated score systems. For most risk factors, odds ratios for mortality were substantially different from ratios for morbidity.
CONCLUSIONS: Among the investigated scores, the Euro score yielded the highest predictive value in our patient population. For most risk factors, predictive values for morbidity were substantially different from predictive values for mortality. Therefore, development of specific morbidity risk scores may improve prediction of outcome and hospital cost. Due to the heterogeneity of morbidity events, future score systems may have to generate separate predictions for mortality and major morbidity events.},
  journal = {European Journal of Cardio-Thoracic Surgery: Official Journal of the European Association for Cardio-Thoracic Surgery},
  keywords = {Adult,Aged,Cardiac Surgical Procedures,Cardiopulmonary Bypass,Evaluation Studies as Topic,Female,Germany,Heart Diseases,Humans,Male,Middle Aged,Odds Ratio,Predictive Value of Tests,Probability,Risk Assessment,Risk Factors,ROC Curve,Sensitivity and Specificity,Severity of Illness Index,Survival Analysis,Survival Rate},
  language = {eng},
  number = {4},
  pmid = {10773562}
}

@article{glance16,
  title = {Impact of {{Risk Adjustment}} for {{Socioeconomic Status}} on {{Risk}}-Adjusted {{Surgical Readmission Rates}}},
  author = {Glance, Laurent G. and Kellermann, Arthur L. and Osler, Turner M. and Li, Yue and Li, Wenjun and Dick, Andrew W.},
  year = {2016},
  month = apr,
  volume = {263},
  pages = {698--704},
  issn = {1528-1140},
  doi = {10.1097/SLA.0000000000001363},
  abstract = {OBJECTIVE: To assess whether differences in readmission rates between safety-net hospitals (SNH) and non-SNHs are due to differences in hospital quality, and to compare the results of hospital profiling with and without SES adjustment.
BACKGROUND: In response to concerns that quality measures unfairly penalizes SNH, NQF recently recommended that performance measures adjust for socioeconomic status (SES) when SES is a risk factor for poor patient outcomes.
METHODS: Multivariate regression was used to examine the association between SNH status and 30-day readmission after major surgery. The results of hospital profiling with and without SES adjustment were compared using the CMS Hospital Compare and the Hospital Readmissions Reduction Program (HRRP) methodologies.
RESULTS: Adjusting for patient risk and SES, patients admitted to SNHs were not more likely to be readmitted compared with patients in in non-SNHs (AOR 1.08; 95\% CI:0.95-1.23; P = 0.23). The results of hospital profiling based on Hospital Compare were nearly identical with and without SES adjustment (ICC 0.99, {$\kappa$} 0.96). Using the HRRP threshold approach, 61\% of SNHs were assigned to the penalty group versus 50\% of non-SNHs. After adjusting for SES, 51\% of SNHs were assigned to the penalty group.
CONCLUSIONS: Differences in surgery readmissions between SNHs and non-SNHs are due to differences in the patient case mix of low-SES patients, and not due to differences in quality. Adjusting readmission measures for SES leads to changes in hospital ranking using the HRRP threshold approach, but not using the CMS Hospital Compare methodology. CMS should consider either adjusting for the effects of SES when calculating readmission thresholds for HRRP, or replace it with the approach used in Hospital Compare.},
  journal = {Annals of Surgery},
  keywords = {Adult,Aged,Aged; 80 and over,Databases; Factual,Female,Humans,Male,Middle Aged,Multivariate Analysis,New York,Patient Readmission,Postoperative Complications,Regression Analysis,Risk Adjustment,Safety-net Providers,Social Class,Surgical Procedures; Operative},
  language = {eng},
  number = {4},
  pmid = {26655922}
}

@article{goggins05,
  title = {Frailty {{Index}} as a {{Measure}} of {{Biological Age}} in a {{Chinese Population}}},
  author = {Goggins, W. B. and Woo, J. and Sham, A. and Ho, S. C.},
  year = {2005},
  month = aug,
  volume = {60},
  pages = {1046--1051},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/60.8.1046},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  language = {en},
  number = {8}
}

@book{grossmann11,
  title = {Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health Care : Workshop Series Summary},
  shorttitle = {Digital Infrastructure for the Learning Health System},
  author = {Grossmann, Claudia and Powers, Brian and McGinnis, J. Michael and {Institute of Medicine (U.S.)} and {Roundtable on Value \& Science-Driven Health Care}},
  year = {2011},
  publisher = {{National Academies Press}},
  address = {{Washington, D.C.}},
  abstract = {"Like many other industries, health care is increasingly turning to digital information and the use of electronic resources. The Institute of Medicine's Roundtable on Value \& Science-Driven Health Care hosted three workshops to explore current efforts and opportunities to accelerate progress in improving health and health care with information technology systems."--Publisher's description.},
  annotation = {OCLC: 762137021},
  isbn = {978-0-309-15417-8},
  language = {English}
}

@article{haider16,
  title = {Setting a {{National Agenda}} for {{Surgical Disparities Research}}: {{Recommendations From}} the {{National Institutes}} of {{Health}} and {{American College}} of {{Surgeons Summit}}},
  shorttitle = {Setting a {{National Agenda}} for {{Surgical Disparities Research}}},
  author = {Haider, Adil H. and {Dankwa-Mullan}, Irene and {Maragh-Bass}, Allysha C. and Torain, Maya and Zogg, Cheryl K. and Lilley, Elizabeth J. and Kodadek, Lisa M. and Changoor, Navin R. and Najjar, Peter and Rose, John A. and Ford, Henri R. and Salim, Ali and Stain, Steven C. and Shafi, Shahid and Sutton, Beth and Hoyt, David and Maddox, Yvonne T. and Britt, L. D.},
  year = {2016},
  month = jun,
  volume = {151},
  pages = {554--563},
  issn = {2168-6262},
  doi = {10.1001/jamasurg.2016.0014},
  abstract = {Health care disparities (differential access, care, and outcomes owing to factors such as race/ethnicity) are widely established. Compared with other groups, African American individuals have an increased mortality risk across multiple surgical procedures. Gender, sexual orientation, age, and geographic disparities are also well documented. Further research is needed to mitigate these inequities. To do so, the American College of Surgeons and the National Institutes of Health-National Institute of Minority Health and Disparities convened a research summit to develop a national surgical disparities research agenda and funding priorities. Sixty leading researchers and clinicians gathered in May 2015 for a 2-day summit. First, literature on surgical disparities was presented within 5 themes: (1) clinician, (2) patient, (3) systemic/access, (4) clinical quality, and (5) postoperative care and rehabilitation-related factors. These themes were identified via an exhaustive preconference literature review and guided the summit and its interactive consensus-building exercises. After individual thematic presentations, attendees contributed research priorities for each theme. Suggestions were collated, refined, and prioritized during the latter half of the summit. Breakout sessions yielded 3 to 5 top research priorities by theme. Overall priorities, regardless of theme, included improving patient-clinician communication, fostering engagement and community outreach by using technology, improving care at facilities with a higher proportion of minority patients, evaluating the longer-term effect of acute intervention and rehabilitation support, and improving patient centeredness by identifying expectations for recovery. The National Institutes of Health and American College of Surgeons Summit on Surgical Disparities Research succeeded in identifying a comprehensive research agenda. Future research and funding priorities should prioritize patients' care perspectives, workforce diversification and training, and systematic evaluation of health technologies to reduce surgical disparities.},
  journal = {JAMA surgery},
  keywords = {Biomedical Research,Cultural Competency,Health Services Accessibility,Healthcare Disparities,Humans,National Institutes of Health (U.S.),Physician-Patient Relations,Postoperative Care,Practice Patterns; Physicians',Quality of Health Care,Societies; Medical,Socioeconomic Factors,Surgical Procedures; Operative,United States},
  language = {eng},
  number = {6},
  pmid = {26982380}
}

@article{hall17,
  title = {Association of a {{Frailty Screening Initiative With Postoperative Survival}} at 30, 180, and 365 {{Days}}},
  author = {Hall, Daniel E. and Arya, Shipra and Schmid, Kendra K. and Carlson, Mark A. and Lavedan, Pierre and Bailey, Travis L. and Purviance, Georgia and Bockman, Tammy and Lynch, Thomas G. and Johanning, Jason M.},
  year = {2017},
  month = mar,
  volume = {152},
  pages = {233},
  issn = {2168-6254},
  doi = {10.1001/jamasurg.2016.4219},
  journal = {JAMA Surgery},
  language = {en},
  number = {3}
}

@article{hall17a,
  title = {Development and {{Initial Validation}} of the {{Risk Analysis Index}} for {{Measuring Frailty}} in {{Surgical Populations}}},
  author = {Hall, Daniel E. and Arya, Shipra and Schmid, Kendra K. and Blaser, Casey and Carlson, Mark A. and Bailey, Travis L. and Purviance, Georgia and Bockman, Tammy and Lynch, Thomas G. and Johanning, Jason},
  year = {2017},
  month = feb,
  volume = {152},
  pages = {175},
  issn = {2168-6254},
  doi = {10.1001/jamasurg.2016.4202},
  journal = {JAMA Surgery},
  language = {en},
  number = {2}
}

@article{hall17b,
  title = {Development and {{Initial Validation}} of the {{Risk Analysis Index}} for {{Measuring Frailty}} in {{Surgical Populations}}},
  author = {Hall, Daniel E. and Arya, Shipra and Schmid, Kendra K. and Blaser, Casey and Carlson, Mark A. and Bailey, Travis L. and Purviance, Georgia and Bockman, Tammy and Lynch, Thomas G. and Johanning, Jason},
  year = {2017},
  month = feb,
  volume = {152},
  pages = {175},
  issn = {2168-6254},
  doi = {10.1001/jamasurg.2016.4202},
  journal = {JAMA Surgery},
  language = {en},
  number = {2}
}

@article{hall17c,
  title = {Association of a {{Frailty Screening Initiative With Postoperative Survival}} at 30, 180, and 365 {{Days}}},
  author = {Hall, Daniel E. and Arya, Shipra and Schmid, Kendra K. and Carlson, Mark A. and Lavedan, Pierre and Bailey, Travis L. and Purviance, Georgia and Bockman, Tammy and Lynch, Thomas G. and Johanning, Jason M.},
  year = {2017},
  month = mar,
  volume = {152},
  pages = {233--240},
  issn = {2168-6262},
  doi = {10.1001/jamasurg.2016.4219},
  abstract = {Importance: As the US population ages, the number of operations performed on elderly patients will likely increase. Frailty predicts postoperative mortality and morbidity more than age alone, thus presenting opportunities to identify the highest-risk surgical patients and improve their outcomes.
Objective: To examine the effect of the Frailty Screening Initiative (FSI) on mortality and complications by comparing the surgical outcomes of a cohort of surgical patients treated before and after implementation of the FSI.
Design, Setting, and Participants: This single-site, facility-wide, prospective cohort quality improvement project studied all 9153 patients from a level 1b Veterans Affairs medical center who presented for major, elective, noncardiac surgery from October 1, 2007, to July 1, 2014.
Interventions: Assessment of preoperative frailty in all patients scheduled for elective surgery began in July 2011. Frailty was assessed with the Risk Analysis Index (RAI), and the records of all frail patients (RAI score, {$\geq$}21) were flagged for administrative review by the chief of surgery (or designee) before the scheduled operation. On the basis of this review, clinicians from surgery, anesthesia, critical care, and palliative care were notified of the patient's frailty and associated surgical risks; if indicated, perioperative plans were modified based on team input.
Main Outcomes and Measures: Postoperative mortality at 30, 180, and 365 days.
Results: From October 1, 2007, to July 1, 2014, a total of 9153 patients underwent surgery (mean [SD] age, 60.3 [13.5] years; female, 653 [7.1\%]; and white, 7096 [79.8\%]). Overall 30-day mortality decreased from 1.6\% (84 of 5275 patients) to 0.7\% (26 of 3878 patients, P\,{$<$}\,.001) after FSI implementation. Improvement was greatest among frail patients (12.2\% [24 of 197 patients] to 3.8\% [16 of 424 patients], P\,{$<$}\,.001), although mortality rates also decreased among the robust patients (1.2\% [60 of 5078 patients] to 0.3\% [10 of 3454 patients], P\,{$<$}\,.001). The magnitude of improvement among frail patients increased at 180 (23.9\% [47 of 197 patients] to 7.7\% [30 of 389 patients], P\,{$<$}\,.001) and 365 days (34.5\% [68 of 197 patients] to 11.7\% [36 of 309 patients], P\,{$<$}\,.001). Multivariable models revealed improved survival after FSI implementation, controlling for age, frailty, and predicted mortality (adjusted odds ratio for 180-day survival, 2.87; 95\% CI, 1.98-4.16).
Conclusions and Relevance: Implementation of the FSI was associated with reduced mortality, suggesting the feasibility of widespread screening of patients preoperatively to identify frailty and the efficacy of system-level initiatives aimed at improving their surgical outcomes. Additional investigation is required to establish a causal connection.},
  journal = {JAMA surgery},
  keywords = {Aged,Elective Surgical Procedures,Female,Frail Elderly,Health Status,Health Status Indicators,Humans,Male,Middle Aged,Postoperative Complications,Preoperative Period,Prospective Studies,Quality Improvement,Risk Assessment,Survival Rate,Time Factors,United States,United States Department of Veterans Affairs},
  language = {eng},
  number = {3},
  pmid = {27902826}
}

@article{hall17d,
  title = {Development and {{Initial Validation}} of the {{Risk Analysis Index}} for {{Measuring Frailty}} in {{Surgical Populations}}},
  author = {Hall, Daniel E. and Arya, Shipra and Schmid, Kendra K. and Blaser, Casey and Carlson, Mark A. and Bailey, Travis L. and Purviance, Georgia and Bockman, Tammy and Lynch, Thomas G. and Johanning, Jason},
  year = {2017},
  month = feb,
  volume = {152},
  pages = {175--182},
  issn = {2168-6262},
  doi = {10.1001/jamasurg.2016.4202},
  abstract = {Importance: Growing consensus suggests that frailty-associated risks should inform shared surgical decision making. However, it is not clear how best to screen for frailty in preoperative surgical populations.
Objective: To develop and validate the Risk Analysis Index (RAI), a 14-item instrument used to measure surgical frailty. It can be calculated prospectively (RAI-C), using a clinical questionnaire, or retrospectively (RAI-A), using variables from the surgical quality improvement databases (Veterans Affairs or American College of Surgeons National Surgical Quality Improvement Projects).
Design, Setting, and Participants: Single-site, prospective cohort from July 2011 to September 2015 at the Veterans Affairs Nebraska-Western Iowa Heath Care System, a Level 1b Veterans Affairs Medical Center. The study included all patients presenting to the medical center for elective surgery.
Exposures: We assessed the RAI-C for all patients scheduled for surgery, linking these scores to administrative and quality improvement data to calculate the RAI-A and the modified Frailty Index.
Main Outcomes and Measures: Receiver operator characteristics and C statistics for each measure predicting postoperative mortality and morbidity.
Results: Of the participants, the mean (SD) age was 60.7 (13.9) years and 249 participants (3.6\%) were women. We assessed the RAI-C 10 698 times, from which we linked 6856 unique patients to mortality data. The C statistic predicting 180-day mortality for the RAI-C was 0.772. Of these 6856 unique patients, we linked 2785 to local Veterans Affairs Surgeons National Surgical Quality Improvement Projects data and calculated the C statistic for both the RAI-A (0.823) and RAI-C (0.824), along with the correlation between the 2 scores (r\,=\,0.478; P\,{$<$}\,.001). Of these 2785 patients, there were sufficient data to calculate the modified Frailty Index for 1021, in which the C statistics were 0.865 (RAI-A), 0.797 (RAI-C), and 0.811 (modified Frailty Index). The correlation between the RAI-A and RAI-C was 0.547, and the correlations of the modified Frailty Index to the RAI-A and RAI-C were 0.301 and 0.269, respectively (all P\,{$<$}\,.001). A cutoff of RAI-C of at least 21 classified 18.3\% patients as "frail" with a sensitivity of 0.50 and specificity of 0.82, whereas the RAI-A was less sensitive (0.25) and more specific (0.97), classifying only 3.7\% as "frail."
Conclusions and Relevance: The RAI-C and RAI-A represent effective tools for measuring frailty in surgical populations with predictive ability on par with other frailty tools. Moderate correlation between the measures suggests convergent validity. The RAI-C offers the advantage of prospective, preoperative assessment that is proved feasible for large-scale screening in clinical practice. However, further efforts should be directed at determining the optimal components of preoperative frailty assessment.},
  journal = {JAMA surgery},
  keywords = {Aged,Elective Surgical Procedures,Female,Health Status,Health Status Indicators,Humans,Male,Middle Aged,Patient Selection,Postoperative Complications,Predictive Value of Tests,Preoperative Period,Prospective Studies,Risk Assessment,ROC Curve},
  language = {eng},
  number = {2},
  pmid = {27893030}
}

@article{hall17e,
  title = {Ambulatory {{Surgery Data From Hospitals}} and {{Ambulatory Surgery Centers}}: {{United States}}, 2010},
  shorttitle = {Ambulatory {{Surgery Data From Hospitals}} and {{Ambulatory Surgery Centers}}},
  author = {Hall, Margaret J. and Schwartzman, Alexander and Zhang, Jin and Liu, Xiang},
  year = {2017},
  month = feb,
  pages = {1--15},
  issn = {2164-8344},
  abstract = {Objectives-This report presents national estimates of surgical and nonsurgical ambulatory procedures performed in hospitals and ambulatory surgery centers (ASCs) in the United States during 2010. Patient characteristics, including age, sex, expected payment source, duration of surgery, and discharge disposition are presented, as well as the number and types of procedures performed in these settings. Methods-Estimates in this report are based on ambulatory surgery data collected in the 2010 National Hospital Ambulatory Medical Care Survey (NHAMCS). NHAMCS has collected outpatient department and emergency department data since 1992 and began gathering ambulatory surgery data from both hospitals and ASCs in 2010. Sample data were weighted to produce annual national estimates. Results-In 2010, 48.3 million surgical and nonsurgical procedures were performed during 28.6 million ambulatory surgery visits to hospitals and ASCs combined. For both males and females, 39\% of procedures were performed on those aged 45-64. For females, about 24\% of procedures were performed on those aged 15-44 compared with 18\% for males, whereas the percentage of procedures performed on those under 15 was lower for females than for males (4\% compared with 9\%). About 19\% of procedures were performed on those aged 65-74, while about 14\% were performed on those aged 75 and over. Private insurance was listed as the principal expected source of payment for 51\% of ambulatory surgery visits, Medicare for 31\% of visits, and Medicaid for 8\% of visits. The most frequently performed procedures included endoscopy of large intestine (4.0 million), endoscopy of small intestine (2.2 million), extraction of lens (2.9 million), insertion of prosthetic lens (2.6 million), and injection of agent into spinal canal (2.9 million). Only 2\% of visits with a discharge status were admitted to the hospital as an inpatient.},
  journal = {National Health Statistics Reports},
  keywords = {outpatient surgery • procedures • ICD-9-CM • National Hospital Ambulatory Medical Care Survey (NHAMCS).},
  language = {eng},
  number = {102},
  pmid = {28256998}
}

@article{heron16,
  title = {National Vital Statistics Reports},
  author = {Heron, Melonie},
  year = {2016},
  volume = {65},
  journal = {National Vital Statistics Reports},
  number = {5}
}

@article{holm79,
  title = {A Simple Sequentially Rejective Multiple Test Procedure.},
  author = {Holm, S.},
  year = {1979},
  volume = {6},
  pages = {65--70},
  journal = {Scandinavian Journal of Statistics}
}

@article{hoover13,
  title = {Validation of an Index to Estimate the Prevalence of Frailty among Community-Dwelling Seniors},
  author = {Hoover, Melanie and Rotermann, Michelle and Sanmartin, Claudia and Bernier, Julie},
  year = {2013},
  month = sep,
  volume = {24},
  pages = {10--17},
  issn = {1209-1367},
  abstract = {BACKGROUND: This study validates cut-points for a frailty index (FI) to identify seniors at risk of a hospital-related event and estimates the number of frail seniors living in the community. The FI developed by Rockwood and Mitnitski defines levels of frailty based on scores of 0 to 1.0.
DATA AND METHODS: The cut-point validation was conducted using Stratum-Specific Likelihood Ratios applied to combined 2003 and 2005 Canadian Community Health Survey (CCHS) data, linked to hospital records from the Discharge Abstract Database (2002 to 2007). Based on the validated cut-points, frailty prevalence was estimated using 2009/2010 CCHS data.
RESULTS: Seniors scoring more than 0.21 on the FI were considered to be at elevated risk of hospital-related events. Four additional frailty levels were identified: non-frail (0 to {$\leq$}0.1), pre-frail ({$>$}0.1 to {$\leq$}0.21), more frail ({$>$}0.30 to {$\leq$}0.35) (women only), and most frail (frail-group subset) (0.45 or more). The number of community-dwelling seniors considered to be frail was estimated at about 1 million (24\%) in 2009/2010; another 1.4 million (32\%) could be considered pre-frail. Frailty prevalence rose with age; was higher among women than among men; and varied by geographic location.
INTERPRETATION: A cut-point of more than 0.21 can be used to identify frail seniors living in the community.},
  journal = {Health Reports},
  keywords = {activities of daily living,Canada,Frail Elderly,Health,health status indicators,hospital records,Humans,Prevalence,probabilistic linkage,Residence Characteristics,validation studies},
  language = {eng},
  number = {9},
  pmid = {24258362}
}

@article{isharwal17,
  title = {Preoperative Frailty Predicts Postoperative Complications and Mortality in Urology Patients},
  author = {Isharwal, Sudhir and Johanning, Jason M. and Dwyer, Jennifer G. and Schimid, Kendra K. and LaGrange, Chad A.},
  year = {2017},
  month = jan,
  volume = {35},
  pages = {21--26},
  issn = {0724-4983, 1433-8726},
  doi = {10.1007/s00345-016-1845-z},
  journal = {World Journal of Urology},
  language = {en},
  number = {1}
}

@article{isharwal17a,
  title = {Preoperative Frailty Predicts Postoperative Complications and Mortality in Urology Patients},
  author = {Isharwal, Sudhir and Johanning, Jason M. and Dwyer, Jennifer G. and Schimid, Kendra K. and LaGrange, Chad A.},
  year = {2017},
  month = jan,
  volume = {35},
  pages = {21--26},
  issn = {0724-4983, 1433-8726},
  doi = {10.1007/s00345-016-1845-z},
  abstract = {PurposeOur objective was to determine the impact of preoperative frailty, as measured by validated Risk Analysis Index (RAI), on the occurrence of postoperative complications after urologic surgeries in a national database comprised of diverse practice groups and cases.Study designThe National Surgical Quality Improvement Program (NSQIP) database was queried from 2005 to 2011 for a list of abdominal, vaginal, transurethral and scrotal urological surgeries using Current Procedural Terminology codes. The study population was subdivided into two groups based on the nature of procedures performed: complex procedures (inpatient) and simple procedures (outpatient). Risk Analysis Index score was calculated using preoperative NSQIP variables to determine preoperative frailty. Major postoperative morbidities (pulmonary, cardiovascular, renal and infectious), mortality, return to operating room, discharge destination and readmission to the hospital were examined.ResultsThe study identified 42,715 patients who underwent urological procedures, 25,693 complex and 17,022 simple procedures. Mean RAI score (range) was 7.75 (0\textendash 53). The majority of patients scored low on the RAI (90.57 \% with RAI {$<$} 10). As the RAI score increased, there was a significant increase in postoperative complication and mortality rate (both p {$<$} 0.0001). Similarly, the rate of return to operating room and hospital readmission rate increased as RAI increased (both p {$<$} 0.0001). Additionally, rate of discharge to home decreased. Interestingly, mortality rate in patients with high RAI did not differ comparing simple to complex procedures (p = 0.90), whereas complications were significantly greater in the complex operation (p = 0.01).ConclusionsIncrease in frailty, as measured by RAI score, is associated with increased postoperative complications and mortality. RAI may allow for rapid identification and counseling of patients who are at high risk of adverse perioperative outcomes.},
  journal = {World Journal of Urology},
  language = {en},
  number = {1}
}

@article{jo17,
  title = {Targeted Use of Growth Mixture Modeling: A Learning Perspective},
  shorttitle = {Targeted Use of Growth Mixture Modeling},
  author = {Jo, Booil and Findling, Robert L. and Wang, Chen-Pin and Hastie, Trevor J. and Youngstrom, Eric A. and Arnold, L. Eugene and Fristad, Mary A. and Horwitz, Sarah McCue},
  year = {2017},
  month = feb,
  volume = {36},
  pages = {671--686},
  issn = {1097-0258},
  doi = {10.1002/sim.7152},
  abstract = {From the statistical learning perspective, this paper shows a new direction for the use of growth mixture modeling (GMM), a method of identifying latent subpopulations that manifest heterogeneous outcome trajectories. In the proposed approach, we utilize the benefits of the conventional use of GMM for the purpose of generating potential candidate models based on empirical model fitting, which can be viewed as unsupervised learning. We then evaluate candidate GMM models on the basis of a direct measure of success; how well the trajectory types are predicted by clinically and demographically relevant baseline features, which can be viewed as supervised learning. We examine the proposed approach focusing on a particular utility of latent trajectory classes, as outcomes that can be used as valid prediction targets in clinical prognostic models. Our approach is illustrated using data from the Longitudinal Assessment of Manic Symptoms study. Copyright \textcopyright{} 2016 John Wiley \& Sons, Ltd.},
  journal = {Statistics in Medicine},
  keywords = {early prediction,growth mixture modeling,latent trajectory class,sensitivity,specificity,supervised learning,unsupervised learning},
  language = {en},
  number = {4}
}

@article{jo17a,
  title = {Construction of Longitudinal Prediction Targets Using Semisupervised Learning},
  author = {Jo, Booil and Findling, Robert L and Hastie, Trevor J and Youngstrom, Eric A and Wang, Chen-Pin and Arnold, L Eugene and Fristad, Mary A and Frazier, Thomas W and Birmaher, Boris and Gill, Mary K and Horwitz, Sarah McCue},
  year = {2017},
  month = jan,
  pages = {0962280216684163},
  issn = {0962-2802},
  doi = {10.1177/0962280216684163},
  abstract = {In establishing prognostic models, often aided by machine learning methods, much effort is concentrated in identifying good predictors. However, the same level of rigor is often absent in improving the outcome side of the models. In this study, we focus on this rather neglected aspect of model development. We are particularly interested in the use of longitudinal information as a way of improving the outcome side of prognostic models. This involves optimally characterizing individuals' outcome status, classifying them, and validating the formulated prediction targets. None of these tasks are straightforward, which may explain why longitudinal prediction targets are not commonly used in practice despite their compelling benefits. As a way of improving this situation, we explore the joint use of empirical model fitting, clinical insights, and cross-validation based on how well formulated targets are predicted by clinically relevant baseline characteristics (antecedent validators). The idea here is that all these methods are imperfect but can be used together to triangulate valid prediction targets. The proposed approach is illustrated using data from the longitudinal assessment of manic symptoms study.},
  journal = {Statistical Methods in Medical Research},
  language = {en}
}

@article{johnston20,
  title = {Relationship of a {{Claims}}-{{Based Frailty Index}} to {{Annualized Medicare Costs}}: {{A Cohort Study}}},
  shorttitle = {Relationship of a {{Claims}}-{{Based Frailty Index}} to {{Annualized Medicare Costs}}},
  author = {Johnston, Kenton J. and Wen, Hefei and Joynt Maddox, Karen E.},
  year = {2020},
  month = apr,
  volume = {172},
  pages = {533},
  issn = {0003-4819},
  doi = {10.7326/M19-3261},
  journal = {Annals of Internal Medicine},
  language = {en},
  number = {8}
}

@article{joynt11,
  title = {Thirty-Day Readmission Rates for {{Medicare}} Beneficiaries by Race and Site of Care},
  author = {Joynt, Karen E. and Orav, E. John and Jha, Ashish K.},
  year = {2011},
  month = feb,
  volume = {305},
  pages = {675--681},
  issn = {1538-3598},
  doi = {10.1001/jama.2011.123},
  abstract = {CONTEXT: Understanding whether and why there are racial disparities in readmissions has implications for efforts to reduce readmissions.
OBJECTIVE: To determine whether black patients have higher odds of readmission than white patients and whether these disparities are related to where black patients receive care.
DESIGN: Using national Medicare data, we examined 30-day readmissions after hospitalization for acute myocardial infarction (MI), congestive heart failure (CHF), and pneumonia. We categorized hospitals in the top decile of proportion of black patients as minority-serving. We determined the odds of readmission for black patients compared with white patients at minority-serving vs non-minority-serving hospitals.
SETTING AND PARTICIPANTS: Medicare Provider Analysis Review files of more than 3.1 million Medicare fee-for-service recipients who were discharged from US hospitals in 2006-2008.
MAIN OUTCOME MEASURE: Risk-adjusted odds of 30-day readmission.
RESULTS: Overall, black patients had higher readmission rates than white patients (24.8\% vs 22.6\%, odds ratio [OR], 1.13; 95\% confidence interval [CI], 1.11-1.14; P {$<$} .001); patients from minority-serving hospitals had higher readmission rates than those from non-minority-serving hospitals (25.5\% vs 22.0\%, OR, 1.23; 95\% CI, 1.20-1.27; P {$<$} .001). Among patients with acute MI and using white patients from non-minority-serving hospitals as the reference group (readmission rate 20.9\%), black patients from minority-serving hospitals had the highest readmission rate (26.4\%; OR, 1.35; 95\% CI, 1.28-1.42), while white patients from minority-serving hospitals had a 24.6\% readmission rate (OR, 1.23; 95\% CI, 1.18-1.29) and black patients from non-minority-serving hospitals had a 23.3\% readmission rate (OR, 1.20; 95\% CI, 1.16-1.23; P {$<$} .001 for each); patterns were similar for CHF and pneumonia. The results were unchanged after adjusting for hospital characteristics including markers of caring for poor patients.
CONCLUSION: Among elderly Medicare recipients, black patients were more likely to be readmitted after hospitalization for 3 common conditions, a gap that was related to both race and to the site where care was received.},
  journal = {JAMA},
  keywords = {African Continental Ancestry Group,Aged,Aged; 80 and over,European Continental Ancestry Group,Fee-for-Service Plans,Female,Health Status Disparities,Healthcare Disparities,Heart Failure,Hospitals,Humans,Male,Medicare,Myocardial Infarction,Odds Ratio,Patient Readmission,Pneumonia,Retrospective Studies,United States},
  language = {eng},
  number = {7},
  pmcid = {PMC3332042},
  pmid = {21325183}
}

@article{joynt11a,
  title = {Patient Race, Site of Care, and 30-Day Readmission Rates among Elderly {{Americans}}},
  author = {Joynt, Karen E. and Orav, E. John and Jha, Ashish K.},
  year = {2011},
  month = feb,
  volume = {305},
  pages = {675--681},
  issn = {0098-7484},
  doi = {10.1001/jama.2011.123},
  abstract = {Context
Understanding whether and why there are racial disparities in readmissions has implications for efforts to reduce readmissions.

Objective
To determine whether black patients have higher odds of readmission than white patients, and if these disparities are related to where black patients receive care.

Design
Using national Medicare data, we examined 30-day readmissions after hospitalization for acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia. We categorized hospitals in the top decile of proportion of black patients as ``minority-serving.'' We determined the odds of readmission for black patients compared with white patients at minority-serving versus non-minority-serving hospitals.

Setting
U.S. hospitals.

Participants
3.1 million Medicare fee-for-service recipients, discharged in 2006\textendash 2008.

Intervention
None.

Main Outcome Measure
Risk-adjusted odds of 30-day readmission.

Results
Overall, black patients had higher readmission rates than white patients (24.8\% versus 22.6\%, odds ratio [OR] 1.13, 95\% confidence interval [CI] 1.11 to 1.14, p{$<$}0.001); patients from minority-serving hospitals had higher readmission rates than those from non-minority-serving hospitals (25.5\% versus 22.0\%, OR 1.23, 95\% CI 1.20, 1.27, p{$<$}0.001). Among AMI patients, using white patients from non-minority-serving hospitals as our reference group (readmission rate 20.9\%), we found that black patients from non-minority-serving hospitals had the highest readmission rate (26.4\%, OR 1.20, 95\% CI 1.16, 1.23), while white patients from minority-serving hospitals had a 24.6\% readmission rate (OR 1.23, 95\% CI 1.18, 1.29) and black patients from minority-serving hospitals had a 23.3\% readmission rate (OR 1.35, 95\% CI 1.28, 1.42, p{$<$}0.001 for each); patterns were similar for CHF and pneumonia. The results were unchanged after adjusting for hospital characteristics including markers of caring for poor patients.

Conclusions
Among elderly Americans, black patients were more likely to be readmitted after hospitalization for three common conditions, a gap that was related to both race and to the site where care was received.},
  journal = {Jama},
  number = {7},
  pmcid = {PMC3332042},
  pmid = {21325183}
}

@article{joynt17,
  title = {Social {{Risk Factors}} and {{Performance Under Medicare}}'s {{Value}}-{{Based Purchasing Programs}}},
  author = {Joynt, Karen E. and Zuckerman, Rachael and Epstein, Arnold M.},
  year = {2017},
  month = may,
  volume = {10},
  issn = {1941-7705},
  doi = {10.1161/CIRCOUTCOMES.117.003587},
  journal = {Circulation. Cardiovascular Quality and Outcomes},
  language = {eng},
  number = {5},
  pmid = {28506982}
}

@article{kahlon15,
  title = {Association between Frailty and 30-Day Outcomes after Discharge from Hospital},
  author = {Kahlon, S. and Pederson, J. and Majumdar, S. R. and Belga, S. and Lau, D. and Fradette, M. and Boyko, D. and Bakal, J. A. and Johnston, C. and Padwal, R. S. and McAlister, F. A.},
  year = {2015},
  month = aug,
  volume = {187},
  pages = {799--804},
  issn = {0820-3946, 1488-2329},
  doi = {10.1503/cmaj.150100},
  journal = {Canadian Medical Association Journal},
  language = {en},
  number = {11}
}

@article{kane16,
  title = {Impact of {{Longevity Interventions}} on a {{Validated Mouse Clinical Frailty Index}}},
  author = {Kane, Alice E. and Hilmer, Sarah N. and Boyer, Dawn and Gavin, Kristan and Nines, Dawn and Howlett, Susan E. and {de Cabo}, Rafael and Mitchell, Sarah J.},
  year = {2016},
  month = mar,
  volume = {71},
  pages = {333--339},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/glu315},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  language = {en},
  number = {3}
}

@article{kane16a,
  title = {Animal Models of Frailty: Current Applications in Clinical Research},
  shorttitle = {Animal Models of Frailty},
  author = {Kane, Alice and Hilmer, Sarah and Mach, John and Mitchell, Sarah and {de Cabo}, Rafael and Howlett, Susan},
  year = {2016},
  month = oct,
  volume = {Volume 11},
  pages = {1519--1529},
  issn = {1178-1998},
  doi = {10.2147/CIA.S105714},
  journal = {Clinical Interventions in Aging},
  language = {en}
}

@article{karam13,
  title = {Simplified {{Frailty Index}} to {{Predict Adverse Outcomes}} and {{Mortality}} in {{Vascular Surgery Patients}}},
  author = {Karam, Joseph and Tsiouris, Athanasios and Shepard, Alexander and Velanovich, Vic and Rubinfeld, Ilan},
  year = {2013},
  month = oct,
  volume = {27},
  pages = {904--908},
  issn = {08905096},
  doi = {10.1016/j.avsg.2012.09.015},
  journal = {Annals of Vascular Surgery},
  language = {en},
  number = {7}
}

@article{keyhani14,
  title = {Effect of Clinical and Social Risk Factors on Hospital Profiling for Stroke Readmission: A Cohort Study},
  shorttitle = {Effect of Clinical and Social Risk Factors on Hospital Profiling for Stroke Readmission},
  author = {Keyhani, Salomeh and Myers, Laura J. and Cheng, Eric and Hebert, Paul and Williams, Linda S. and Bravata, Dawn M.},
  year = {2014},
  month = dec,
  volume = {161},
  pages = {775--784},
  issn = {1539-3704},
  doi = {10.7326/M14-0361},
  abstract = {BACKGROUND: The Centers for Medicare \& Medicaid Services (CMS) and Veterans Health Administration (VA) will report 30-day stroke readmission rates as a measure of hospital quality. A national debate on whether social risk factors should be included in models developed for hospital profiling is ongoing.
OBJECTIVE: To compare a CMS-based model of 30-day readmission with a more comprehensive model that includes measures of social risk (such as homelessness) or clinical factors (such as stroke severity and functional status).
DESIGN: Data from a retrospective cohort study were used to develop a CMS-based 30-day readmission model that included age and comorbid conditions based on codes from the International Classification of Diseases, Ninth Revision, Clinical Modification (model 1). This model was then compared with one that included administrative social risk factors (model 2). Finally, the CMS model (model 1) was compared with a model that included social risk and clinical factors from chart review (model 3). These 3 models were used to rank hospitals by 30-day risk-standardized readmission rates and examine facility rankings among the models.
SETTING: Hospitals in the VA.
PARTICIPANTS: Patients hospitalized with stroke in 2007.
MEASUREMENTS: 30-day readmission rates.
RESULTS: The 30-day readmission rate was 12.8\%. The c-statistics for the 3 models were 0.636, 0.646, and 0.661, respectively. All hospitals were classified as performing "as expected" using all 3 models (that is, performance did not differ from the VA national average); therefore, the addition of detailed clinical information or social risk factors did not alter assessment of facility performance.
LIMITATION: A predominantly male veteran cohort limits the generalizability of these findings.
CONCLUSION: In the VA, more comprehensive models that included social risk and clinical factors did not affect hospital comparisons based on 30-day readmission rates.
PRIMARY FUNDING SOURCE: U.S. Department of Veterans Affairs.},
  journal = {Annals of Internal Medicine},
  keywords = {Age Factors,Aged,Comorbidity,Female,Homeless Persons,Hospitals; Veterans,Humans,Male,Medicare,Patient Readmission,Poverty,Retrospective Studies,Risk Factors,Severity of Illness Index,Stroke,United States,United States Department of Veterans Affairs},
  language = {eng},
  number = {11},
  pmid = {25437405}
}

@article{kim14,
  title = {Measuring Frailty Using Claims Data for Pharmacoepidemiologic Studies of Mortality in Older Adults: Evidence and Recommendations: {{FRAILTY INDEX IN CLAIMS DATABASE}}},
  shorttitle = {Measuring Frailty Using Claims Data for Pharmacoepidemiologic Studies of Mortality in Older Adults},
  author = {Kim, Dae Hyun and Schneeweiss, Sebastian},
  year = {2014},
  month = sep,
  volume = {23},
  pages = {891--901},
  issn = {10538569},
  doi = {10.1002/pds.3674},
  journal = {Pharmacoepidemiology and Drug Safety},
  language = {en},
  number = {9}
}

@article{kirkman12,
  title = {Diabetes in {{Older Adults}}},
  author = {Kirkman, M. S. and Briscoe, V. J. and Clark, N. and Florez, H. and Haas, L. B. and Halter, J. B. and Huang, E. S. and Korytkowski, M. T. and Munshi, M. N. and Odegard, P. S. and Pratley, R. E. and Swift, C. S.},
  year = {2012},
  month = dec,
  volume = {35},
  pages = {2650--2664},
  issn = {0149-5992, 1935-5548},
  doi = {10.2337/dc12-1801},
  journal = {Diabetes Care},
  language = {en},
  number = {12}
}

@article{ko11,
  title = {The {{Clinical Care}} of {{Frail}}, {{Older Adults}}},
  author = {Ko, Fred Chau-Yang},
  year = {2011},
  month = feb,
  volume = {27},
  pages = {89--100},
  issn = {07490690},
  doi = {10.1016/j.cger.2010.08.007},
  journal = {Clinics in Geriatric Medicine},
  language = {en},
  number = {1}
}

@article{kohl06,
  title = {The Inflammatory Response to Surgery and Trauma},
  author = {Kohl, Benjamin A. and Deutschman, Clifford S.},
  year = {2006},
  month = aug,
  volume = {12},
  pages = {325--332},
  issn = {1070-5295},
  doi = {10.1097/01.ccx.0000235210.85073.fc},
  abstract = {PURPOSE OF REVIEW: The inflammatory or stress response to injury has evolved to ensure survival. This review will examine this response in otherwise healthy patients. Additionally, the impact of several common comorbid conditions on the inflammatory response will be considered. What will become evident is that the stress response may be exaggerated in some conditions and suppressed in others. Rapid identification of both an abnormal response and its cause will allow clinicians to maximize a patient's healing potential.
RECENT FINDINGS: Recent work has shown that an altered inflammatory response has marked effects on both immune competence and the endocrine system. Investigations are ongoing to delineate the mechanism of lymphocyte dysfunction. With regard to critical care endocrinopathies, the effects of insulin and hyperglycemia on inflammation and wound healing are being investigated.
SUMMARY: An understanding of the stress response will aid the clinician in preparing for expected responses, recognizing and perhaps correcting deviations from the norm and accounting for potential complications that arise in the face of preexisting disease. Deviations from the normal time course may represent the effects of preexisting medical illness, treatment or postoperative/injury complications.},
  journal = {Current Opinion in Critical Care},
  keywords = {Humans,Stress; Physiological,Surgical Procedures; Operative,Systemic Inflammatory Response Syndrome,Wounds and Injuries},
  language = {eng},
  number = {4},
  pmid = {16810043}
}

@article{kulminski08,
  title = {Cumulative {{Deficits Better Characterize Susceptibility}} to {{Death}} in {{Elderly People}} than {{Phenotypic Frailty}}: {{Lessons}} from the {{Cardiovascular Health Study}}: {{FRAILTY}}, {{CUMULATIVE DEFICITS}}, {{AND SURVIVAL}}},
  shorttitle = {Cumulative {{Deficits Better Characterize Susceptibility}} to {{Death}} in {{Elderly People}} than {{Phenotypic Frailty}}},
  author = {Kulminski, Alexander M. and Ukraintseva, Svetlana V. and Kulminskaya, Irina V. and Arbeev, Konstantin G. and Land, Kenneth and Yashin, Anatoli I.},
  year = {2008},
  month = may,
  volume = {56},
  pages = {898--903},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2008.01656.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {5}
}

@article{lascano15,
  title = {Validation of a Frailty Index in Patients Undergoing Curative Surgery for Urologic Malignancy and Comparison with Other Risk Stratification Tools},
  author = {Lascano, Danny and Pak, Jamie S. and Kates, Max and Finkelstein, Julia B. and Silva, Mark and Hagen, Elizabeth and RoyChoudhury, Arindam and Bivalacqua, Trinity J. and DeCastro, G. Joel and Benson, Mitchell C. and McKiernan, James M.},
  year = {2015},
  month = oct,
  volume = {33},
  pages = {426.e1-426.e12},
  issn = {10781439},
  doi = {10.1016/j.urolonc.2015.06.002},
  journal = {Urologic Oncology: Seminars and Original Investigations},
  language = {en},
  number = {10}
}

@article{leng02,
  title = {Serum {{Interleukin}}-6 and {{Hemoglobin}} as {{Physiological Correlates}} in the {{Geriatric Syndrome}} of {{Frailty}}: {{A Pilot Study}}},
  shorttitle = {Serum {{Interleukin}}-6 and {{Hemoglobin}} as {{Physiological Correlates}} in the {{Geriatric Syndrome}} of {{Frailty}}},
  author = {Leng, Sean and Chaves, Paulo and Koenig, Kathleen and Walston, Jeremy},
  year = {2002},
  month = jul,
  volume = {50},
  pages = {1268--1271},
  issn = {00028614, 15325415},
  doi = {10.1046/j.1532-5415.2002.50315.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {7}
}

@article{leng09,
  title = {White {{Blood Cell Counts}}, {{Insulinlike Growth Factor}}-1 {{Levels}}, and {{Frailty}} in {{Community}}-{{Dwelling Older Women}}},
  author = {Leng, S. X. and Hung, W. and Cappola, A. R. and Yu, Q. and Xue, Q.-L. and Fried, L. P.},
  year = {2009},
  month = apr,
  volume = {64A},
  pages = {499--502},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/gln047},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  language = {en},
  number = {4}
}

@article{levine13,
  title = {Modeling the {{Rate}} of {{Senescence}}: {{Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age}}?},
  shorttitle = {Modeling the {{Rate}} of {{Senescence}}},
  author = {Levine, M. E.},
  year = {2013},
  month = jun,
  volume = {68},
  pages = {667--674},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/gls233},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  language = {en},
  number = {6}
}

@article{li15,
  title = {Comparison between {{Frailty Index}} of {{Deficit Accumulation}} and {{Phenotypic Model}} to {{Predict Risk}} of {{Falls}}: {{Data}} from the {{Global Longitudinal Study}} of {{Osteoporosis}} in {{Women}} ({{GLOW}}) {{Hamilton Cohort}}},
  shorttitle = {Comparison between {{Frailty Index}} of {{Deficit Accumulation}} and {{Phenotypic Model}} to {{Predict Risk}} of {{Falls}}},
  author = {Li, Guowei and Thabane, Lehana and Ioannidis, George and Kennedy, Courtney and Papaioannou, Alexandra and Adachi, Jonathan D.},
  editor = {Chamberlain, Alanna M},
  year = {2015},
  month = mar,
  volume = {10},
  pages = {e0120144},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0120144},
  journal = {PLOS ONE},
  language = {en},
  number = {3}
}

@article{lin16,
  title = {Frailty and Post-Operative Outcomes in Older Surgical Patients: A Systematic Review},
  shorttitle = {Frailty and Post-Operative Outcomes in Older Surgical Patients},
  author = {Lin, Hui-Shan and Watts, J. N. and Peel, N. M. and Hubbard, R. E.},
  year = {2016},
  month = aug,
  volume = {16},
  pages = {157},
  issn = {1471-2318},
  doi = {10.1186/s12877-016-0329-8},
  abstract = {BACKGROUND: As the population ages, increasing numbers of older adults are undergoing surgery. Frailty is prevalent in older adults and may be a better predictor of post-operative morbidity and mortality than chronological age. The aim of this review was to examine the impact of frailty on adverse outcomes in the 'older old' and 'oldest old' surgical patients.
METHODS: A systematic review was undertaken. Electronic databases from 2010 to 2015 were searched to identify articles which evaluated the relationship between frailty and post-operative outcomes in surgical populations with a mean age of 75 and older. Articles were excluded if they were in non-English languages or if frailty was measured using a single marker only. Demographic data, type of surgery performed, frailty measure and impact of frailty on adverse outcomes were extracted from the selected studies. Quality of the studies and risk of bias was assessed by the Epidemiological Appraisal Instrument.
RESULTS: Twenty-three studies were selected for the review and they were assessed as medium to high quality. The mean age ranged from 75 to 87~years, and included patients undergoing cardiac, oncological, general, vascular and hip fracture surgeries. There were 21 different instruments used to measure frailty. Regardless of how frailty was measured, the strongest evidence in terms of numbers of studies, consistency of results and study quality was for associations between frailty and increased mortality at 30~days, 90~days and one year follow-up, post-operative complications and length of stay. A small number of studies reported on discharge to institutional care, functional decline and lower quality of life after surgery, and also found a significant association with frailty.
CONCLUSION: There was strong evidence that frailty in older-old and oldest-old surgical patients predicts post-operative mortality, complications, and prolonged length of stay. Frailty assessment may be a valuable tool in peri-operative assessment. It is possible that different frailty tools are best suited for different acuity and type of surgical patients. The association between frailty and return to pre-morbid function, discharge destination, and quality of life after surgery warrants further research.},
  journal = {BMC geriatrics},
  keywords = {Activities of Daily Living,Aged,Aged; 80 and over,Frail Elderly,Frailty,Geriatric,Geriatric Assessment,Humans,Institutionalization,Mortality,Oldest old,Post-operative complications,Postoperative Complications,Quality of Life,Surgical Procedures; Operative},
  language = {eng},
  number = {1},
  pmcid = {PMC5007853},
  pmid = {27580947}
}

@article{liu17,
  title = {Subtypes of Physical Frailty: {{Latent}} Class Analysis and Associations with Clinical Characteristics and Outcomes},
  shorttitle = {Subtypes of Physical Frailty},
  author = {Liu, Li-Kuo and Guo, Chao-Yu and Lee, Wei-Ju and Chen, Liang-Yu and Hwang, An-Chun and Lin, Ming-Hsien and Peng, Li-Ning and Chen, Liang-Kung and Liang, Kung-Yee},
  year = {2017},
  month = apr,
  volume = {7},
  pages = {46417},
  issn = {2045-2322},
  doi = {10.1038/srep46417},
  journal = {Scientific Reports}
}

@misc{lucas18,
  title = {{{NHIS}} - {{Tables}} of {{Summary Health Statistics}}. {{Table P}}-10: {{Number}} of Overnight Hospital Stays during the Past 12 Months, by Selected Characteristics: {{United States}}, 2015},
  author = {Lucas, JW and Benson, V},
  year = {2018},
  month = feb,
  howpublished = {ftp://ftp.cdc.gov/pub/Health\_Statistics/NCHS/NHIS/SHS/2015\_SHS\_Table\_P-10.pdf},
  language = {en-us}
}

@article{malmstrom14,
  title = {A {{Comparison}} of {{Four Frailty Models}}},
  author = {Malmstrom, Theodore K. and Miller, Douglas K. and Morley, John E.},
  year = {2014},
  month = apr,
  volume = {62},
  pages = {721--726},
  issn = {00028614},
  doi = {10.1111/jgs.12735},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {4}
}

@article{martsolf16,
  title = {Impact of {{Race}}/{{Ethnicity}} and {{Socioeconomic Status}} on {{Risk}}-{{Adjusted Hospital Readmission Rates Following Hip}} and {{Knee Arthroplasty}}},
  author = {Martsolf, Grant R. and Barrett, Marguerite L. and Weiss, Audrey J. and Kandrack, Ryan and Washington, Raynard and Steiner, Claudia A. and Mehrotra, Ateev and SooHoo, Nelson F. and Coffey, Rosanna},
  year = {2016},
  month = aug,
  volume = {98},
  pages = {1385--1391},
  issn = {1535-1386},
  doi = {10.2106/JBJS.15.00884},
  abstract = {BACKGROUND: Readmission rates following total hip arthroplasty (THA) and total knee arthroplasty (TKA) are increasingly used to measure hospital performance. Readmission rates that are not adjusted for race/ethnicity and socioeconomic status, patient risk factors beyond a hospital's control, may not accurately reflect a hospital's performance. In this study, we examined the extent to which risk-adjusting for race/ethnicity and socioeconomic status affected hospital performance in terms of readmission rates following THA and TKA.
METHODS: We calculated 2 sets of risk-adjusted readmission rates by (1) using the Centers for Medicare \& Medicaid Services standard risk-adjustment algorithm that incorporates patient age, sex, comorbidities, and hospital effects and (2) adding race/ethnicity and socioeconomic status to the model. Using data from the Healthcare Cost and Utilization Project, 2011 State Inpatient Databases, we compared the relative performances of 1,194 hospitals across the 2 methods.
RESULTS: Addition of race/ethnicity and socioeconomic status to the risk-adjustment algorithm resulted in (1) little or no change in the risk-adjusted readmission rates at nearly all hospitals; (2) no change in the designation of the readmission rate as better, worse, or not different from the population mean at {$>$}99\% of the hospitals; and (3) no change in the excess readmission ratio at {$>$}97\% of the hospitals.
CONCLUSIONS: Inclusion of race/ethnicity and socioeconomic status in the risk-adjustment algorithm led to a relative-performance change in readmission rates following THA and TKA at {$<$}3\% of the hospitals. We believe that policymakers and payers should consider this result when deciding whether to include race/ethnicity and socioeconomic status in risk-adjusted THA and TKA readmission rates used for hospital accountability, payment, and public reporting.
LEVEL OF EVIDENCE: Prognostic Level III. See instructions for Authors for a complete description of levels of evidence.},
  journal = {The Journal of Bone and Joint Surgery. American Volume},
  keywords = {Adolescent,Adult,Aged,Aged; 80 and over,Arthroplasty; Replacement; Hip,Arthroplasty; Replacement; Knee,Ethnic Groups,Female,Humans,Male,Middle Aged,Patient Readmission,Postoperative Complications,Risk Assessment,Risk Factors,Social Class,Socioeconomic Factors,Young Adult},
  language = {eng},
  number = {16},
  pmid = {27535441}
}

@article{mclachlan19,
  title = {{{LAGOS}}: Learning Health Systems and How They Can Integrate with Patient Care},
  shorttitle = {{{LAGOS}}},
  author = {McLachlan, Scott and Dube, Kudakwashe and Kyrimi, Evangelia and Fenton, Norman},
  year = {2019},
  month = oct,
  volume = {26},
  pages = {e100037},
  issn = {2632-1009},
  doi = {10.1136/bmjhci-2019-100037},
  abstract = {Problem               Learning health systems (LHS) are an underexplored concept. How LHS will operate in clinical practice is not well understood. This paper investigates the relationships between LHS, clinical care process specifications (CCPS) and the established levels of medical practice to enable LHS integration into daily healthcare practice.                                         Methods               Concept analysis and thematic analysis were used to develop an LHS characterisation. Pathway theory was used to create a framework by relating LHS, CCPS, health information systems and the levels of medical practice. A case study approach evaluates the framework in an established health informatics project.                                         Results               Five concepts were identified and used to define the LHS learning cycle. A framework was developed with five pathways, each having three levels of practice specificity spanning population to precision medicine. The framework was evaluated through application to case studies not previously understood to be LHS.                                         Discussion               Clinicians show limited understanding of LHS, increasing resistance and limiting adoption and integration into care routine. Evaluation of the presented framework demonstrates that its use enables: (1) correct analysis and characterisation of LHS; (2) alignment and integration into the healthcare conceptual setting; (3) identification of the degree and level of patient application; and (4) impact on the overall healthcare system.                                         Conclusion               This paper contributes a theoretical framework for analysis, characterisation and use of LHS. The framework allows clinicians and informaticians to correctly identify, characterise and integrate LHS within their daily routine. The overall contribution improves understanding, practice and evaluation of the LHS application in healthcare.},
  file = {/home/a/Zotero/storage/Q8Y54F69/McLachlan et al. - 2019 - LAGOS learning health systems and how they can in.pdf},
  journal = {BMJ Health \& Care Informatics},
  language = {en},
  number = {1}
}

@article{melin15,
  title = {Preoperative Frailty {{Risk Analysis Index}} to Stratify Patients Undergoing Carotid Endarterectomy},
  author = {Melin, Alyson A. and Schmid, Kendra K. and Lynch, Thomas G. and Pipinos, Iraklis I. and Kappes, Steven and Longo, G. Matthew and Gupta, Prateek K. and Johanning, Jason M.},
  year = {2015},
  month = mar,
  volume = {61},
  pages = {683--689},
  issn = {07415214},
  doi = {10.1016/j.jvs.2014.10.009},
  journal = {Journal of Vascular Surgery},
  language = {en},
  number = {3}
}

@article{melder20,
  title = {An {{Overview}} of {{Healthcare Improvement}}: {{Unpacking}} the {{Complexity}} for {{Clinicians}} and {{Managers}} in a {{Learning Health System}}},
  shorttitle = {An {{Overview}} of {{Healthcare Improvement}}},
  author = {Melder, Angela and Robinson, Tracy and Mcloughlin, Ian and Iedema, Rick and Teede, Helena},
  year = {2020},
  month = may,
  pages = {imj.14876},
  issn = {1444-0903, 1445-5994},
  doi = {10.1111/imj.14876},
  journal = {Internal Medicine Journal},
  language = {en}
}

@article{melin15a,
  title = {Preoperative Frailty {{Risk Analysis Index}} to Stratify Patients Undergoing Carotid Endarterectomy},
  author = {Melin, Alyson A. and Schmid, Kendra K. and Lynch, Thomas G. and Pipinos, Iraklis I. and Kappes, Steven and Longo, G. Matthew and Gupta, Prateek K. and Johanning, Jason M.},
  year = {2015},
  month = mar,
  volume = {61},
  pages = {683--689},
  issn = {1097-6809},
  doi = {10.1016/j.jvs.2014.10.009},
  abstract = {OBJECTIVE: Rapid and objective preoperative assessment of patients undergoing carotid endarterectomy (CEA) remains problematic. Preoperative variables correlate with increased morbidity and mortality, yet no easily implemented tool exists to stratify patients. We determined the relationship between our fully implemented frailty-based bedside Risk Analysis Index (RAI) and complications after CEA.
METHODS: Patients undergoing CEA in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database from 2005 to 2011 were included. Variables of frailty RAI were matched to preoperative NSQIP variables, and outcomes including stroke, mortality, myocardial infarction (MI), and length of stay were analyzed. We further analyzed patients who were symptomatic and asymptomatic before CEA.
RESULTS: With use of the NSQIP database, 44,832 patients undergoing CEA were analyzed (17,696 [39.5\%] symptomatic; 27,136 [60.5\%] asymptomatic). Increasing frailty RAI score correlated with increasing stroke, death, and MI (P {$<$} .0001) as well as with length of stay. RAI demonstrated increasing risk of stroke and death on the basis of risk stratification (low risk [0-10], 2.1\%; high risk [{$>$}10], 5.0\%). Among patients undergoing CEA, 88\% scored low ({$<$}10) on the RAI. In symptomatic patients, the risk of stroke and death for patients with a score of {$\leq$}10 is 2.9\%, whereas if the RAI score is 11 to 15, it is 5.0\%; 16 to 20, 6.9\%; and {$>$}21, 8.6\%. In asymptomatic patients, the risk of stroke and death for patients with a score of {$\leq$}10 is 1.6\%, whereas if the RAI score is 11 to 15, it is 2.9\%; 16 to 20, 5.2\%; and {$>$}21, 6.2\%.
CONCLUSIONS: Frailty is a predictor of increased stroke, mortality, MI, and length of stay after CEA. An easily implemented RAI holds the potential to identify a limited subset of patients who are at higher risk for postoperative complications and may not benefit from CEA.},
  journal = {Journal of Vascular Surgery},
  keywords = {Aged,Aged; 80 and over,Asymptomatic Diseases,Carotid Artery Diseases,Databases; Factual,Decision Support Techniques,Endarterectomy; Carotid,Female,Health Status,Health Status Indicators,Humans,Length of Stay,Male,Middle Aged,Myocardial Infarction,Patient Selection,Predictive Value of Tests,Risk Assessment,Risk Factors,Stroke,Time Factors,Treatment Outcome,United States},
  language = {eng},
  number = {3},
  pmid = {25499711}
}

@article{mendez14,
  title = {Impact of {{Hospital Variables}} on {{Case Mix Index}} as a {{Marker}} of {{Disease Severity}}},
  author = {Mendez, Carmen M. and Harrington, Darrell W. and Christenson, Peter and Spellberg, Brad},
  year = {2014},
  month = feb,
  volume = {17},
  pages = {28--34},
  issn = {1942-7891},
  doi = {10.1089/pop.2013.0002},
  abstract = {Case mix index (CMI) has become a standard indicator of hospital disease severity in the United States and internationally. However, CMI was designed to calculate hospital payments, not to track disease severity, and is highly dependent on documentation and coding accuracy. The authors evaluated whether CMI varied by characteristics affecting hospitals' disease severity (eg, trauma center or not). The authors also evaluated whether CMI was lower at public hospitals than private hospitals, given the diminished financial resources to support documentation enhancement at public hospitals. CMI data for a 14-year period from a large public database were analyzed longitudinally and cross-sectionally to define the impact of hospital variables on average CMI within and across hospital groups. Between 1996 and 2007, average CMI declined by 0.4\% for public hospitals, while rising significantly for private for-profit (14\%) and nonprofit (6\%) hospitals. After the introduction of the Medicare Severity Diagnosis Related Group (MS-DRG) system in 2007, average CMI increased for all 3 hospital types but remained lowest in public vs. private for-profit or nonprofit hospitals (1.05 vs. 1.25 vs. 1.20; P{$<$}0.0001). By multivariate analysis, teaching hospitals, level 1 trauma centers, and larger hospitals had higher average CMI, consistent with a marker of disease severity, but only for private hospitals. Public hospitals had lower CMI across all subgroups. Although CMI had some characteristics of a disease severity marker, it was lower across all strata for public hospitals. Hence, caution is warranted when using CMI to adjust for disease severity across public vs. private hospitals. (Population Health Management 2014;17:28\textendash 34)},
  journal = {Population Health Management},
  number = {1},
  pmcid = {PMC3931432},
  pmid = {23965045}
}

@article{meyer05,
  title = {Aging},
  author = {Meyer, K. C.},
  year = {2005},
  month = dec,
  volume = {2},
  pages = {433--439},
  issn = {1546-3222},
  doi = {10.1513/pats.200508-081JS},
  journal = {Proceedings of the American Thoracic Society},
  language = {en},
  number = {5}
}

@article{miller17,
  title = {A {{Clinically Relevant Frailty Index}} for {{Aging Rats}}},
  author = {Miller, Marshall G. and Thangthaeng, Nopporn and {Shukitt-Hale}, Barbara},
  year = {2017},
  month = jul,
  volume = {72},
  pages = {892--896},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/glw338},
  journal = {The Journals of Gerontology: Series A},
  language = {en},
  number = {7}
}

@article{mitnitski01a,
  title = {Accumulation of {{Deficits}} as a {{Proxy Measure}} of {{Aging}}},
  author = {Mitnitski, Arnold B. and Mogilner, Alexander J. and Rockwood, Kenneth},
  year = {2001},
  volume = {1},
  pages = {323--336},
  issn = {1537-744X},
  doi = {10.1100/tsw.2001.58},
  journal = {The Scientific World JOURNAL},
  language = {en}
}

@misc{mitnitski01b,
  title = {Accumulation of {{Deficits}} as a {{Proxy Measure}} of {{Aging}}},
  author = {Mitnitski, Arnold B. and Mogilner, Alexander J. and Rockwood, Kenneth},
  year = {2001},
  doi = {10.1100/tsw.2001.58},
  abstract = {This paper develops a method for appraising health status in elderly people. A frailty index was defined as the proportion of accumulated deficits (symptoms, signs, functional impairments, and laboratory abnormalities). It serves as an individual state variable, reflecting severity of illness and proximity to death. In a representative database of elderly Canadians we found that deficits accumulated at 3\% per year, and show a gamma distribution, typical for systems with redundant components that can be used in case of failure of a given subsystem. Of note, the slope of the index is insensitive to the individual nature of the deficits, and serves as an important prognostic factor for life expectancy. The formula for estimating an individual\dbend s life span given the frailty index value is presented. For different patterns of cognitive impairments the average within-group index value increases with the severity of the cognitive impairment, and the relative variability of the index is significantly reduced. Finally, the statistical distribution of the frailty index sharply differs between well groups (gamma distribution) and morbid groups (normal distribution). This pattern reflects an increase in uncompensated deficits in impaired organisms, which would lead to illness of various etiologies, and ultimately to increased mortality. The accumulation of deficits is as an example of a macroscopic variable, i.e., one that reflects general properties of aging at the level of the whole organism rather than any given functional deficiency. In consequence, we propose that it may be used as a proxy measure of aging.},
  journal = {The Scientific World Journal},
  language = {en},
  pmid = {12806071},
  type = {Research Article}
}

@article{mitnitski02a,
  title = {The Mortality Rate as a Function of Accumulated Deficits in a Frailty Index},
  author = {Mitnitski, Arnold B and Mogilner, Alexander J and MacKnight, Chris and Rockwood, Kenneth},
  year = {2002},
  month = sep,
  volume = {123},
  pages = {1457--1460},
  issn = {00476374},
  doi = {10.1016/S0047-6374(02)00082-9},
  journal = {Mechanisms of Ageing and Development},
  language = {en},
  number = {11}
}

@article{mitnitski17,
  title = {Aging, Frailty and Complex Networks},
  author = {Mitnitski, A. B. and Rutenberg, A. D. and Farrell, S. and Rockwood, K.},
  year = {2017},
  month = aug,
  volume = {18},
  pages = {433--446},
  issn = {1389-5729, 1573-6768},
  doi = {10.1007/s10522-017-9684-x},
  journal = {Biogerontology},
  language = {en},
  number = {4}
}

@article{morley13a,
  title = {Frailty {{Consensus}}: {{A Call}} to {{Action}}},
  shorttitle = {Frailty {{Consensus}}},
  author = {Morley, John E. and Vellas, Bruno and {Abellan van Kan}, G. and Anker, Stefan D. and Bauer, Juergen M. and Bernabei, Roberto and Cesari, Matteo and Chumlea, W.C. and Doehner, Wolfram and Evans, Jonathan and Fried, Linda P. and Guralnik, Jack M. and Katz, Paul R. and Malmstrom, Theodore K. and McCarter, Roger J. and Gutierrez Robledo, Luis M. and Rockwood, Ken and {von Haehling}, Stephan and Vandewoude, Maurits F. and Walston, Jeremy},
  year = {2013},
  month = jun,
  volume = {14},
  pages = {392--397},
  issn = {15258610},
  doi = {10.1016/j.jamda.2013.03.022},
  journal = {Journal of the American Medical Directors Association},
  language = {en},
  number = {6}
}

@article{murphy09,
  title = {Instrumenting the Health Care Enterprise for Discovery Research in the Genomic Era},
  author = {Murphy, Shawn and Churchill, Susanne and Bry, Lynn and Chueh, Henry and Weiss, Scott and Lazarus, Ross and Zeng, Qing and Dubey, Anil and Gainer, Vivian and Mendis, Michael and Glaser, John and Kohane, Isaac},
  year = {2009},
  month = sep,
  volume = {19},
  pages = {1675--1681},
  issn = {1088-9051},
  doi = {10.1101/gr.094615.109},
  abstract = {Tens of thousands of subjects may be required to obtain reliable evidence relating disease characteristics to the weak effects typically reported from common genetic variants. The costs of assembling, phenotyping, and studying these large populations are substantial, recently estimated at three billion dollars for 500,000 individuals. They are also decade-long efforts. We hypothesized that automation and analytic tools can repurpose the informational byproducts of routine clinical care, bringing sample acquisition and phenotyping to the same high-throughput pace and commodity price-point as is currently true of genome-wide genotyping. Described here is a demonstration of the capability to acquire samples and data from densely phenotyped and genotyped individuals in the tens of thousands for common diseases (e.g., in a 1-yr period: N = 15,798 for rheumatoid arthritis; N = 42,238 for asthma; N = 34,535 for major depressive disorder) in one academic health center at an order of magnitude lower cost. Even for rare diseases caused by rare, highly penetrant mutations such as Huntington disease (N = 102) and autism (N = 756), these capabilities are also of interest.},
  journal = {Genome Research},
  number = {9},
  pmcid = {PMC2752136},
  pmid = {19602638}
}

@article{nagasako14,
  title = {Adding {{Socioeconomic Data To Hospital Readmissions Calculations May Produce More Useful Results}}},
  author = {Nagasako, Elna M. and Reidhead, Mat and Waterman, Brian and Dunagan, Wm. Claiborne},
  year = {2014},
  month = may,
  volume = {33},
  pages = {786--791},
  issn = {0278-2715},
  doi = {10.1377/hlthaff.2013.1148},
  abstract = {To better understand the degree to which risk-standardized thirty-day readmission rates may be influenced by social factors, we compared results for hospitals in Missouri under two types of models. The first type of model is currently used by the Centers for Medicare and Medicaid Services for public reporting of condition-specific hospital readmission rates of Medicare patients. The second type of model is an ``enriched'' version of the first type of model with census tract-level socioeconomic data such as poverty rate, educational attainment, and housing vacancy rate. We found that the inclusion of these factors had a pronounced effect on calculated hospital readmission rates for patients admitted with acute myocardial infarction, heart failure, and pneumonia. Specifically, the models including socioeconomic data narrowed the range of observed variation in readmission rates for the above conditions, in percentage points, from 6.5 to 1.8, 14.0 to 7.4, and 7.4 to 3.7, respectively. Interestingly the average readmission rates for the three conditions did not change significantly between the two types of models. The results of our exploratory analysis suggest that further work to characterize and report the effects of socioeconomic factors on standardized readmission measures may assist efforts to improve care quality and deliver more equitable care on the part of hospitals, payers, and other stakeholders.},
  journal = {Health affairs (Project Hope)},
  number = {5},
  pmcid = {PMC4079850},
  pmid = {24799575}
}

@article{obeid12,
  title = {Predictors of Critical Care-Related Complications in Colectomy Patients Using the {{National Surgical Quality Improvement Program}}: Exploring Frailty and Aggressive Laparoscopic Approaches},
  shorttitle = {Predictors of Critical Care-Related Complications in Colectomy Patients Using the {{National Surgical Quality Improvement Program}}},
  author = {Obeid, Nadia M. and Azuh, Ogochukwu and Reddy, Subhash and Webb, Shawn and Reickert, Craig and Velanovich, Vic and Horst, H. Mathilda and Rubinfeld, Ilan},
  year = {2012},
  month = apr,
  volume = {72},
  pages = {878--883},
  issn = {2163-0763},
  doi = {10.1097/TA.0b013e31824d0f70},
  abstract = {BACKGROUND: Colectomy patients experience a broad set of adverse outcomes. Complications requiring critical care support are common in this group. We hypothesized that as frailty increases, the risk of Clavien class IV and V complications will increase in colectomy patients.
METHODS: Using the National Surgical Quality Improvement Program (NSQIP) participant use files for 2005-2009, we identified patients who underwent laparoscopic and open colectomies by Current Procedural Terminology code. Using the Clavien classification for postoperative complications, we identified NSQIP data points most consistent with Clavien class IV requiring intensive care unit (ICU) care or class V complications (death). We used a modified frailty index with 11 variables based on mapping the Canadian Study of Health and Aging Frailty Index and existing NSQIP variables. Logistic regression was performed to acuity adjust the findings.
RESULTS: A total of 58,448 colectomies were identified. As frailty index increased from 0 to 0.55, the proportion of those experiencing Clavien class IV or V complications increased from 3.2\% at baseline to 56.3\%. Variables found to be significant by logistic regression (odds ratio) were frailty index (14.4; p = 0.001), open procedure (2.35; p {$<$} 0.001), and American Society of Anesthesiologists class 4 (3.2; p = 0.038) or 5 (7.1; p = 0.001) while emergency operation and wound classification 3 or 4 were not.
CONCLUSIONS: Complications requiring ICU care represent a significant morbidity in the colectomy patient population. Frailty index seems to be an important predictor of ICU-level complications and death, and laparoscopy seems to be protective.},
  journal = {The Journal of Trauma and Acute Care Surgery},
  keywords = {Aged,Aged; 80 and over,Colectomy,Critical Care,Female,Frail Elderly,Humans,Laparoscopy,Logistic Models,Male,Middle Aged,Odds Ratio,Postoperative Complications,Quality Improvement,Retrospective Studies,Severity of Illness Index,United States},
  language = {eng},
  number = {4},
  pmid = {22491599}
}

@article{orkaby17,
  title = {Comparison of Two Frailty Indices in the Physicians' Health Study},
  author = {Orkaby, Ariela R. and Hshieh, Tammy T. and Gaziano, John M. and Djousse, Luc and Driver, Jane A.},
  year = {2017},
  month = jul,
  volume = {71},
  pages = {21--27},
  issn = {01674943},
  doi = {10.1016/j.archger.2017.02.009},
  journal = {Archives of Gerontology and Geriatrics},
  language = {en}
}

@article{pajewski19,
  title = {Frailty {{Screening Using}} the {{Electronic Health Record Within}} a {{Medicare Accountable Care Organization}}},
  author = {Pajewski, Nicholas M and Lenoir, Kristin and Wells, Brian J and Williamson, Jeff D and Callahan, Kathryn E},
  editor = {Newman, Anne},
  year = {2019},
  month = oct,
  volume = {74},
  pages = {1771--1777},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/glz017},
  abstract = {Abstract

              Background
              The accumulation of deficits model for frailty has been used to develop an electronic health record (EHR) frailty index (eFI) that has been incorporated into British guidelines for frailty management. However, there have been limited applications of EHR-based approaches in the United States.


              Methods
              We constructed an adapted eFI for patients in our Medicare Accountable Care Organization (ACO, N = 12,798) using encounter, diagnosis code, laboratory, medication, and Medicare Annual Wellness Visit (AWV) data from the EHR. We examined the association of the eFI with mortality, health care utilization, and injurious falls.


              Results
              The overall cohort was 55.7\% female, 85.7\% white, with a mean age of 74.9 (SD = 7.3) years. In the prior 2 years, 32.1\% had AWV data. The eFI could be calculated for 9,013 (70.4\%) ACO patients. Of these, 46.5\% were classified as prefrail (0.10 {$<$} eFI {$\leq$} 0.21) and 40.1\% frail (eFI {$>$} 0.21). Accounting for age, comorbidity, and prior health care utilization, the eFI independently predicted all-cause mortality, inpatient hospitalizations, emergency department visits, and injurious falls (all p {$<$} .001). Having at least one functional deficit captured from the AWV was independently associated with an increased risk of hospitalizations and injurious falls, controlling for other components of the eFI.


              Conclusions
              Construction of an eFI from the EHR, within the context of a managed care population, is feasible and can help to identify vulnerable older adults. Future work is needed to integrate the eFI with claims-based approaches and test whether it can be used to effectively target interventions tailored to the health needs of frail patients.},
  journal = {The Journals of Gerontology: Series A},
  language = {en},
  number = {11}
}

@article{parks12,
  title = {A Procedure for Creating a Frailty Index Based on Deficit Accumulation in Aging Mice},
  author = {Parks, Randi J. and Fares, Elias and Macdonald, Jennifer K. and Ernst, Matthew C. and Sinal, Christopher J. and Rockwood, Kenneth and Howlett, Susan E.},
  year = {2012},
  month = mar,
  volume = {67},
  pages = {217--227},
  issn = {1758-535X},
  doi = {10.1093/gerona/glr193},
  abstract = {This study developed an approach to quantify frailty with a frailty index (FI) and investigated whether age-related changes in contractions, calcium transients, and ventricular myocyte length were more prominent in mice with a high FI. The FI combined 31 variables that reflect different aspects of health in middle-aged ({$\sim$}12 months) and aged ({$\sim$}30 months) mice of both sexes. Aged animals had a higher FI than younger animals (FI = 0.43 {$\pm$} 0.03 vs 0.08 {$\pm$} 0.02, p {$<$} .001, n = 12). Myocyte hypertrophy increased by 30\%-50\% as the FI increased in aged animals. Peak contractions decreased more than threefold from lowest to highest FI values in aged mice (p {$<$} .037), but calcium transients were unaffected. Similar results were seen with an FI based on eight noninvasive variables identified as underlying factors. These results show that an FI can be developed for murine models and suggest that age-associated changes in myocytes are more prominent in animals with a high FI.},
  journal = {The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences},
  keywords = {Aged,Aged; 80 and over,Aging,Animals,Calcium Channels,Cardiomegaly,Disease Models; Animal,Female,Frail Elderly,Geriatric Assessment,Humans,Male,Mice,Myocardial Contraction,Severity of Illness Index},
  language = {eng},
  number = {3},
  pmid = {22021390}
}

@article{patel14,
  title = {Association of a {{Modified Frailty Index With Mortality After Femoral Neck Fracture}} in {{Patients Aged}} 60 {{Years}} and {{Older}}},
  author = {Patel, Kushal V. and Brennan, Kindyle L. and Brennan, Michael L. and Jupiter, Daniel C. and Shar, Adam and Davis, Matthew L.},
  year = {2014},
  month = mar,
  volume = {472},
  pages = {1010--1017},
  issn = {0009-921X, 1528-1132},
  doi = {10.1007/s11999-013-3334-7},
  journal = {Clinical Orthopaedics and Related Research\textregistered},
  language = {en},
  number = {3}
}

@article{pena14a,
  title = {Comparison of Alternate Scoring of Variables on the Performance of the Frailty Index},
  author = {Pe{\~n}a, Fernando G and Theou, Olga and Wallace, Lindsay and Brothers, Thomas D and Gill, Thomas M and Gahbauer, Evelyne A and Kirkland, Susan and Mitnitski, Arnold and Rockwood, Kenneth},
  year = {2014},
  month = dec,
  volume = {14},
  issn = {1471-2318},
  doi = {10.1186/1471-2318-14-25},
  journal = {BMC Geriatrics},
  language = {en},
  number = {1}
}

@article{polanczyk01,
  title = {Impact of Age on Perioperative Complications and Length of Stay in Patients Undergoing Noncardiac Surgery},
  author = {Polanczyk, C. A. and Marcantonio, E. and Goldman, L. and Rohde, L. E. and Orav, J. and Mangione, C. M. and Lee, T. H.},
  year = {2001},
  month = apr,
  volume = {134},
  pages = {637--643},
  issn = {0003-4819},
  abstract = {BACKGROUND: Major surgical procedures are performed with increasing frequency in elderly persons, but the impact of age on resource use and outcomes is uncertain.
OBJECTIVE: To evaluate the influence of age on perioperative cardiac and noncardiac complications and length of stay in patients undergoing noncardiac surgery.
DESIGN: Prospective cohort study.
SETTING: Urban academic medical center.
PATIENTS: Consecutive sample of 4315 patients 50 years of age or older who underwent nonemergent major noncardiac procedures.
MEASUREMENTS: Major perioperative complications (cardiac and noncardiac), in-hospital mortality, and length of stay.
RESULTS: Major perioperative complications occurred in 4.3\% (44 of 1015) of patients 59 years of age or younger, 5.7\% (93 of 1646) of patients 60 to 69 years of age, 9.6\% (129 of 1341) of patients 70 to 79 years of age, and 12.5\% (39 of 313) of patients 80 years of age or older (P {$<$} 0.001). In-hospital mortality was significantly higher in patients 80 years of age or older than in those younger than 80 years of age (0.7\% vs. 2.6\%, respectively). Multivariate analyses indicated an increased odds ratio for perioperative complications or in-hospital mortality in patients 70 to 79 years of age (1.8 [95\% CI, 1.2 to 2.7]) and those 80 years of age or older (OR, 2.1 [CI, 1.2 to 3.6]) compared with patients 50 to 59 years of age. Patients 80 years of age or older stayed an average of 1 day more in the hospital, after adjustment for other clinical data (P = 0.001).
CONCLUSIONS: Elderly patients had a higher rate of major perioperative complications and mortality after noncardiac surgery and a longer length of stay, but even in patients 80 years of age or older, mortality was low.},
  journal = {Annals of Internal Medicine},
  keywords = {Age Factors,Aged,Aged; 80 and over,Elective Surgical Procedures,Female,Hospital Mortality,Humans,Length of Stay,Male,Middle Aged,Multivariate Analysis,Postoperative Complications,Prospective Studies,Regression Analysis,Statistics; Nonparametric},
  language = {eng},
  number = {8},
  pmid = {11304103}
}

@article{porock05,
  title = {Predicting Death in the Nursing Home: Development and Validation of the 6-Month {{Minimum Data Set}} Mortality Risk Index},
  shorttitle = {Predicting Death in the Nursing Home},
  author = {Porock, Davina and Oliver, Debra Parker and Zweig, Steve and Rantz, Marilyn and Mehr, David and Madsen, Richard and Petroski, Greg},
  year = {2005},
  month = apr,
  volume = {60},
  pages = {491--498},
  issn = {1079-5006},
  abstract = {BACKGROUND: Currently, 24\% of all deaths nationally occur in nursing homes making this an important focus of care. However, many residents are not identified as dying and thus do not receive appropriate care in the last weeks and months of life. The aim of our study was to develop and validate a predictive model of 6-month mortality risk using functional, emotional, cognitive, and disease variables found in the Minimum Data Set.
METHODS: This retrospective cohort study developed and validated a clinical prediction model using stepwise logistic regression analysis. Our study sample included all Missouri long-term-care residents (43,510) who had a full Minimum Data Set assessment transmitted to the Federal database in calendar year 1999. Death was confirmed by death certificate data.
RESULTS: The validated predictive model with a c-statistic of.75 included the following predictors: a) demographics (age and male sex); b) diseases (cancer, congestive heart failure, renal failure, and dementia/Alzheimer's disease); c) clinical signs and symptoms (shortness of breath, deteriorating condition, weight loss, poor appetite, dehydration, increasing number of activities of daily living requiring assistance, and poor score on the cognitive performance scale); and d) adverse events (recent admission to the nursing home). A simple point system derived from the regression equation can be totaled to aid in predicting mortality.
CONCLUSIONS: A reasonably accurate, validated model has been produced, with clinical application through a scored point system, to assist clinicians, residents, and family members in defining good goals of care around end-of-life care.},
  journal = {The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences},
  keywords = {Activities of Daily Living,Age Factors,Aged,Aged; 80 and over,Alzheimer Disease,Cognition Disorders,Cohort Studies,Death Certificates,Dyspnea,Feeding and Eating Disorders,Female,Forecasting,Heart Failure,Humans,Male,Missouri,Mortality,Neoplasms,Nursing Homes,Renal Insufficiency,Retrospective Studies,Risk Assessment,Sex Factors,Terminal Care},
  language = {eng},
  number = {4},
  pmid = {15933390}
}

@article{porock10,
  title = {The {{MDS Mortality Risk Index}}: {{The}} Evolution of a Method for Predicting 6-Month Mortality in Nursing Home Residents},
  shorttitle = {The {{MDS Mortality Risk Index}}},
  author = {Porock, Davina and {Parker-Oliver}, Debra and Petroski, Gregory F and Rantz, Marilyn},
  year = {2010},
  month = jul,
  volume = {3},
  pages = {200},
  issn = {1756-0500},
  doi = {10.1186/1756-0500-3-200},
  abstract = {Background
Accurate prognosis is vital to the initiation of advance care planning particularly in a vulnerable, at risk population such as care home residents. The aim of this paper is to report on the revision and simplification of the MDS Mortality Rating Index (MMRI) for use in clinical practice to predict the probability of death in six months for care home residents.

Methods
The design was a secondary analysis of a US Minimum Data Set (MDS) for long term care residents using regression analysis to identify predictors of mortality within six months.

Results
Using twelve easy to collect items, the probability of mortality within six months was accurately predicted within the MDS database. The items are: admission to the care home within three months; lost weight unintentionally in past three months; renal failure; chronic heart failure; poor appetite; male; dehydrated; short of breath; active cancer diagnosis; age; deteriorated cognitive skills in past three months; activities of daily living score.

Conclusion
A lack of recognition of the proximity of death is often blamed for inappropriate admission to hospital at the end of an older person's life. An accurate prognosis for older adults living in a residential or nursing home can facilitate end of life decision making and planning for preferred place of care at the end of life. The original MMRI was derived and validated from a large database of long term care residents in the USA. However, this simplification of the revised index (MMRI-R) may provide a means for facilitating prognostication and end of life discussions for application outside the USA where the MDS is not in use. Prospective testing is needed to further test the accuracy of the MMRI-R and its application in the UK and other non-MDS settings.},
  journal = {BMC Research Notes},
  pmcid = {PMC2913927},
  pmid = {20637076}
}

@article{pugh14,
  title = {Influence of {{Frailty}}-{{Related Diagnoses}}, {{High}}-{{Risk Prescribing}} in {{Elderly Adults}}, and {{Primary Care Use}} on {{Readmissions}} in {{Fewer}} than 30 {{Days}} for {{Veterans Aged}} 65 and {{Older}}},
  author = {Pugh, Jacqueline A. and Wang, Chen-Pin and Espinoza, Sara E. and No{\"e}l, Polly H. and Bollinger, Mary and Amuan, Megan and Finley, Erin and Pugh, Mary Jo},
  year = {2014},
  month = feb,
  volume = {62},
  pages = {291--298},
  issn = {00028614},
  doi = {10.1111/jgs.12656},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {2}
}

@article{qureshi14,
  title = {The Influence of Limited {{English}} Proficiency on Outcome in Patients Treated with Radiotherapy for Head and Neck Cancer},
  author = {Qureshi, Muhammad M. and Romesser, Paul B. and Jalisi, Scharukh and Zaner, Ken S. and Cooley, Timothy P. and Grillone, Gregory and Kachnic, Lisa A. and Truong, Minh Tam},
  year = {2014},
  month = nov,
  volume = {97},
  pages = {276--282},
  issn = {0738-3991},
  doi = {10.1016/j.pec.2014.07.031},
  abstract = {Objective
To evaluate how limited English proficiency affects treatment outcome in head and neck cancer (HNC) patients treated with curative intent radiation therapy (RT).

Methods
From 2004 to 2010, 131 patients with HNC underwent RT. Patient's self-reported primary language and race/ethnicity were obtained at hospital registration. English proficiency was categorized as being English proficient (EP) or limited English proficient (LEP). Race/ethnicity was categorized as white, black and other (Hispanics and Asians). Patients were evaluated for locoregional (LRC), distant control (DC), overall (OS) and disease-free (DFS) survival.

Results
Fewer LEP patients (60.0\%) underwent chemoradiation compared to EP (83.8\%), P = 0.028. The three-year actuarial LRC for EP and LEP patients was 82.2\% and 58.3\%, respectively, P = 0.038. LEP patients had an increased risk of locoregional failure on univariate Cox regression analysis (hazard ratio, HR 2.4, 95\% CI, 1.0\textendash 5.8). No differences by English proficiency were seen for DC, OS and DFS. Race/ethnicity was not associated LRC, DC, OS and DFS.

Conclusion
Inferior locoregional control was observed in LEP patients receiving RT for HNC. Potential health disparities as a result of limited English proficiency require further investigation.

Practice implications
Patient education, use of culturally sensitive interpreter and patient navigation services, and improved patient compliance should be considered in head and neck cancer patients receiving complex multidisciplinary care.},
  journal = {Patient education and counseling},
  number = {2},
  pmcid = {PMC5014351},
  pmid = {25190640}
}

@article{revenig13,
  title = {Too Frail for Surgery? {{Initial}} Results of a Large Multidisciplinary Prospective Study Examining Preoperative Variables Predictive of Poor Surgical Outcomes},
  shorttitle = {Too Frail for Surgery?},
  author = {Revenig, Louis M. and Canter, Daniel J. and Taylor, Maxwell D. and Tai, Caroline and Sweeney, John F. and Sarmiento, Juan M. and Kooby, David A. and Maithel, Shishir K. and Master, Viraj A. and Ogan, Kenneth},
  year = {2013},
  month = oct,
  volume = {217},
  pages = {665-670.e1},
  issn = {1879-1190},
  doi = {10.1016/j.jamcollsurg.2013.06.012},
  abstract = {BACKGROUND: The decision as to whether a patient can tolerate surgery is often subjective and can misjudge a patient's true physiologic state. The concept of frailty is an important assessment tool in the geriatric medical population, but has only recently gained attention in surgical patients. Frailty potentially represents a measureable phenotype, which, if quantified with a standardized protocol, could reliably estimate the risk of adverse surgical outcomes.
STUDY DESIGN: Frailty was prospectively evaluated in the clinic setting in patients consenting for major general, oncologic, and urologic procedures. Evaluation included an established assessment tool (Hopkins Frailty Score), self-administered questionnaires, clinical assessment of performance status, and biochemical measures. Primary outcome was 30-day postoperative complications.
RESULTS: There were 189 patients evaluated: 117 from urology, 52 from surgical oncology, and 20 from general surgery clinics. Mean age was 62 years, 59.8\% were male, and 71.4\% were Caucasian. Patients who scored intermediately frail or frail on the Hopkins Frailty Score were more likely to experience postoperative complications (odds ratio [OR] 2.07, 95\% CI 1.05 to 4.08, p = 0.036). Of all other preoperative assessment tools, only higher hemoglobin (p = 0.033) had a significant association and was protective for 30-day complications.
CONCLUSIONS: The aggregate score of patients as "intermediately frail or frail" on the Hopkins Frailty Score was predictive of a patient experiencing a postoperative complication. This preoperative assessment tool may prove beneficial when weighing the risks and benefits of surgery, allowing objective data to guide surgical decision-making and patient counseling.},
  journal = {Journal of the American College of Surgeons},
  keywords = {Adult,Aged,Aged; 80 and over,American Society of Anesthesiologists,ASA,BMI,body mass index,CCI,Center for Epidemiologic Studies Depression Scale,CES-D,Charlson Comorbidity Index,Cohort Studies,Eastern Cooperative Oncology Group,ECOG,Female,Frail Elderly,Geriatric Assessment,Health Status,Humans,Male,Middle Aged,Outcome Assessment (Health Care),Patient Selection,Postoperative Complications,Predictive Value of Tests,Risk Assessment,Risk Factors,Treatment Outcome,Young Adult},
  language = {eng},
  number = {4},
  pmid = {24054409}
}

@article{reyes17,
  title = {Implementation of a {{Clinical Documentation Improvement Curriculum Improves Quality Metrics}} and {{Hospital Charges}} in an {{Academic Surgery Department}}},
  author = {Reyes, Cynthia and Greenbaum, Alissa and Porto, Catherine and Russell, John C.},
  year = {2017},
  month = mar,
  volume = {224},
  pages = {301--309},
  issn = {1879-1190},
  doi = {10.1016/j.jamcollsurg.2016.11.010},
  abstract = {BACKGROUND: Accurate clinical documentation (CD) is necessary for many aspects of modern health care, including excellent communication, quality metrics reporting, and legal documentation. New requirements have mandated adoption of ICD-10-CM coding systems, adding another layer of complexity to CD. A clinical documentation improvement (CDI) and ICD-10 training program was created for health care providers in our academic surgery department. We aimed to assess the impact of our CDI curriculum by comparing quality metrics, coding, and reimbursement before and after implementation of our CDI program.
STUDY DESIGN: A CDI/ICD-10 training curriculum was instituted in September 2014 for all members of our university surgery department. The curriculum consisted of didactic lectures, 1-on-1 provider training, case reviews, e-learning modules, and CD queries from nurse CDI staff and hospital coders. Outcomes parameters included monthly documentation completion rates, severity of illness (SOI), risk of mortality (ROM), case-mix index (CMI), all-payer refined diagnosis-related groups (APR-DRG), and Surgical Care Improvement Program (SCIP) metrics. Financial gain from responses to CDI queries was determined retrospectively.
RESULTS: Surgery department delinquent documentation decreased by 85\% after CDI implementation. Compliance with SCIP measures improved from 85\% to 97\%. Significant increases in surgical SOI, ROM, CMI, and APR-DRG (all p {$<$} 0.01) were found after CDI/ICD-10 training implementation. Provider responses to CDI queries resulted in an estimated \$4,672,786 increase in charges.
CONCLUSIONS: Clinical documentation improvement/ICD-10 training in an academic surgery department is an effective method to improve documentation rates, increase the hospital estimated reimbursement based on more accurate CD, and provide better compliance with surgical quality measures.},
  journal = {Journal of the American College of Surgeons},
  keywords = {Curriculum,Documentation,Hospital Charges,Humans,International Classification of Diseases,Program Evaluation,Quality Improvement,Retrospective Studies,Surgery Department; Hospital},
  language = {eng},
  number = {3},
  pmid = {27919741}
}

@article{ritt17,
  title = {Operationalizing a Frailty Index Using Routine Blood and Urine Tests},
  author = {Ritt, Martin and J{\"a}ger, Jakob and Ritt, Julia and Sieber, Cornel and Ga{\ss}mann, Karl},
  year = {2017},
  month = jun,
  volume = {Volume 12},
  pages = {1029--1040},
  issn = {1178-1998},
  doi = {10.2147/CIA.S131987},
  journal = {Clinical Interventions in Aging},
  language = {en}
}

@article{robinson11,
  title = {Frailty {{Predicts Increased Hospital}} and {{Six}}-{{Month Healthcare Cost Following Colorectal Surgery}} in {{Older Adults}}},
  author = {Robinson, Thomas N and Wu, Daniel S and Stiegmann, Gregory V and Moss, Marc},
  year = {2011},
  month = nov,
  volume = {202},
  pages = {511--514},
  issn = {0002-9610},
  doi = {10.1016/j.amjsurg.2011.06.017},
  abstract = {BACKGROUND
The purpose of this study was to determine the relationship of frailty and six-month post-operative costs.

METHODS
Subjects {$\geq$}65 years undergoing elective colorectal operations were enrolled in a prospective observational study. Frailty was assessed by a validated measure of function, cognition, nutrition, co-morbidity burden and geriatric syndromes. Frailty was quantified by summing the number of positive characteristics in each subject.

RESULTS
Sixty subjects (mean age 75{$\pm$}8 years) were studied. Inpatient mortality was 2\% (n=1). Overall, 40\% (n=24) of subjects were considered non-frail, 22\% (n=13) were pre-frail and 38\% (n=22) were frail. With advancing frailty, hospital cost increased (p{$<$}.001) and cost from discharge to six-months increased (p{$<$}.001). Higher degrees of frailty were related to increased rates of discharge institutionalization (p{$<$}.001) and thirty-day readmission (p=.044).

CONCLUSIONS
A simple, brief pre-operative frailty assessment accurately forecasts increased surgical hospital costs and post-discharge to six-month healthcare costs following colorectal operations in older adults.},
  journal = {American Journal of Surgery},
  number = {5},
  pmcid = {PMC3346286},
  pmid = {21890098}
}

@article{robinson11a,
  title = {Accumulated {{Frailty Characteristics Predict Postoperative Discharge Institutionalization}} in the {{Geriatric Patient}}},
  author = {Robinson, Thomas N and Wallace, Jeffrey I and Wu, Daniel S and Wiktor, Arek and Pointer, Lauren and Pfister, Shirley M and Sharp, Terra J and Buckley, Mary J and Moss, Marc},
  year = {2011},
  month = jul,
  volume = {213},
  pages = {37--42},
  issn = {1072-7515},
  doi = {10.1016/j.jamcollsurg.2011.01.056},
  abstract = {Introduction
Frailty is a state of increased vulnerability to health-related stressors and can be measured by summing the number of frailty characteristics present in an individual. Discharge institutionalization (rather than discharge to home) represents disease burden and functional dependence following hospitalization. Our aim was to determine the relationship between frailty and need for post-operative discharge institutionalization.

Study Design
Subjects {$\geq$}65 years undergoing major elective operations requiring post-operative ICU admission were enrolled. Discharge institutionalization was defined as need for institutionalized care at hospital discharge. Fourteen pre-operative frailty characteristics were measured in six domains: co-morbidity burden, function, nutrition, cognition geriatric syndromes and extrinsic frailty.

Results
223 subjects (mean age 73{$\pm$}6 years) were studied. Discharge institutionalization occurred in 30\% (66). Frailty characteristics related to need for post-operative discharge institutionalization included: older age, Charlson {$\geq$}3, Hematocrit {$<$}35\%, any functional dependence, Up-and-Go {$\geq$}15 seconds, albumin {$<$}3.4 mg/dL, Mini-Cog {$\leq$}3, and having fallen within six-months (p{$<$}.0001 for all comparisons). Multivariate logistic regression retained prolonged timed up-and-go (p{$<$}.0001) and any functional dependence (p{$<$}.0001) as the variables most closely related to need for discharge institutionalization. An increased number of frailty characteristics present in any one subject resulted in increased rate of discharge institutionalization.

Conclusions
Nearly one in three geriatric patients required discharge to an institutional care facility following major surgery. The frailty characteristics of prolonged up-and-go and any functional dependence were most closely related to the need for discharge institutionalization. Accumulation of a higher number of frailty characteristics in any one geriatric patient increased their risk of discharge institutionalization.},
  journal = {Journal of the American College of Surgeons},
  number = {1},
  pmcid = {PMC3132184},
  pmid = {21435921}
}

@article{robinson13,
  title = {Simple {{Frailty Score Predicts Post}}-{{Operative Complications Across Surgical Specialties}}},
  author = {Robinson, Thomas N and Wu, Daniel S and Pointer, Lauren and Dunn, Christina L and Cleveland, Joseph C and Moss, Marc},
  year = {2013},
  month = oct,
  volume = {206},
  pages = {544--550},
  issn = {0002-9610},
  doi = {10.1016/j.amjsurg.2013.03.012},
  abstract = {Introduction
Our purpose was to determine the relationship between pre-operative frailty and the occurrence of postoperative complications following colorectal and cardiac operations.

Study Design
Patients {$\geq$}65 years undergoing elective colorectal or cardiac surgery were enrolled. Seven baseline frailty traits were measured pre-operatively: Katz Score {$\leq$}5, Timed Up-and-Go {$\geq$}15 seconds, Charlson Index {$\geq$}3, anemia{$<$}35\%, Mini-Cog score {$\leq$}3, albumin{$<$}3.4gm/dL and {$\geq$}1 fall within six-months. Patients were categorized by the number of positive traits: non-frail: 0\textendash 1 trait, pre-frail: 2\textendash 3 traits and frail: {$\geq$}4 traits.

Results
201 subjects (age 74{$\pm$}6 years) were studied. Preoperative frailty was associated with increased postoperative complications following colorectal (non-frail 21\%, pre-frail 40\% and frail 58\%; p=0.016) and cardiac operations (non-frail 17\%, pre-frail 28\% and frail 56\%; p{$<$}0.001). This finding in both groups was independent of advancing age. Frail individuals in both groups had longer hospital stays and higher 30-day readmission rates. Receiver operating characteristic curves examining frailty's ability to forecast complications were: colorectal (0.702; p=0.004) and cardiac (0.711; p{$<$}0.001).

Conclusion
A simple pre-operative frailty score defines older adults at higher risk for postoperative complications across surgical specialties.},
  journal = {American journal of surgery},
  number = {4},
  pmcid = {PMC3788864},
  pmid = {23880071}
}

@article{rockwood05,
  ids = {rockwood05a},
  title = {A Global Clinical Measure of Fitness and Frailty in Elderly People},
  author = {Rockwood, K.},
  year = {2005},
  month = aug,
  volume = {173},
  pages = {489--495},
  issn = {0820-3946, 1488-2329},
  doi = {10.1503/cmaj.050051},
  journal = {Canadian Medical Association Journal},
  language = {en},
  number = {5}
}

@article{rockwood06,
  title = {Long-{{Term Risks}} of {{Death}} and {{Institutionalization}} of {{Elderly People}} in {{Relation}} to {{Deficit Accumulation}} at {{Age}} 70: {{LONG}}-{{TERM RISK OF DEATH DEFINED BY AGE}} 70},
  shorttitle = {Long-{{Term Risks}} of {{Death}} and {{Institutionalization}} of {{Elderly People}} in {{Relation}} to {{Deficit Accumulation}} at {{Age}} 70},
  author = {Rockwood, Kenneth and Mitnitski, Arnold and Song, Xiaowei and Steen, Bertil and Skoog, Ingmar},
  year = {2006},
  month = jun,
  volume = {54},
  pages = {975--979},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2006.00738.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {6}
}

@article{rockwood07,
  title = {Frailty in {{Relation}} to the {{Accumulation}} of {{Deficits}}},
  author = {Rockwood, K. and Mitnitski, A.},
  year = {2007},
  month = jul,
  volume = {62},
  pages = {722--727},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/62.7.722},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  language = {en},
  number = {7}
}

@article{rockwood07a,
  ids = {rockwood07b},
  title = {A {{Comparison}} of {{Two Approaches}} to {{Measuring Frailty}} in {{Elderly People}}},
  author = {Rockwood, K. and Andrew, M. and Mitnitski, A.},
  year = {2007},
  month = jul,
  volume = {62},
  pages = {738--743},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/62.7.738},
  abstract = {BACKGROUND: Many definitions of frailty exist, but few have been directly compared. We compared the relationship between a definition of frailty based on a specific phenotype with one based on an index of deficit accumulation.
METHODS: The data come from all 2305 people 70 years old and older who composed the clinical examination cohort of the second wave of the Canadian Study of Health and Aging. We tested convergent validity by correlating the measures with each other and with other health status measures, and analyzed cumulative index distributions in relation to phenotype. To test criterion validity, we evaluated survival (institutionalization and all-cause mortality) by frailty index (FI) score, stratified by the phenotypic definitions as "robust," "pre-frail," and "frail."
RESULTS: The measures correlated moderately well with each other (R=0.65) and with measures of function (phenotypic definition R=0.66; FI R=0.73) but less well with cognition (phenotypic definition R=-0.35; FI R=-0.58). The median FI scores increased from 0.12 for the robust to 0.30 for the pre-frail and 0.44 for the frail. Survival was also lower with increasing frailty, and institutionalization was more common, but within each phenotypic class, there were marked differences in outcomes based on the FI values-e.g., among robust people, the median 5-year survival for those with lower FI values was 85\%, compared with 55\% for those with higher FI values.
CONCLUSION: The phenotypic definition of frailty, which offers ready clinical operationalization, discriminates broad levels of risk. The FI requires additional clinical translation, but allows the risk of adverse outcomes to be defined more precisely.},
  journal = {The Journals of Gerontology Series A: Biological Sciences and Medical Sciences},
  keywords = {Aged,Frail Elderly,Humans,Institutionalization,Models; Theoretical,Phenotype,Survival Rate},
  language = {en},
  number = {7},
  pmid = {17634321}
}

@article{romano93,
  title = {Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Data: Differing Perspectives},
  shorttitle = {Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Data},
  author = {Romano, P. S. and Roos, L. L. and Jollis, J. G.},
  year = {1993},
  month = oct,
  volume = {46},
  pages = {1075-1079; discussion 1081-1090},
  issn = {0895-4356},
  journal = {Journal of Clinical Epidemiology},
  keywords = {Acute Disease,Chronic Disease,Comorbidity,Databases; Factual,Disease,Health Services Research,Humans,Logistic Models,Models; Statistical,Mortality,Outcome Assessment (Health Care),Prognosis,Proportional Hazards Models,Risk Factors,Severity of Illness Index,Surgical Procedures; Operative,United States},
  language = {eng},
  number = {10},
  pmid = {8410092}
}

@article{romano93a,
  title = {Presentation Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Data: {{Differing}} Perspectives},
  shorttitle = {Presentation Adapting a Clinical Comorbidity Index for Use with {{ICD}}-9-{{CM}} Administrative Data},
  author = {Romano, Patrick S. and Roos, Leslie L. and Jollis, James G.},
  year = {1993},
  month = oct,
  volume = {46},
  pages = {1075--1079},
  issn = {08954356},
  doi = {10.1016/0895-4356(93)90103-8},
  journal = {Journal of Clinical Epidemiology},
  language = {en},
  number = {10}
}

@article{rothman08,
  title = {Prognostic {{Significance}} of {{Potential Frailty Criteria}}: {{PROGNOSTIC SIGNIFICANCE OF POTENTIAL FRAILTY CRITERIA}}},
  shorttitle = {Prognostic {{Significance}} of {{Potential Frailty Criteria}}},
  author = {Rothman, Marc D. and {Leo-Summers}, Linda and Gill, Thomas M.},
  year = {2008},
  month = dec,
  volume = {56},
  pages = {2211--2216},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2008.02008.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {12}
}

@article{ryan13,
  title = {Will {{Value}}-{{Based Purchasing Increase Disparities}} in {{Care}}?},
  author = {Ryan, Andrew M.},
  year = {2013},
  month = dec,
  volume = {369},
  pages = {2472--2474},
  issn = {0028-4793},
  doi = {10.1056/NEJMp1312654},
  abstract = {U.S. hospitals caring for more disadvantaged patients fared worse in the first year of Medicare's Hospital Value-Based Purchasing program. Over time, such resource reductions may cause the quality of care to deteriorate in hospitals serving more disadvantaged patients.},
  journal = {New England Journal of Medicine},
  number = {26},
  pmid = {24369072}
}

@article{ryan15,
  title = {The {{Early Effects}} of {{Medicare}}'s {{Mandatory Hospital Pay}}-for-{{Performance Program}}},
  author = {Ryan, Andrew M and Burgess, James F and Pesko, Michael F and Borden, William B and Dimick, Justin B},
  year = {2015},
  month = feb,
  volume = {50},
  pages = {81--97},
  issn = {0017-9124},
  doi = {10.1111/1475-6773.12206},
  abstract = {Objective
To evaluate the impact of hospital value-based purchasing (HVBP) on clinical quality and patient experience during its initial implementation period (July 2011\textendash March 2012).

Data Sources
Hospital-level clinical quality and patient experience data from Hospital Compare from up to 5~years before and three quarters after HVBP was initiated.

Study Design
Acute care hospitals were exposed to HVBP by mandate while critical access hospitals and hospitals located in Maryland~were not exposed. We performed a difference-in-differences analysis, comparing performance on 12 incentivized clinical process and 8 incentivized patient experience measures between hospitals exposed to the program and a matched comparison group of nonexposed hospitals. We also evaluated whether hospitals that were ultimately exposed to HVBP may have anticipated the program by improving quality in advance of its introduction.

Principal Findings
Difference-in-differences estimates indicated that hospitals that were exposed to HVBP did not show greater improvement for either the clinical process or patient experience measures during the program's first implementation period. Estimates from our preferred specification showed that HVBP was associated with a 0.51 percentage point reduction in composite quality for the clinical process measures (p~{$>~$}.10, 95 percent CI: -1.37, 0.34) and a 0.30 percentage point reduction in composite quality for the patient experience measures (p~{$>~$}.10, 95 percent CI: -0.79, 0.19). We found some evidence that hospitals improved performance on clinical process measures prior to the start of HVBP, but no evidence of this phenomenon for the patient experience measures.

Conclusions
The timing of the financial incentives in HVBP was not associated with improved quality of care. It is unclear whether improvement for the clinical process measures prior to the start of HVBP was driven by the expectation of the program or was the result of other factors.},
  journal = {Health Services Research},
  number = {1},
  pmcid = {PMC4319872},
  pmid = {25040485}
}

@article{samson16,
  title = {Examining {{Measures}} of {{Income}} and {{Poverty}} in {{Medicare Administrative Data}}},
  author = {Samson, Lok Wong and Finegold, Kenneth and Ahmed, Azeem and Jensen, Matthew and Filice, Clara E. and Joynt, Karen E.},
  year = {2016},
  month = jul,
  issn = {1537-1948},
  doi = {10.1097/MLR.0000000000000606},
  abstract = {Disparities by economic status are observed in the health status and health outcomes of Medicare beneficiaries. For health services and health policy researchers, one barrier to addressing these disparities is the ability to use Medicare data to ascertain information about an individual's income level or poverty, because Medicare administrative data contains limited information about individual economic status. Information gleaned from other sources-such as the Medicaid and Supplemental Security Income programs-can be used in some cases to approximate the income of Medicare beneficiaries. However, such information is limited in its availability and applicability to all beneficiaries. Neighborhood-level measures of income can be used to infer individual-level income, but level of neighborhood aggregation impacts accuracy and usability of the data. Community-level composite measures of economic status have been shown to be associated with health and health outcomes of Medicare beneficiaries and may capture neighborhood effects that are separate from individual effects, but are not readily available in Medicare data and do not serve to replace information about individual economic status. There is no single best method of obtaining income data from Medicare files, but understanding strengths and limitations of different approaches to identifying economic status will help researchers choose the best method for their particular purpose, and help policymakers interpret studies using measures of income.},
  journal = {Medical Care},
  language = {eng},
  pmid = {27479597}
}

@article{saxton11,
  title = {Preoperative {{Frailty}} and {{Quality}} of {{Life}} as {{Predictors}} of {{Postoperative Complications}}:},
  shorttitle = {Preoperative {{Frailty}} and {{Quality}} of {{Life}} as {{Predictors}} of {{Postoperative Complications}}},
  author = {Saxton, Adrienne and Velanovich, Vic},
  year = {2011},
  month = jun,
  volume = {253},
  pages = {1223--1229},
  issn = {0003-4932},
  doi = {10.1097/SLA.0b013e318214bce7},
  journal = {Annals of Surgery},
  language = {en},
  number = {6}
}

@article{searle08a,
  title = {A Standard Procedure for Creating a Frailty Index},
  author = {Searle, Samuel D and Mitnitski, Arnold and Gahbauer, Evelyne A and Gill, Thomas M and Rockwood, Kenneth},
  year = {2008},
  month = dec,
  volume = {8},
  issn = {1471-2318},
  doi = {10.1186/1471-2318-8-24},
  journal = {BMC Geriatrics},
  language = {en},
  number = {1}
}

@article{segal17,
  title = {Development of a {{Claims}}-Based {{Frailty Indicator Anchored}} to a {{Well}}-Established {{Frailty Phenotype}}:},
  shorttitle = {Development of a {{Claims}}-Based {{Frailty Indicator Anchored}} to a {{Well}}-Established {{Frailty Phenotype}}},
  author = {Segal, Jodi B. and Chang, Hsien-Yen and Du, Yu and Walston, Jeremy D. and Carlson, Michelle C. and Varadhan, Ravi},
  year = {2017},
  month = may,
  pages = {1},
  issn = {0025-7079},
  doi = {10.1097/MLR.0000000000000729},
  journal = {Medical Care},
  language = {en}
}

@article{segal17a,
  title = {Development of a {{Claims}}-Based {{Frailty Indicator Anchored}} to a {{Well}}-Established {{Frailty Phenotype}}:},
  shorttitle = {Development of a {{Claims}}-Based {{Frailty Indicator Anchored}} to a {{Well}}-Established {{Frailty Phenotype}}},
  author = {Segal, Jodi B. and Chang, Hsien-Yen and Du, Yu and D. Walston, Jeremy and C. Carlson, Michelle and Varadhan, Ravi},
  year = {2017},
  month = jul,
  volume = {55},
  pages = {716--722},
  issn = {0025-7079},
  doi = {10.1097/MLR.0000000000000729},
  journal = {Medical Care},
  language = {en},
  number = {7}
}

@article{shanafelt15,
  title = {Impact of Organizational Leadership on Physician Burnout and Satisfaction},
  author = {Shanafelt, Tait D. and Gorringe, Grace and Menaker, Ronald and Storz, Kristin A. and Reeves, David and Buskirk, Steven J. and Sloan, Jeff A. and Swensen, Stephen J.},
  year = {2015},
  month = apr,
  volume = {90},
  pages = {432--440},
  issn = {1942-5546},
  doi = {10.1016/j.mayocp.2015.01.012},
  abstract = {OBJECTIVE: To evaluate the impact of organizational leadership on the professional satisfaction and burnout of individual physicians working for a large health care organization.
PARTICIPANTS AND METHODS: We surveyed physicians and scientists working for a large health care organization in October 2013. Validated tools were used to assess burnout. Physicians also rated the leadership qualities of their immediate supervisor in 12 specific dimensions on a 5-point Likert scale. All supervisors were themselves physicians/scientists. A composite leadership score was calculated by summing scores for the 12 individual items (range, 12-60; higher scores indicate more effective leadership).
RESULTS: Of the 3896 physicians surveyed, 2813 (72.2\%) responded. Supervisor scores in each of the 12 leadership dimensions and composite leadership score strongly correlated with the burnout and satisfaction scores of individual physicians (all P{$<$}.001). On multivariate analysis adjusting for age, sex, duration of employment at Mayo Clinic, and specialty, each 1-point increase in composite leadership score was associated with a 3.3\% decrease in the likelihood of burnout (P{$<$}.001) and a 9.0\% increase in the likelihood of satisfaction (P{$<$}.001) of the physicians supervised. The mean composite leadership rating of each division/department chair (n=128) also correlated with the prevalence of burnout (correlation=-0.330; r(2)=0.11; P{$<$}.001) and satisfaction (correlation=0.684; r(2)=0.47; P{$<$}.001) at the division/department level.
CONCLUSION: The leadership qualities of physician supervisors appear to impact the well-being and satisfaction of individual physicians working in health care organizations. These findings have important implications for the selection and training of physician leaders and provide new insights into organizational factors that affect physician well-being.},
  journal = {Mayo Clinic Proceedings},
  keywords = {Adult,Aged,Attitude of Health Personnel,Burnout; Professional,Female,Humans,Institutional Practice,Job Satisfaction,Leadership,Male,Medical Staff,Middle Aged,Personnel Management,Physician Executives},
  language = {eng},
  number = {4},
  pmid = {25796117}
}

@article{shanafelt15a,
  title = {Changes in {{Burnout}} and {{Satisfaction With Work}}-{{Life Balance}} in {{Physicians}} and the {{General US Working Population Between}} 2011 and 2014},
  author = {Shanafelt, Tait D. and Hasan, Omar and Dyrbye, Lotte N. and Sinsky, Christine and Satele, Daniel and Sloan, Jeff and West, Colin P.},
  year = {2015},
  month = dec,
  volume = {90},
  pages = {1600--1613},
  issn = {1942-5546},
  doi = {10.1016/j.mayocp.2015.08.023},
  abstract = {OBJECTIVE: To evaluate the prevalence of burnout and satisfaction with work-life balance in physicians and US workers in 2014 relative to 2011.
PATIENTS AND METHODS: From August 28, 2014, to October 6, 2014, we surveyed both US physicians and a probability-based sample of the general US population using the methods and measures used in our 2011 study. Burnout was measured using validated metrics, and satisfaction with work-life balance was assessed using standard tools.
RESULTS: Of the 35,922 physicians who received an invitation to participate, 6880 (19.2\%) completed surveys. When assessed using the Maslach Burnout Inventory, 54.4\% (n=3680) of the physicians reported at least 1 symptom of burnout in 2014 compared with 45.5\% (n=3310) in 2011 (P{$<$}.001). Satisfaction with work-life balance also declined in physicians between 2011 and 2014 (48.5\% vs 40.9\%; P{$<$}.001). Substantial differences in rates of burnout and satisfaction with work-life balance were observed by specialty. In contrast to the trends in physicians, minimal changes in burnout or satisfaction with work-life balance were observed between 2011 and 2014 in probability-based samples of working US adults, resulting in an increasing disparity in burnout and satisfaction with work-life balance in physicians relative to the general US working population. After pooled multivariate analysis adjusting for age, sex, relationship status, and hours worked per week, physicians remained at an increased risk of burnout (odds ratio, 1.97; 95\% CI, 1.80-2.16; P{$<$}.001) and were less likely to be satisfied with work-life balance (odds ratio, 0.68; 95\% CI, 0.62-0.75; P{$<$}.001).
CONCLUSION: Burnout and satisfaction with work-life balance in US physicians worsened from 2011 to 2014. More than half of US physicians are now experiencing professional burnout.},
  journal = {Mayo Clinic Proceedings},
  keywords = {Adaptation; Psychological,Adult,Burnout; Professional,Depression,Female,Humans,Job Satisfaction,Male,Personal Satisfaction,Physicians,Prevalence,Suicidal Ideation,Surveys and Questionnaires,United States},
  language = {eng},
  number = {12},
  pmid = {26653297}
}

@article{shavers07,
  title = {Measurement of Socioeconomic Status in Health Disparities Research},
  author = {Shavers, Vickie L.},
  year = {2007},
  month = sep,
  volume = {99},
  pages = {1013--1023},
  issn = {0027-9684},
  abstract = {Socioeconomic status (SES) is frequently implicated as a contributor to the disparate health observed among racial/ ethnic minorities, women and elderly populations. Findings from studies that examine the role of SES and health disparities, however, have provided inconsistent results. This is due in part to the: 1) lack of precision and reliability of measures; 2) difficulty with the collection of individual SES data; 3) the dynamic nature of SES over a lifetime; 4) the classification of women, children, retired and unemployed persons; 5) lack of or poor correlation between individual SES measures; and 6) and inaccurate or misleading interpretation of study results. Choosing the best variable or approach for measuring SES is dependent in part on its relevance to the population and outcomes under study. Many of the commonly used compositional and contextual SES measures are limited in terms of their usefulness for examining the effect of SES on outcomes in analyses of data that include population subgroups known to experience health disparities. This article describes SES measures, strengths and limitations of specific approaches and methodological issues related to the analysis and interpretation of studies that examine SES and health disparities.},
  journal = {Journal of the National Medical Association},
  keywords = {Adolescent,Adult,Continental Population Groups,Delivery of Health Care,Ethnic Groups,Female,Health Services Accessibility,Health Services Research,Health Status Indicators,Humans,Male,Middle Aged,Minority Groups,Poverty,Social Class,Social Justice,Socioeconomic Factors,United States},
  language = {eng},
  number = {9},
  pmcid = {PMC2575866},
  pmid = {17913111}
}

@article{shih15,
  title = {Medicare's {{Hospital Readmission Reduction Program}} in {{Surgery May Disproportionately Affect Minority}}-{{Serving Hospitals}}},
  author = {Shih, Terry and Ryan, Andrew M. and Gonzalez, Andrew A. and Dimick, Justin B.},
  year = {2015},
  month = jun,
  volume = {261},
  pages = {1027--1031},
  issn = {0003-4932},
  doi = {10.1097/SLA.0000000000000778},
  abstract = {Objective
To project readmission penalties for hospitals performing cardiac surgery and examine how these penalties will affect minority-serving hospitals.

Background
The Hospital Readmission Reduction Program (HRRP) will potentially expand penalties for higher-than-predicted readmission rates to cardiac procedures in the near future. The impact of these penalties on minority-serving hospitals is unknown.

Methods
We examined national Medicare beneficiaries undergoing coronary artery bypass grafting (CABG) in 2008\textendash 2010 (N=255,250 patients, 1,186 hospitals). Using hierarchical logistic regression, we calculated hospital observed-to-expected readmission ratios. Hospital penalties were projected according to the HRRP formula using only CABG readmissions with a 3\% maximum penalty of total Medicare revenue. Hospitals were classified into quintiles according to proportion of black patients treated. Minority-serving hospitals were defined as hospitals in the top quintile while non-minority-serving hospitals those in the bottom quintile. Projected readmission penalties were compared across quintiles.

Results
Forty-seven percent of hospitals (559 of 1,186) were projected to be assessed a penalty. Twenty-eight percent of hospitals (330 of 1,186) would be penalized {$<$}1\% of total Medicare revenue while 5\% of hospitals (55 of 1,186) would receive the maximum 3\% penalty. Minority-serving hospitals were almost twice as likely to be penalized than non-minority-serving hospitals (61\% vs. 32\%) and were projected almost triple the reductions in reimbursement (\$112 million vs. \$41 million).

Conclusions
Minority-serving hospitals would disproportionately bear the burden of readmission penalties if expanded to include cardiac surgery. Given these hospitals' narrow profit margins, readmission penalties may have a profound impact on these hospitals' ability to care for disadvantaged patients.},
  journal = {Annals of surgery},
  number = {6},
  pmcid = {PMC4248020},
  pmid = {24887984}
}

@article{singh14,
  title = {Importance of Frailty in Patients with Cardiovascular Disease},
  author = {Singh, M. and Stewart, R. and White, H.},
  year = {2014},
  month = jul,
  volume = {35},
  pages = {1726--1731},
  issn = {0195-668X, 1522-9645},
  doi = {10.1093/eurheartj/ehu197},
  journal = {European Heart Journal},
  language = {en},
  number = {26}
}

@article{sinsky16,
  title = {Allocation of {{Physician Time}} in {{Ambulatory Practice}}: {{A Time}} and {{Motion Study}} in 4 {{Specialties}}},
  shorttitle = {Allocation of {{Physician Time}} in {{Ambulatory Practice}}},
  author = {Sinsky, Christine and Colligan, Lacey and Li, Ling and Prgomet, Mirela and Reynolds, Sam and Goeders, Lindsey and Westbrook, Johanna and Tutty, Michael and Blike, George},
  year = {2016},
  month = dec,
  volume = {165},
  pages = {753--760},
  issn = {1539-3704},
  doi = {10.7326/M16-0961},
  abstract = {Background: Little is known about how physician time is allocated in ambulatory care.
Objective: To describe how physician time is spent in ambulatory practice.
Design: Quantitative direct observational time and motion study (during office hours) and self-reported diary (after hours).
Setting: U.S. ambulatory care in 4 specialties in 4 states (Illinois, New Hampshire, Virginia, and Washington).
Participants: 57 U.S. physicians in family medicine, internal medicine, cardiology, and orthopedics who were observed for 430 hours, 21 of whom also completed after-hours diaries.
Measurements: Proportions of time spent on 4 activities (direct clinical face time, electronic health record [EHR] and desk work, administrative tasks, and other tasks) and self-reported after-hours work.
Results: During the office day, physicians spent 27.0\% of their total time on direct clinical face time with patients and 49.2\% of their time on EHR and desk work. While in the examination room with patients, physicians spent 52.9\% of the time on direct clinical face time and 37.0\% on EHR and desk work. The 21 physicians who completed after-hours diaries reported 1 to 2 hours of after-hours work each night, devoted mostly to EHR tasks.
Limitations: Data were gathered in self-selected, high-performing practices and may not be generalizable to other settings. The descriptive study design did not support formal statistical comparisons by physician and practice characteristics.
Conclusion: For every hour physicians provide direct clinical face time to patients, nearly 2 additional hours is spent on EHR and desk work within the clinic day. Outside office hours, physicians spend another 1 to 2 hours of personal time each night doing additional computer and other clerical work.
Primary Funding Source: American Medical Association.},
  journal = {Annals of Internal Medicine},
  keywords = {Adult,Ambulatory care,Cardiology,Electronic Health Records,Family Practice,Female,Humans,Internal Medicine,Male,Middle Aged,Orthopedics,Practice Management; Medical,Time and Motion Studies,Time Management,United States},
  language = {eng},
  number = {11},
  pmid = {27595430}
}

@article{song10,
  title = {Prevalence and 10-Year Outcomes of Frailty in Older Adults in Relation to Deficit Accumulation},
  author = {Song, Xiaowei and Mitnitski, Arnold and Rockwood, Kenneth},
  year = {2010},
  month = apr,
  volume = {58},
  pages = {681--687},
  issn = {1532-5415},
  doi = {10.1111/j.1532-5415.2010.02764.x},
  abstract = {OBJECTIVES: To evaluate the prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation.
DESIGN: Prospective cohort study.
SETTING: The National Population Health Survey of Canada, with frailty estimated at baseline (1994/95) and mortality follow-up to 2004/05.
PARTICIPANTS: Community-dwelling older adults (N=2,740, 60.8\% women) aged 65 to 102 from 10 Canadian provinces. During the 10-year follow-up, 1,208 died.
MEASUREMENTS: Self-reported health information was used to construct a frailty index (Frailty Index) as a proportion of deficits accumulated in individuals. The main outcome measure was mortality.
RESULTS: The prevalence of frailty increased with age in men and women (correlation coefficient=0.955-0.994, P{$<$}.001). The Frailty Index estimated that 622 (22.7\%, 95\% confidence interval (CI)=21.0-24.4\%) of the sample was frail. Frailty was more common in women (25.3\%, 95\% CI=23.2-27.5\%) than in men (18.6\%, 95\% CI=15.9-21.3\%). For those aged 85 and older, the Frailty Index identified 39.1\% (95\% CI=31.3-46.9\%) of men as frail, compared with 45.1\% (95\% CI=39.7-50.5\%) of women. Frailty significantly increased the risk of death, with an age- and sex-adjusted hazard ratio for the Frailty Index of 1.57 (95\% CI=1.41-1.74).
CONCLUSION: The prevalence of frailty increases with age and at any age lessens survival. The Frailty Index approach readily identifies frail people at risk of death, presumably because of its use of multiple health deficits in multidimensional domains.},
  journal = {Journal of the American Geriatrics Society},
  keywords = {Age Distribution,Aged,Aged; 80 and over,Analysis of Variance,Canada,Chi-Square Distribution,Comorbidity,Disabled Persons,Female,Frail Elderly,Geriatric Assessment,Health Status,Health Surveys,Humans,Logistic Models,Male,Mortality,Prevalence,Prospective Studies,Risk Assessment,ROC Curve,Severity of Illness Index,Sex Distribution,Statistics; Nonparametric,Survival Analysis},
  language = {ENG},
  number = {4},
  pmid = {20345864}
}

@article{soobader01,
  title = {Using Aggregate Geographic Data to Proxy Individual Socioeconomic Status: Does Size Matter?},
  shorttitle = {Using Aggregate Geographic Data to Proxy Individual Socioeconomic Status},
  author = {Soobader, M. and LeClere, F. B. and Hadden, W. and Maury, B.},
  year = {2001},
  month = apr,
  volume = {91},
  pages = {632--636},
  issn = {0090-0036},
  abstract = {OBJECTIVES: This study assessed whether aggregate-level measures of socioeconomic status (SES) are less biased as proxies for individual-level measures if the unit of geographic aggregation is small in size and population.
METHODS: National Health Interview Survey and census data were used to replicate analyses that identified the degree to which aggregate proxies of individual SES bias interpretations of the effects of SES on health.
RESULTS: Ordinary least squares regressions on self-perceived health showed that the coefficients for income and education measured at the tract and block group levels were larger than those at the individual level but smaller than those estimated by Geronimus et al. at the zip code level.
CONCLUSIONS: Researchers should be cautious about use of proxy measurement of individual SES even if proxies are calculated from small geographic units.},
  journal = {American Journal of Public Health},
  keywords = {Data Collection,Geography,Health Status Indicators,Humans,Research Design,Selection Bias,Social Class,United States},
  language = {eng},
  number = {4},
  pmcid = {PMC1446644},
  pmid = {11291379}
}

@article{southern17,
  title = {Deriving {{ICD}}-10 {{Codes}} for {{Patient Safety Indicators}} for {{Large}}-Scale {{Surveillance Using Administrative Hospital Data}}:},
  shorttitle = {Deriving {{ICD}}-10 {{Codes}} for {{Patient Safety Indicators}} for {{Large}}-Scale {{Surveillance Using Administrative Hospital Data}}},
  author = {Southern, Danielle A. and Burnand, Bernard and Droesler, Saskia E. and Flemons, Ward and Forster, Alan J. and Gurevich, Yana and Harrison, James and Quan, Hude and Pincus, Harold A. and Romano, Patrick S. and Sundararajan, Vijaya and Kostanjsek, Nenad and Ghali, William A.},
  year = {2017},
  month = mar,
  volume = {55},
  pages = {252--260},
  issn = {0025-7079},
  doi = {10.1097/MLR.0000000000000649},
  journal = {Medical Care},
  language = {en},
  number = {3}
}

@article{st.sauver11,
  title = {Use of a {{Medical Records Linkage System}} to {{Enumerate}} a {{Dynamic Population Over Time}}: {{The Rochester Epidemiology Project}}},
  shorttitle = {Use of a {{Medical Records Linkage System}} to {{Enumerate}} a {{Dynamic Population Over Time}}},
  author = {St. Sauver, Jennifer L. and Grossardt, Brandon R. and Yawn, Barbara P. and Melton, L. Joseph and Rocca, Walter A.},
  year = {2011},
  month = may,
  volume = {173},
  pages = {1059--1068},
  issn = {1476-6256, 0002-9262},
  doi = {10.1093/aje/kwq482},
  journal = {American Journal of Epidemiology},
  language = {en},
  number = {9}
}

@article{stow18,
  title = {Evaluating Frailty Scores to Predict Mortality in Older Adults Using Data from Population Based Electronic Health Records: Case Control Study},
  shorttitle = {Evaluating Frailty Scores to Predict Mortality in Older Adults Using Data from Population Based Electronic Health Records},
  author = {Stow, Daniel and Matthews, Fiona E and Barclay, Stephen and Iliffe, Steve and Clegg, Andrew and De Biase, Sarah and Robinson, Louise and Hanratty, Barbara},
  year = {2018},
  month = jul,
  volume = {47},
  pages = {564--569},
  issn = {0002-0729, 1468-2834},
  doi = {10.1093/ageing/afy022},
  journal = {Age and Ageing},
  language = {en},
  number = {4}
}

@article{stow18a,
  title = {Frailty Trajectories to Identify End of Life: A Longitudinal Population-Based Study},
  shorttitle = {Frailty Trajectories to Identify End of Life},
  author = {Stow, Daniel and Matthews, Fiona E. and Hanratty, Barbara},
  year = {2018},
  month = dec,
  volume = {16},
  pages = {171},
  issn = {1741-7015},
  doi = {10.1186/s12916-018-1148-x},
  journal = {BMC Medicine},
  language = {en},
  number = {1}
}

@article{strausbaugh01,
  title = {Emerging Health Care-Associated Infections in the Geriatric Population.},
  author = {Strausbaugh, Larry James},
  year = {2001},
  volume = {7},
  pages = {268},
  journal = {Emerging infectious diseases},
  number = {2}
}

@book{streiner95,
  title = {Health Measurement Scales: A Practical Guide to Their Development and Use},
  shorttitle = {Health Measurement Scales},
  author = {Streiner, David L. and Norman, Geoffrey R.},
  year = {1995},
  edition = {2nd ed},
  publisher = {{Oxford University Press}},
  address = {{Oxford ; New York}},
  isbn = {978-0-19-262670-7 978-0-19-262637-0},
  keywords = {Epidemiologic Methods,Evaluation,Health Status Indicators,Health Surveys,Measurement,Medical care,Public health},
  lccn = {RA408.5 .S77 1995},
  series = {Oxford Medical Publications}
}

@article{sutorius16,
  title = {Comparison of 10 Single and Stepped Methods to Identify Frail Older Persons in Primary Care: Diagnostic and Prognostic Accuracy},
  shorttitle = {Comparison of 10 Single and Stepped Methods to Identify Frail Older Persons in Primary Care},
  author = {Sutorius, Fleur L. and Hoogendijk, Emiel O. and Prins, Bernard A. H. and {van Hout}, Hein P. J.},
  year = {2016},
  month = dec,
  volume = {17},
  issn = {1471-2296},
  doi = {10.1186/s12875-016-0487-y},
  journal = {BMC Family Practice},
  language = {en},
  number = {1}
}

@article{theou13,
  title = {Operationalization of {{Frailty Using Eight Commonly Used Scales}} and {{Comparison}} of {{Their Ability}} to {{Predict All}}-{{Cause Mortality}}},
  author = {Theou, Olga and Brothers, Thomas D. and Mitnitski, Arnold and Rockwood, Kenneth},
  year = {2013},
  month = sep,
  volume = {61},
  pages = {1537--1551},
  issn = {00028614},
  doi = {10.1111/jgs.12420},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {9}
}

@article{theou14,
  title = {Identifying {{Common Characteristics}} of {{Frailty Across Seven Scales}}},
  author = {Theou, Olga and Brothers, Thomas D. and Pe{\~n}a, Fernando G. and Mitnitski, Arnold and Rockwood, Kenneth},
  year = {2014},
  month = may,
  volume = {62},
  pages = {901--906},
  issn = {00028614},
  doi = {10.1111/jgs.12773},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {5}
}

@article{thompson17,
  title = {Most {{Hospitals Received Annual Penalties For Excess Readmissions}}, {{But Some Fared Better Than Others}}},
  author = {Thompson, Michael P. and Waters, Teresa M. and Kaplan, Cameron M. and Cao, Yu and Bazzoli, Gloria J.},
  year = {2017},
  month = may,
  volume = {36},
  pages = {893--901},
  issn = {1544-5208},
  doi = {10.1377/hlthaff.2016.1204},
  abstract = {The Hospital Readmissions Reduction Program (HRRP) initiated by the Affordable Care Act levies financial penalties against hospitals with excess thirty-day Medicare readmissions. We sought to understand the penalty burden over the program's first five years, focusing on characteristics of hospitals that received penalties during all five years, how penalties changed over time, and the relationship between baseline and subsequent performance. More than half of participating hospitals were penalized by the Centers for Medicare and Medicaid Services in all five years of the program. From fiscal years 2013 to 2017, the growth in average penalties was modest, doubling from 0.29~percent to 0.60~percent, despite increasing opportunities for penalization. The penalty burden was greater in hospitals that were urban, major teaching, large, or for-profit and that treated larger shares of Medicare or socioeconomically disadvantaged patients. Surprisingly, hospitals treating greater proportions of medically complex Medicare patients had a lower cumulative penalty burden compared to those treating fewer proportions of these patients. Lastly, we found that hospitals with high baseline penalties in the first year continued to receive significantly higher penalties in subsequent years. For many hospitals, the HRRP leads to persistent penalization and limited capacity to reduce penalty burden. Alternative structures might avoid persistent penalization, while still motivating reductions in hospital readmissions.},
  journal = {Health Affairs (Project Hope)},
  keywords = {Hospitals,Medicare,Pay for Performance,Readmissions},
  language = {eng},
  number = {5},
  pmid = {28461357}
}

@article{torpy06,
  title = {Frailty in {{Older Adults}}},
  author = {Torpy, Janet M. and Lynm, Cassio and Glass, Richard M.},
  year = {2006},
  month = nov,
  volume = {296},
  pages = {2280--2280},
  issn = {0098-7484},
  doi = {10.1001/jama.296.18.2280},
  abstract = {Frailty, commonly associated with aging, includes several characteristics (see below). Frail older adults are weak, often have many complex medical problems, have a lower ability for independent living, may have impaired mental abilities, and often require assistance for daily activities (dressing,...},
  journal = {JAMA},
  number = {18}
}

@article{tsiouris13,
  title = {A Modified Frailty Index to Assess Morbidity and Mortality after Lobectomy},
  author = {Tsiouris, Athanasios and Hammoud, Zane T. and Velanovich, Vic and Hodari, Arielle and Borgi, Jamil and Rubinfeld, Ilan},
  year = {2013},
  month = jul,
  volume = {183},
  pages = {40--46},
  issn = {00224804},
  doi = {10.1016/j.jss.2012.11.059},
  journal = {Journal of Surgical Research},
  language = {en},
  number = {1}
}

@article{uppal15,
  title = {Frailty Index Predicts Severe Complications in Gynecologic Oncology Patients},
  author = {Uppal, Shitanshu and Igwe, Elena and Rice, Laurel W. and Spencer, Ryan J. and Rose, Stephen L.},
  year = {2015},
  month = apr,
  volume = {137},
  pages = {98--101},
  issn = {00908258},
  doi = {10.1016/j.ygyno.2015.01.532},
  journal = {Gynecologic Oncology},
  language = {en},
  number = {1}
}

@article{villareal06,
  title = {Effect of {{Weight Loss}} and {{Exercise}} on {{Frailty}} in {{Obese Older Adults}}},
  author = {Villareal, Dennis T. and Banks, Marian and Sinacore, David R. and Siener, Catherine and Klein, Samuel},
  year = {2006},
  month = apr,
  volume = {166},
  pages = {860},
  issn = {0003-9926},
  doi = {10.1001/archinte.166.8.860},
  journal = {Archives of Internal Medicine},
  language = {en},
  number = {8}
}

@article{wang14,
  title = {Frailty {{Attenuates}} the {{Impact}} of {{Metformin}} on {{Reducing Mortality}} in {{Older Adults}} with {{Type}} 2 {{Diabetes}}},
  author = {Wang, Chen-Pin and Lorenzo, Carlos and Espinoza, Sara E.},
  year = {2014},
  volume = {2},
  abstract = {OBJECTIVE: To determine whether the protective effect of metformin against death is modified by frailty status in older adults with type 2 diabetes.
RESEARCH DESIGN AND METHODS: We conducted a cohort study during October 1, 1999-September 30, 2006 among veterans aged 65-89 years old with type 2 diabetes but without history of liver, renal diseases, or cancers, who had sulfonylureas or metformin as the sole antidiabetic drug for {$\geq$}180 days. The Cox proportional hazard model was used to compare hazard rates of all-cause mortality between the metformin and sulfonylurea users adjusting for the propensity score of metformin use and covariates: age, race/ethnicity, diabetes duration, Charlson comorbidity score, statin use, smoking status, BMI, LDL, and HbA1c.
RESULTS: In this cohort of 2,415 veterans, 307 (12.7\%) were metformin users, 2,108 (87.3\%) were sulfonylurea users, the mean age was 73.7{$\pm$}5.2 years, the mean study period was 5.6{$\pm$}2.3 years, the mean HbA1c at baseline was 6.7{$\pm$}1.0\%, 23\% had diabetes for {$\geq$}10 years, and 43.6\% (N=1,048) died during the study period. For patients with and without frailty, the adjusted hazard ratio (HR) of death for metformin vs. sulfonylurea use were 0.92 (95\% CI=0.90-1.31, p-value=0.19) and 0.69 (95\% CI = 0.60-0.79, p-value{$<$}0.001), respectively. Logistic regression analyses showed that metformin (vs. sulfonylurea) was significantly associated with a decreased odds of frailty (OR: 0.66, 95\% CI: 0.61-0.71, p-value {$<$}.0001).
CONCLUSION: Our study suggests that metformin could potentially promote longevity via preventing frailty in older adults with type 2 diabetes.},
  journal = {Journal of Endocrinology, Diabetes \& Obesity},
  keywords = {Frailty,Metformin,Mortality,Type 2 diabetes},
  language = {ENG},
  number = {2},
  pmcid = {PMC4264048},
  pmid = {25506599}
}

@article{wang16,
  title = {Metformin for {{Reducing Racial}}/{{Ethnic Difference}} in {{Prostate Cancer Incidence}} for {{Men}} with {{Type}} 2 {{Diabetes}}},
  author = {Wang, Chen-Pin and Lehman, Donna M. and Lam, Yui-Wing F. and Kuhn, John G. and Mahalingam, Devalingam and Weitman, Steven and Lorenzo, Carlos and Downs, John R. and Stuart, Elizabeth A and Hernandez, Javier and Thompson, Ian M. and Ramirez, Amelie G.},
  year = {2016},
  month = oct,
  volume = {9},
  pages = {779--787},
  issn = {1940-6207},
  doi = {10.1158/1940-6207.CAPR-15-0425},
  abstract = {Racial/ethnic disparity in prostate cancer (PCa) is under studied in men with diabetes who are at higher risk for aggressive PCa. This study assessed the race/ethnic disparity in PCa incidence for men with type 2 diabetes (T2D), and whether the impact of metformin on PCa incidence varied by race/ethnicity. We conducted a retrospective study in 76,733 male veterans with T2D during 2003\textendash 2012. Cox proportional hazard model adjusting for covariates and propensity scores of metformin use and race/ethnic group membership were utilized to compute the hazard ratio (HR) of PCa incidence associated with race/ethnicity, and compare HR associated with metformin use between race/ethnic groups. Mean follow-up was 6.4{$\pm$}2.8 years; 7\% were Hispanics; 17\% were African American (AA); mean age was 67.8{$\pm$}9.8 years; 5.2\% developed PCa; 38.9\% used metformin. Among these diabetic men without metformin use, PCa incidence was higher in Hispanics and AA than in non-Hispanic White (NHW). Use of metformin alone or metformin+statins was associated with a greater PCa incidence reduction in Hispanics compared to NHW, but not between AA and NHW. Use of metformin+finasteride was associated with a greater PCa incidence reduction in Hispanics and AA compared to NHW. Our results suggested that metformin treatment could be a potential strategy to reduce PCa incidence in the minority populations who are at high risk for fatal PCa. It will be important to further examine the pleiotropic effects of metformin in multi-race/ethnic prospective studies to better inform clinical management, and potentially reduce racial/ethnic disparity in PCa incidence among diabetic men.},
  journal = {Cancer prevention research (Philadelphia, Pa.)},
  number = {10},
  pmcid = {PMC5042809},
  pmid = {27026681}
}

@article{west17,
  title = {Genomics, {{Health Disparities}}, and {{Missed Opportunities}} for the {{Nation}}'s {{Research Agenda}}},
  author = {West, Kathleen McGlone and Blacksher, Erika and Burke, Wylie},
  year = {2017},
  month = may,
  volume = {317},
  pages = {1831--1832},
  issn = {1538-3598},
  doi = {10.1001/jama.2017.3096},
  journal = {JAMA},
  keywords = {Genetic Predisposition to Disease,Genomics,Health Status Disparities,Healthcare Disparities,Human Genome Project,Humans,Research,United States},
  language = {eng},
  number = {18},
  pmid = {28346599}
}

@article{woods05,
  title = {Frailty: Emergence and Consequences in Women Aged 65 and Older in the {{Women}}'s {{Health Initiative Observational Study}}},
  shorttitle = {Frailty},
  author = {Woods, Nancy Fugate and LaCroix, Andrea Z. and Gray, Shelly L. and Aragaki, Aaron and Cochrane, Barbara B. and Brunner, Robert L. and Masaki, Kamal and Murray, Anne and Newman, Anne B. and {Women's Health Initiative}},
  year = {2005},
  month = aug,
  volume = {53},
  pages = {1321--1330},
  issn = {0002-8614},
  doi = {10.1111/j.1532-5415.2005.53405.x},
  abstract = {OBJECTIVES: To define frailty using simple indicators; to identify risk factors for frailty as targets for prevention; and to investigate the predictive validity of this frailty classification for death, hospitalization, hip fracture, and activity of daily living (ADL) disability.
DESIGN: Prospective study, the Women's Health Initiative Observational Study.
SETTING: Forty U.S. clinical centers.
PARTICIPANTS: Forty thousand six hundred fifty-seven women aged 65 to 79 at baseline.
MEASUREMENTS: Components of frailty included self-reported muscle weakness/impaired walking, exhaustion, low physical activity, and unintended weight loss between baseline and 3 years of follow-up. Death, hip fractures, ADL disability, and hospitalizations were ascertained during an average of 5.9 years of follow-up.
RESULTS: Baseline frailty was classified in 16.3\% of participants, and incident frailty at 3-years was 14.8\%. Older age, chronic conditions, smoking, and depressive symptom score were positively associated with incident frailty, whereas income, moderate alcohol use, living alone, and self-reported health were inversely associated. Being underweight, overweight, or obese all carried significantly higher risk of frailty than normal weight. Baseline frailty independently predicted risk of death (hazard ratio (HR)=1.71, 95\% confidence interval (CI)=1.48-1.97), hip fracture (HR=1.57, 95\% CI=1.11-2.20), ADL disability (odds ratio (OR)=3.15, 95\% CI=2.47-4.02), and hospitalizations (OR=1.95, 95\% CI=1.72-2.22) after adjustment for demographic characteristics, health behaviors, disability, and comorbid conditions.
CONCLUSION: These results support the robustness of the concept of frailty as a geriatric syndrome that predicts several poor outcomes in older women. Underweight, obesity, smoking, and depressive symptoms are strongly associated with the development of frailty and represent important targets for prevention.},
  journal = {Journal of the American Geriatrics Society},
  keywords = {Activities of Daily Living,Aged,Chronic Disease,Depression,Female,Follow-Up Studies,Frail Elderly,Hip Fractures,Hospitalization,Humans,Obesity,Outcome Assessment (Health Care),Prospective Studies,Risk Factors,Smoking,Walking,Weight Loss},
  language = {ENG},
  number = {8},
  pmid = {16078957}
}

@article{yorke17,
  title = {Development of a {{Rat Clinical Frailty Index}}},
  author = {Yorke, Amy and Kane, Alice E. and Hancock Friesen, Camille L. and Howlett, Susan E. and O'Blenes, Stacy},
  year = {2017},
  month = jul,
  volume = {72},
  pages = {897--903},
  issn = {1079-5006, 1758-535X},
  doi = {10.1093/gerona/glw339},
  journal = {The Journals of Gerontology: Series A},
  language = {en},
  number = {7}
}


@article{meissner20a,
  title = {Engagement Science: {{The}} Core of Dissemination, Implementation, and Translational Research Science},
  shorttitle = {Engagement Science},
  author = {Meissner, Paul and Cottler, Linda B. and Eder, Milton ``Mickey'' and Michener, J. Lloyd},
  year = {2020},
  month = jun,
  volume = {4},
  pages = {216--218},
  issn = {2059-8661},
  doi = {10.1017/cts.2020.8},
  abstract = {Abstract             Stakeholder engagement is acknowledged as central to dissemination and implementation (D\&I) of research that generates and answers new clinical and health service research questions. There is both benefit and risk in conducting stakeholder engagement. Done wrong, it can damage trust and adversely impact study results, outcomes, and reputations. Done correctly with sensitivity, inclusion, and respect, it can significantly facilitate improvements in research prioritization, communication, design, recruitment strategies, and ultimately provide results useful to improve population and individual health. There is a recognized science of stakeholder engagement, but a general lack of knowledge that matches its strategies and approaches to particular populations of interest based on history and characteristics. This article reviews stakeholder engagement, provides several examples of its application across the range of translational research, and recommends that Clinical Translational Science Awards, with their unique geographical, systems, and historical characteristics, actively participate in deepening our understanding of stakeholder engagement science and methods within implementation and dissemination research. These recommendations include (a) development of an inventory of successful stakeholder engagement strategies; (b) coordination and intentionally testing a variety of stakeholder engagement strategies; (c) tool kit development; and (d) identification of fundamental motivators and logic models for stakeholder engagement to help align stakeholders and researchers.},
  journal = {Journal of Clinical and Translational Science},
  language = {en},
  number = {3}
}

@article{harrell84,
  title = {Regression Modelling Strategies for Improved Prognostic Prediction},
  author = {Harrell, Frank E. and Lee, Kerry L. and Califf, Robert M. and Pryor, David B. and Rosati, Robert A.},
  year = {1984},
  month = apr,
  volume = {3},
  pages = {143--152},
  issn = {02776715, 10970258},
  doi = {10.1002/sim.4780030207},
  journal = {Statistics in Medicine},
  language = {en},
  number = {2}
}

@article{harrell96,
  title = {Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors},
  shorttitle = {Multivariable Prognostic Models},
  author = {Harrell, F. E. and Lee, K. L. and Mark, D. B.},
  year = {1996},
  month = feb,
  volume = {15},
  pages = {361--387},
  issn = {0277-6715},
  abstract = {Multivariable regression models are powerful tools that are used frequently in studies of clinical outcomes. These models can use a mixture of categorical and continuous variables and can handle partially observed (censored) responses. However, uncritical application of modelling techniques can result in models that poorly fit the dataset at hand, or, even more likely, inaccurately predict outcomes on new subjects. One must know how to measure qualities of a model's fit in order to avoid poorly fitted or overfitted models. Measurement of predictive accuracy can be difficult for survival time data in the presence of censoring. We discuss an easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities. Both types of predictive accuracy should be unbiasedly validated using bootstrapping or cross-validation, before using predictions in a new data series. We discuss some of the hazards of poorly fitted and overfitted regression models and present one modelling strategy that avoids many of the problems discussed. The methods described are applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes. Methods are illustrated with a survival analysis in prostate cancer using Cox regression.},
  journal = {Statistics in Medicine},
  keywords = {Clinical Trials as Topic,Computer Graphics,Computer Simulation,Data Interpretation; Statistical,Discriminant Analysis,Humans,Linear Models,Male,Mathematical Computing,Models; Statistical,Multivariate Analysis,Prostatic Neoplasms,Regression Analysis,Software,Survival Analysis,Treatment Outcome},
  language = {eng},
  number = {4},
  pmid = {8668867}
}



@article{cox72,
  title = {Regression {{Models}} and {{Life}}-{{Tables}}},
  author = {Cox, DR},
  year = {1972},
  volume = {34},
  pages = {187--220},
  issn = {1369-7412},
  journal = {Journal of the Royal Statistical Society Series B-Statistical Methodology},
  language = {English},
  number = {2}
}



@article{rahman17,
  title = {Review and Evaluation of Performance Measures for Survival Prediction Models in External Validation Settings},
  author = {Rahman, M. Shafiqur and Ambler, Gareth and {Choodari-Oskooei}, Babak and Omar, Rumana Z.},
  year = {2017},
  month = dec,
  volume = {17},
  pages = {60},
  issn = {1471-2288},
  doi = {10.1186/s12874-017-0336-2},
  file = {/home/a/Zotero/storage/9WUUQUX5/Rahman et al. - 2017 - Review and evaluation of performance measures for .pdf},
  journal = {BMC Medical Research Methodology},
  language = {en},
  number = {1},
  pmcid = {PMC5395888},
  pmid = {28420338}
}

@article{royston04,
  title = {A New Measure of Prognostic Separation in Survival Data},
  author = {Royston, Patrick and Sauerbrei, Willi},
  year = {2004},
  month = mar,
  volume = {23},
  pages = {723--748},
  issn = {02776715, 10970258},
  doi = {10.1002/sim.1621},
  journal = {Statistics in Medicine},
  language = {en},
  number = {5}
}

@article{royston13,
  title = {External Validation of a {{Cox}} Prognostic Model: Principles and Methods},
  shorttitle = {External Validation of a {{Cox}} Prognostic Model},
  author = {Royston, Patrick and Altman, Douglas G},
  year = {2013},
  month = dec,
  volume = {13},
  pages = {33},
  issn = {1471-2288},
  doi = {10.1186/1471-2288-13-33},
  file = {/home/a/Zotero/storage/ZZLC7T6G/Royston and Altman - 2013 - External validation of a Cox prognostic model pri.pdf},
  journal = {BMC Medical Research Methodology},
  language = {en},
  number = {1},
  pmcid = {PMC3667097},
  pmid = {23496923}
}



@article{grambsch94,
  title = {Proportional Hazards Tests and Diagnostics Based on Weighted Residuals},
  author = {Grambsch, Patricia M. and Therneau, Terry M.},
  year = {1994},
  volume = {81},
  pages = {515--526},
  issn = {0006-3444, 1464-3510},
  doi = {10.1093/biomet/81.3.515},
  journal = {Biometrika},
  language = {en},
  number = {3}
}

@Book{therneau00,
    title = {Modeling Survival Data: Extending the {C}ox Model},
    author = {{Terry M. Therneau} and {Patricia M. Grambsch}},
    year = {2000},
    publisher = {Springer},
    address = {New York},
    isbn = {0-387-98784-3},
}

@Manual{rteam21,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2021},
    url = {https://www.R-project.org/},
}



@article{mitnitski05,
  title = {Relative {{Fitness}} and {{Frailty}} of {{Elderly Men}} and {{Women}} in {{Developed Countries}} and {{Their Relationship}} with {{Mortality}}: {{FITNESS AND FRAILTY IN RELATION TO MORTALITY}}},
  shorttitle = {Relative {{Fitness}} and {{Frailty}} of {{Elderly Men}} and {{Women}} in {{Developed Countries}} and {{Their Relationship}} with {{Mortality}}},
  author = {Mitnitski, Arnold and Song, Xiaowei and Skoog, Ingmar and Broe, Ga and Cox, Jafna L. and Grunfeld, Eva and Rockwood, Kenneth},
  year = {2005},
  month = dec,
  volume = {53},
  pages = {2184--2189},
  issn = {00028614, 15325415},
  doi = {10.1111/j.1532-5415.2005.00506.x},
  journal = {Journal of the American Geriatrics Society},
  language = {en},
  number = {12}
}





@article{etheredge07,
  title = {A Rapid-Learning Health System},
  author = {Etheredge, Lynn M.},
  year = {2007 Mar-Apr},
  journal = {Health Affairs (Project Hope)},
  volume = {26},
  number = {2},
  pages = {w107-118},
  issn = {1544-5208},
  doi = {10.1377/hlthaff.26.2.w107},
  abstract = {Private- and public-sector initiatives, using electronic health record (EHR) databases from millions of people, could rapidly advance the U.S. evidence base for clinical care. Rapid learning could fill major knowledge gaps about health care costs, the benefits and risks of drugs and procedures, geographic variations, environmental health influences, the health of special populations, and personalized medicine. Policymakers could use rapid learning to revitalize value-based competition, redesign Medicare's payments, advance Medicaid into national health care leadership, foster national collaborative research initiatives, and design a national technology assessment system.},
  language = {eng},
  pmid = {17259191},
  keywords = {Delivery of Health Care,Evidence-Based Medicine,Female,Humans,Information Systems,Learning,Male,Medicaid,Medical Records Systems; Computerized,Medicare,National Health Insurance; United States,Private Sector,Public Health Informatics,Public Sector,Regional Medical Programs,Systems Integration,Total Quality Management,United States}
}

@article{greene12,
  title = {Implementing the {{Learning Health System}}: {{From Concept}} to {{Action}}},
  shorttitle = {Implementing the {{Learning Health System}}},
  author = {Greene, Sarah M. and Reid, Robert J. and Larson, Eric B.},
  year = {2012},
  month = aug,
  journal = {Annals of Internal Medicine},
  volume = {157},
  number = {3},
  pages = {207},
  issn = {0003-4819},
  doi = {10.7326/0003-4819-157-3-201208070-00012},
  language = {en}
}