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Use Case Intake for Extended Oncology CDM #171

sratwani opened this issue Oct 18, 2019 · 2 comments

Use Case Intake for Extended Oncology CDM #171

sratwani opened this issue Oct 18, 2019 · 2 comments


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@sratwani sratwani commented Oct 18, 2019

This issue has been opened to gather use cases from partners interested in running a research study using the extended Oncology CDM.
Please include the following information:

  1. Name of your organization,
  2. Your contact information
  3. Objectives
  4. Study Design
  5. Data Source
  6. Study Population
  7. Outcomes of interest
  8. Exclusion Criteria
@sratwani sratwani added the Use Cases label Oct 18, 2019
@sratwani sratwani self-assigned this Oct 18, 2019
@sratwani sratwani added this to In progress in Oncology WG Oct 20, 2019

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@ParkYouJin ParkYouJin commented Nov 20, 2019

A Rigorous Global Observation System for burden of diseases (ARGOS)

  1. Organization : Ajou University
  2. Name : Youjin Park, Email :
  3. Objectives :
  • To assess disease burden and economic burden of cancer
    • To monitor cancer disease burden over OHDSI community by assessing
      • Temporal trend in incidence
      • Incidence according to age, gender, and birth year
      • Temporal trend in survival
      • Disability-Adjusted Life Loss (DALY)
    • To measure cost-effectiveness of cancer registry
      • Quality-Adjusted Life Year (QALY)
      • Incremental Cost-effectiveness Ratio (ICER)
  1. Study design
  • Assess burden of disease
    • We already presented our pilot study in 2019 OHDSI Europe symposium about disease burden. Click Here
    • Also, in OHDSI USA, we posted another poster. click Here
  • Assess economic burden
    • Using extended Oncology CDM, I will compare cost-effectiveness among treatment protocols of cancer
    • Calculate increased QALY for each treatment protocol and calculate ICER to compare cost-effectiveness
  1. Data Source
  • National Health Insurance Service-National Sample Cohort (NHIS-NSC) from 2002-2013 in Korea (for POC study, we posted the result using this data source in OHDSI Europe)
  • Korean cancer patients' data from National Insurance data fo HIRA (we posted the result using this data source in OHDSI USA)
  1. Study population
  • All population
  1. outcomes of interest
  • Cancer incidence (colorectal, lung, stomach, liver, breast, tyroid)
  • Cancer survival
  • Yearly expenses
  • Monthly expenses
  • DALY
  • QALY
  • ICER
  1. Exclusion criteria
  • persons who had observation period less than 2 years

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@odikia odikia commented Dec 5, 2019

Differences in the relative rate of pain management prescriptions in the context of late stage cancer among racial and ethnic groups.

  1. Organization: Emory University Winship Cancer Institute
  2. Contact Info:
    a. Daniel Smith:
    b. Renjian Jiang:
  3. Objectives: To determine if a patient’s race and ethnicity influences the prescription of medications for the management of pain in the context of late stage cancer.
  4. Study Design: Observational study utilizing historical records located within Emory’s local OMOP CDM instance.
  5. Data Source: Primary data sources will include data from Emory’s Cancer Data Mart housed on an Oracle Server housing data from a Cerner EMR application (i.e., PowerChart). EMR data will be the primary source data for relevant patient demographics (age, gender, race, ethnicity) as well as drug prescriptions. Data will additionally be ingested from a METRIQ NAACCR database, providing for the source of cancer staging, and specific histology.
  6. Study Population: Patient data will be made available from Winship Cancer Institute exclusively, and Data will be restricted from 2015 to present per the data currently available within Emory’s Cancer Data Mart. The patient population will include all late stage cancer patients within this time period.
  7. Outcomes of Interest: The rate of prescriptions for pain management will be broken down by cancer type, stage, and examined per racial and ethnic background. Gender and age will serve as additional categories of interest in assessing the relative rate of pain management prescriptions.
  8. Exclusion Criteria: Patient’s with a history of documented opioid abuse or dependence will not be included in the study.
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