Polypharmacy NMA: Pharmacist #1 for Falls, Deprescribing #1 for PIMs — 8 RCTs, 5 Nodes

[howard6204]

Polypharmacy Interventions in Older Adults — Network Meta-Analysis

5 strategies compared across 3 outcomes: Pharmacist-led review ranked #1 for falls; Deprescribing ranked #1 for PIMs reduction.

Project path: projects/polypharmacy-nma/
Pipeline stages: 01 Protocol → 02 Search → 06 Analysis → 07 Manuscript

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Background

Polypharmacy (>=5 medications) affects over 40% of older adults and is associated with falls, hospitalization, and potentially inappropriate medication (PIM) use. Multiple intervention strategies exist — pharmacist-led review, CDSS, multidisciplinary team (MDT) care, physician deprescribing, and usual care — but no head-to-head trials have compared them simultaneously. This NMA fills that gap using real published RCT data from PubMed.

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Included Studies (8 real RCTs, 2011-2026)

Study	PMID	Node	Region	Setting
Lapane 2011	21649623	Pharmacist	N. American	Institutionalized
Che 2024	39078632	MDT	Asian	Institutionalized
McCarthy 2022 (OPERAM)	34986166	Deprescribing	European	Community
Niquille 2021 (QC-DeMo)	33933030	MDT	European	Institutionalized
Kua 2020	32423694	MDT	Asian	Institutionalized
Hellemans 2026 (ASPIRE)	41619153	Pharmacist	European	Institutionalized
Cateau 2021 (IDeI)	34798826	Pharmacist	European	Institutionalized
Streit 2023 (OPTICA)	37225248	CDSS	European	Community

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Treatment Networks

Falls network (k=4 trials): Pharmacist, MDT, Deprescribing vs. Usual Care. I2=0%.

PIMs network (k=6 trials): all 5 nodes including CDSS. I2=81%.

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Forest Plots

Falls NMA — low heterogeneity (I2=0%), consistent directional effect favoring active interventions.

PIMs NMA — high heterogeneity (I2=81%), subgroup analysis triggered by setting.

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P-score Rankings

Comparative P-score rankings across all three outcomes.

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Key Findings

Outcome	I2	#1 (P-score)	#2 (P-score)	Notes
Falls	0%	Pharmacist (0.79)	Deprescribing (0.64)	Robust; no subgroup needed
Hospitalization	97.3%	MDT (0.76)	Pharmacist (0.45)	Dominated by Kua 2020 (Singapore NH, HR=0.16); interpret with caution
PIMs (all)	81%	Deprescribing (0.87)	Pharmacist (0.76)	CDSS last (0.22); no significant effect
PIMs (European)	88.5%	Deprescribing (0.85)	Pharmacist (0.73)	Consistent with overall
PIMs (Asian)	N/A	Insufficient data (k=1)	—	Kua 2020 only

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Clinical Implications

• Fall prevention: Pharmacist-led medication review is the top-ranked strategy for fall risk reduction in older adults with polypharmacy, especially in institutionalized settings.
• PIMs reduction: Both deprescribing (STOPP/START-guided) and pharmacist-led review are highly effective; choose based on local resources.
• Hospitalization: Extreme heterogeneity (I2=97.3%) precludes reliable conclusions. MDT care shows dramatic effect in Singapore NH model (Kua 2020), but generalizability is uncertain.
• CDSS: The OPTICA trial showed no significant PIMs reduction; passive technology-only approaches appear insufficient without reinforcing prescriber behavior change.

Methodology

• Analysis type: Frequentist Network Meta-Analysis (NMA)
• Software: R 4.3.0 — netmeta package (v2.x)
• Ranking metric: P-scores (frequentist SUCRA equivalent); higher = better
• Heterogeneity rule: I2 > 50% triggers auto subgroup (setting for falls/hosp; region for PIMs)
• Outcome measures: log-HR / log-IRR / log-OR converted to contrast format with SE from 95% CI
• Bayesian NMA: Planned extension (requires JAGS for gemtc/true SUCRA)

Pipeline

Stages completed:

• 01 Protocol (PICO, eligibility criteria)
• 02 Search (PubMed real retrieval, 8 RCTs with extractable data)
• 06 Analysis (22 figures, 9 tables, 15 R scripts)
• 07 Manuscript (full draft ~4,200 words + supplementary + submission checklist)

Total committed: 90 files

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Generated with meta-pipe — AI-assisted meta-analysis pipeline

#NMA #Polypharmacy #GeriatricPharmacy #Deprescribing #Falls #PIMs