Polypharmacy Burden and Potentially Inappropriate Prescribing Among Older Adults in a Ghanaian District Referral Hospital: A Validated Synthetic Cohort Study Using AGS Beers 2023 and STOPP/START v3
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Background
Geriatric polypharmacy and potentially inappropriate prescribing (PIP) represent severe iatrogenic safety challenges in sub-Saharan Africa. However, clinical quality auditing in under-resourced settings is routinely impeded by electronic health record (EHR) scarcity and data-privacy constraints.
Objective
To generate, validate, and clinically audit a privacy-preserving synthetic cohort representing older adults in Tatale, Ghana, comparing the diagnostic yield and statistical concordance of the 2023 American Geriatrics Society (AGS) Beers and STOPP/START version 3 (v3) screening criteria.
Methods
Utilizing the Synthea framework, a synthetic cohort of N = 3, 958 geriatric patients (≥ 60 years) diagnosed with comorbid hypertension and Type 2 diabetes was generated. Demographic parameters were calibrated to the 2022 Ghana Demographic and Health Survey (GDHS; N = 5, 785). Multidimensional validation was conducted using the first Wasserstein distance (W 1 ). Local health system vulnerabilities, including an 11.2% duplicate prescribing rate and a 27.0% stockout-driven drug substitution probability, were programmatically modeled. Automated scripts screened the cohort’s medications against both criteria. Descriptive, ANOVA, and concordance (Cohen’s Kappa) analyses were performed in JASP 0.97.0.
Results
The synthetic cohort exhibited high demographic alignment with the target population (W 1 = 15.25 for age; simulated: 47.55% female; GDHS: 52.15% female). The baseline polypharmacy rate was 58.29% (n = 2, 307). Programmatic screening under the STOPP criteria identified a significantly higher potentially inappropriate medication (PIM) prevalence (76.00%; 95% CI: 74.6%–77.3%) compared to the Beers criteria (49.22%; 95% CI: 47.6%–50.8%; McNemar’s p < 0.001). Inter-criteria agreement was moderate ( κ = 0.469; 95% CI: 0.446–0.492). Male sex (χ 2 = 58.97, p < 0.001) and advanced age (ANOVA F = 47.93, p < 0.001) were associated with significantly higher medication counts.
Conclusions
Rural older adults in secondary-care settings face severe polypharmacy and PIP exposure. Programmatic screening using STOPP/START v3 exhibits superior diagnostic sensitivity compared to the Beers criteria. Validated synthetic clinical data modeling represents a scalable, privacy-preserving, and ethically responsible methodology to audit clinical prescribing safety in data-scarce health networks.
Key Highlights Box
What is already known on this topic
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Rural older adults managing chronic cardiometabolic multimorbidity are highly exposed to polypharmacy and potentially inappropriate prescribing (PIP) in sub-Saharan Africa [22, 31].
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Clinical quality auditing in low-resource environments is routinely hindered by data-privacy regulations, health workforce shortages, and a lack of unified digital health records [28, 37].
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Electronic clinical decision support systems (eCDSS) can identify prescribing errors, but passive alerts frequently suffer from low clinician implementation due to alert fatigue [26].
What this study adds
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This study represents the first computerized prescribing safety audit at a rural secondary referral hospital (Tatale District Hospital) in Northern Ghana.
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Programmatic screening of our calibrated cohort (N = 3, 958) shows that the STOPP/START v3 criteria identify a significantly higher PIP prevalence (76.00%) compared to the AGS Beers 2023 criteria (49.22%).
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Validated synthetic cohorts (calibrated with W 1 = 15.25 for age and 4.85 for BMI) offer an ethically compliant, open-science sandbox to evaluate clinical quality in data-scarce medical networks.
