A Pharmaceutical Care Model for Medication Safety in Primary Care

Thesis Abstract

Medication safety remains a persistent challenge in primary care, where polypharmacy, fragmented care, and limited patient engagement contribute to adverse drug events, prescribing cascades, and medication-related problems that compromise patient outcomes. This study develops and empirically tests a Pharmaceutical Care Model (PCM) designed to enhance medication safety in primary care settings by systematizing pharmacist-clinician collaboration, patient-centered monitoring, and decision-support integration. The aim is to create a validated framework that improves detection, prevention, and resolution of medication-related risks across diverse primary care teams. Specific objectives include (1) delineating core components of an evidence-based PCM grounded in patient safety and pharmaceutical care theories, (2) evaluating the feasibility and acceptability of PCM implementation in primary care clinics, (3) assessing the impact of PCM on medication safety indicators such as potentially inappropriate prescriptions (PIPs), adverse drug events (ADEs), and drug–drug interaction (DDI) incidence, and (4) examining mediating factors (team communication, information sharing, and patient activation) that influence safety outcomes. A sequential mixed-methods design is employed. The qualitative phase (n=40 semi-structured interviews and 20 focus groups with general practitioners, pharmacists, and nurses across 10 primary care clinics) explores contextual determinants and informs PCM refinement using thematic analysis anchored in the Normalization Process Theory (NPT) and the Pharmaceutical Care Framework. The quantitative phase uses a quasi-experimental pre-post design with 2,000 patient records from intervention clinics and 2,000 matched controls over 12 months, analyzing changes in PIP rates (based on STOPP/START criteria), ADE incidence, and incidence of DDIs through medication reconciliation data. Data collection instruments include a validated PCM implementation checklist, standardized patient safety audit tools, and a structured pharmacist-physician collaborative survey. Validity and reliability are addressed through pilot testing, triangulation of data sources, intraclass correlation coefficients for inter-rater reliability in chart reviews (target ICC ? 0.75), and Cronbach’s alpha for survey scales (? ? 0.80). Data analysis comprises descriptive statistics, multilevel logistic regression to assess treatment effects on binary safety outcomes, Poisson or negative binomial regression for count data, and thematic analysis for qualitative data, with integration via mixed-methods joint displays. Key expected findings indicate that PCM adoption will be associated with statistically significant reductions in PIP prescriptions (relative risk reduction >15%), lower ADE reporting rates, and a measurable decrease in clinically relevant DDIs within 12 months post-implementation. The study anticipates identifying critical mediators—enhanced interprofessional communication, standardized medication reviews, and patient activation through education and shared decision-making—that explain a substantial portion of the observed safety improvements. Sensitivity analyses will assess potential confounding due to clinic size, baseline safety performance, and patient comorbidity burden. The study contributes to knowledge by operationalizing a theory-informed PCM tailored to primary care and providing empirical evidence on its effectiveness, feasibility, and sustainability in real-world settings. It advances the Pharmaceutical Care literature by integrating Normalization Process Theory with a pragmatic, scalable model that aligns pharmacist expertise with primary care workflows, decision-support interfaces, and patient engagement strategies. Findings will inform policy and program design for medication safety enhancement, including training curricula for pharmacists and clinicians, documentation standards for collaborative care plans, and implementation guides for electronic health record (EHR) integration of PCM components. Conclusions will articulate that a well-structured Pharmaceutical Care Model can meaningfully improve medication safety indicators in primary care when embedded within routine practice, supported by organizational buy-in, continuous feedback loops, and patient-centered monitoring. Recommendations include scaling the PCM across diverse primary care environments, integrating PCM metrics into quality improvement dashboards, investing in interoperable EHR tools for shared care planning, and developing targeted professional development modules to sustain interprofessional collaboration and patient activation beyond the study period.