Proceedings of Singapore Healthcare (Jun 2023)

Factors associated with potentially inappropriate prescribing among older persons in primary care settings: Systematic review

  • Cia Sin Lee,
  • Ngiap Chuan Tan,
  • Kuan Liang Shawn Goh,
  • Zi Ying Chang,
  • Tau Ming Liew

DOI
https://doi.org/10.1177/20101058231181478
Journal volume & issue
Vol. 32

Abstract

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Background Potentially inappropriate prescribing (PIP) is common in primary care and is associated with adverse outcomes. Knowledge of the risk factors of PIP can be critical in designing PIP interventions, especially in guiding our understanding on how PIP occurs in primary care. Objective This systematic review examined factors associated with PIP, specific to primary care. Methods We searched PubMed, Embase, CINAHL, Web of Science, Scopus and PsycINFO for studies related to ‘older persons’, ‘primary care’ and ‘inappropriate prescribing’. Two reviewers conducted study selection, data extraction and quality appraisal. Factors associated with PIP were narratively synthesized. Results Of the 1017 articles identified, we included 25 articles and a total of 2,893,925 participants, with average age of 70.4–84.0 years. Risk factors of PIP could be classified into patient, physician and system factors. Patient factors were related to patient demographics (advanced age, lower education level and lower socioeconomic status), medical comorbidities (polypharmacy and multimorbidity) and lifestyle factors (unhealthy habits and use of over-the-counter medications). Physician and system factors included older, male, solo general practitioner (GP), higher number of visits of pharmaceutical sales representatives to GP, centrally located GP practice, and smaller number of older patients following up with GP, and medication source from public health system. Conclusions The findings provide contextual information to guide our understanding of PIP in primary care. Factors identified in this review can inform the design of complex interventions for PIP, as well as be used to develop risk prediction tools to identify high-risk groups who may require further interventions related to PIP.