AI Article Synopsis

  • The study aimed to see how comorbidities and high-risk medications influence how often older patients visit their family doctors.
  • Researchers reviewed charts of patients aged 65 and older to identify the top and bottom 5% of frequent visitors, resulting in a sample of 265 patients.
  • Key findings showed that being female, over 85 years old, and taking more medications were significant predictors of frequent visits, while traditional health assessment tools did not effectively predict visit frequency.

Article Abstract

Objective: To determine if comorbidities and high-risk medications affect the frequency of family physician visits among older patients.

Design: Retrospective chart review.

Setting: Academic family health team at Sunnybrook Health Sciences Centre in Toronto, Ont.

Participants: Among patients aged 65 years and older who were registered patients of the family health team between July 1, 2013, and June 30, 2014, the 5% who visited their family physicians most frequently and the 5% who visited their family physicians least frequently were selected for the study (N = 265).

Main Outcome Measures: Predictors of frequent visits to family physicians.

Results: The significant predictors of being a high-frequency user were female sex (odds ratio [OR] = 2.20, P = .03), age older than 85 years (OR = 5.35, P = .001), and higher total number of medications (OR = 1.49, P < .001). Age-adjusted Charlson comorbidity index score, number of Beers criteria medications, and Anticholinergic Risk Scale score were not significant predictors (P > .05).

Conclusion: Female sex, age older than 85, and higher total number of medications were independent significant predictors of higher frequency of family physician visits among older patients. Validated tools, such as the Charlson comorbidity index, Beers criteria, and Anticholinergic Risk Scale, did not independently predict the frequency of visits, indicating that predicting frequency of visits is likely complex.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5257221PMC

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