Potentially Inappropriate Medication Prescribing in U.S. Older Adults with Selected Chronic Conditions

Consult Pharm. 2017 Sep 1;32(9):525-534. doi: 10.4140/TCP.n.2017.525.

Abstract

Objective: Developing one or more chronic diseases increases with age. Appropriate treatment for chronic conditions often requires multiple medications. The purpose of this study was to examine potentially inappropriate prescriptions in patients 65 years of age or older, seen in a primary care office, with at least one of three chronic conditions (diabetes, arthritis, depression), who were prescribed at least two medications, one of which was inappropriate for the patient's condition.

Design: 2012 National Ambulatory Medical Care Survey data were examined using multivariate techniques.

Setting: U.S. primary care office visits.

Main outcome measures: Drug appropriateness was ascertained from practice guidelines. Potentially inappropriate medications were ascertained from the 2012 Beers criteria. The 2012 Beers criteria were used since the data analyzed were from 2012.

Results: Logistic regression analysis yielded that older adults with diabetes had greater odds of having a potentially inappropriate prescription if they saw a provider in a rural setting, were non-white, had health insurance, and had two or more office visits in the last 12 months.

Conclusion: There is a need to address prescribing of potentially inappropriate medications to older, non-white patients who have diabetes. Living in rural areas is also an important factor in prescribing patterns for older adults with diabetes. Our findings suggest that interventions are warranted to address this health problem. One solution is the establishment of interprofessional and multidisciplinary teams of health care providers constituted of prescribers and nonprescribers to comprehensively evaluate prescribing practices.

MeSH terms

  • Aged
  • Arthritis / drug therapy*
  • Chronic Disease
  • Depression / drug therapy*
  • Diabetes Mellitus / drug therapy*
  • Humans
  • Inappropriate Prescribing*
  • Logistic Models
  • Patient Care Team
  • United States