Potentially Inappropriate Medication Prescribing by Nurse Practitioners and Physicians

Lin-Na Chou MS; Yong-Fang Kuo PhD; Mukaila A. Raji MD; James S. Goodwin MD

Disclosures

J Am Geriatr Soc. 2021;69(7):1916-1924. 

In This Article

Results

There were 2,502,374 outpatient visits by 615,395 beneficiaries included in the analyses. Table 1 summarizes the distribution of visit characteristics and the percent of visits associated with a prescription for an initial or refilled PIM. The distribution of characteristics for beneficiaries cared for by a physician, NP, or both, is presented in Table S2. In total, 6.4% of visits were to NPs and 93.6% to physicians; 24.1 per 1000 visits were associated with a prescription for a PIM: 9.0 per 1000 visits for an initial PIM prescription and 15.1 per 1000 visits for a refill of an existing PIM prescription.

Table 2 presents the rate of PIM prescriptions per 1000 visits by type of provider and patient characteristics, and the adjusted ORs after a logistic regression analysis controlling for other relevant characteristics. In both the unadjusted rates and the adjusted ORs, visits to an NP were significantly less likely to result in an initial (OR = 0.74, 95% confidence interval [CI] = 0.70–0.79) or refill (OR = 0.54, 95% CI = 0.51–0.57) PIM prescription. Older age, male sex, black race, and metropolitan residence were also associated with lower odds of receiving an initial PIM or PIM refill. Sensitivity analyses revealed similar results in multilevel logistic regression with visits nested within providers, although the association of provider type was weaker in the same direction among those visits from enrollees with the same type of provider (Table S3). For example, the OR for receiving an initial PIM prescription from an NP (compared with a physician) was 0.88 (95% CI = 0.80–0.97) for enrollees with same type of provider; the OR was 0.74 (95% CI = 0.64–0.85) in a multilevel logistic regression model.

In the analyses in Table 2 for the odds of an initial PIM, there were significant interactions between provider type (NP vs physician) and both race/ethnicity and place of residence. For a PIM refill, there were interactions of provider type with age, race/ethnicity, and number of comorbidities. To further describe the interactions, Table 3 presents analyses stratified by characteristics. The association of lower odds of receiving a prescription for an initial PIM from an NP was substantially stronger among black enrollees than white enrollees (OR = 0.44, 95% CI = 0.30–0.65 for black enrollees and OR = 0.73, 95% CI = 0.68–0.78 for white enrollees). The association of lower odds of receiving an initial PIM after an NP visit became weaker in nonmetropolitan areas than metropolitan areas. The association of an NP provider with lower odds of receiving a PIM refill was more pronounced in older patients and in those with more comorbidities.

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