Physician Factors Associated with Polypharmacy and Potentially Inappropriate Medication Use

Article Figures & Data

Table 1.

Characteristics of Patients (n = 932) and Visits (n = 2,103) Seen by 61 Participating Physicians

Data are number (%) of patients or visits.
↵* “Other” includes Asian and others.
↵† Potentially inappropriate medications (PIMs) were defined based on the table 2 of 2015 American Geriatrics Society Beers Criteria for Potentially Inappropriate Medication Use in Older Adults.⁶

Table 2.

Physician Survey Responses (n = 61)

Physician characteristics
Age (years), mean (SD)	36.1 (10.6)
Female sex, n (%)	30 (49.9)
Years since graduation, mean (SD)	9.7 (10.1)
Position, n (%)
Resident	38 (62.3)
Fellow/Faculty	23 (37.7)
Patient panel characteristics^* (%), mean (SD)
Patients ≥75 years old	34.1 (17.6)
Minority patients (black and others)	46.0 (24.7)
Item responses
Perceived importance/confidence for deprescribing, mean (SD) (1 = not at all, 5 = very much)
How important is it for you to deprescribe for patients 65 years or older in outpatient settings?	4.4 (0.7)
How confident are you in deprescribing for patients 65 years or older in outpatient settings?	3.7 (1.0)
Importance of 9 triggers for deprescribing,^{^†} mean (SD) (1 = not important, 5 = very important)
Symptoms possibly related to medication	4.8 (0.5)
Cognitive impairment	4.6 (0.7)
Limited life expectancy	4.6 (0.7)
Wishes of patient/family	4.5 (0.8)
Functional dependency	4.4 (0.7)
Number of medications	4.4 (0.8)
Older age	4.2 (0.9)
Budgetary considerations	4.2 (0.9)
Number of chronic conditions	4.1 (0.9)
Importance of 6 barriers for deprescribing,^{^‡} mean (SD) (1 = not important, 5 = very important)
Patients belief that drugs might help	3.6 (0.9)
Lack of time	3.5 (1.1)
Medications started by other doctor	3.5 (1.0)
Lack of benefit/risk information about deprescribing	2.9 (1.2)
Lack of experience	2.6 (1.4)
Patients belief that you are giving up on them	2.6 (1.2)

↵* Data obtained from health record review.
↵† “How important are the following factors for you to consider deprescribing?”
↵‡ “To what extent do the following factors make you less likely to deprescribe?”

Table 3.

Multivariable Regression: Factors Associated with Physicians' Numbers of Prescriptions and Potentially Inappropriate Medication Orders

Variables	Prescriptions	PIM Orders
Lack of benefit/risk information about deprescribing^*	−0.40 (0.16)^{^†}	−0.06 (0.03)^{^†}
Number of medications^*	−0.67 (0.24)^{^†}	−0.07 (0.04)
Proportion of minority patients	−3.72 (0.81)^{^†}	−0.34 (0.14)^{^†}
Proportion of patients aged ≥75	−2.92 (1.13)^{^†}	−0.45 (0.20)^{^†}
Use of the Beers List^{^‡}		−0.17 (0.08)
Intercept	16.31 (1.32)^{^†}	1.40 (0.24)^{^†}
Adjusted R² (AIC)	0.3939 (228)	0.2062 (12.4)

Data are β (standard error). All variables included in the fitted models are reported in this table.
↵* The importance of triggers/barriers were assessed using 5-point Likert scales ranging from 1(Not important) to 5(very important).
↵† P < .05.
↵‡ Reference group includes those physicians who did not use the Beers List.
AIC, Akaike information criterion; PIM, potentially inappropriate medication.