Appendix Table 3:

Association between Practice Location Rurality and Low Value Care Spending of Attributed Medicare Patients Across Specialty

Characteristic	Panel A: OLS Estimates		Panel B: Logit Odds Ratio Estimates
Characteristic	Coefficient	SE	OR	SE
Physician Characteristics
Allopath	−1.617^‡	0.4605	0.652^†	0.0875
Female	−0.566	0.4528	1.014	0.1500
Non-US Medical Graduate	−0.216	0.4158	0.985	0.1138
Patient Size
<50	−4.131^‡	0.5712	0.322^‡	0.0525
50 to 149	−2.779^‡	0.4675	0.416^‡	0.0560
150 to 299	−1.811^‡	0.4171	0.54^‡	0.0701
300+
Specialty
Internal Medicine
Family Medicine	−1.182^†	0.3499	0.68^‡	0.0687
Other Specialty	−0.829	0.7742	0.84	0.2193
Graduation Year
Pre-1980
1980 to 1989	−0.166	0.3834	1.090	0.1236
1990 to 2000	−0.741	0.4086	0.972	0.1122
Post-2000	−1.582^*	0.6339	0.717	0.1578
Practice Region
Northeast
Midwest	−2.752^‡	0.4570	0.408^‡	0.0606
South	0.339	0.4870	1.062	0.1369
West	0.03	0.5730	0.996	0.1529
Rural	−2.152^‡	0.5269	0.43^†	0.1104
RuralXSpecialty
RuralXInternal Medicine
RuralXFamily Medicine	0.764	0.5822	1.421	0.4270
RuralXOther Specialty	−0.831	1.2300	0.922	0.5493
Patient Characteristics
Age (years)
65 to 69
70 to 74	−0.037	0.0396	0.995	0.0105
75 to 79	−0.064	0.0345	0.989	0.0102
80 to 84	−0.131^‡	0.0338	0.983	0.0102
85+	−0.336^‡	0.0248	0.923^‡	0.0073
Female	−0.042^†	0.0154	0.984^†	0.0049
Race/Ethnicity
White
Black	−0.068^‡	0.0116	0.985^‡	0.0038
Other	−0.038	0.0202	0.991	0.0050
ElixHauser Comorbidity Index
0
1 to 2	0.050^*	0.0236	1.015	0.0085
3 to 5	0.214^‡	0.0307	1.058^‡	0.0074
6+	0.307^‡	0.0877	1.049^‡	0.0107
Practice Location Characteristics
<12 years schooling	−0.096^†	0.0336	0.978^*	0.0105
Black	0.051^‡	0.0118	1.015^‡	0.0037
Hispanic	0.103^‡	0.0159	1.028^‡	0.0043
< 200% FPL	−0.077^‡	0.0152	0.979^‡	0.0050
Number of Observations	6,905

OR, odds ratio; FLP, federal poverty line; OLS, ordinary least squares. Note: The dependent variable for Panel A was per-patient low value care (LVC) Medicare spending in dollar amounts, while the ORs in Panel B were calculated from logit regression results, where the dependent variable was equal to 1 if the primary care physician's (PCP) per-patient LVC Medicare spending was in the top quintile. RuralXSpecialty indicated a set of interaction terms between the rurality of PCP's practice location and PCP's specialty type. Practice was considered to be in a rural area if it was located in any of the six non-metropolitan county categories in the Rural Urban Continuum Code that divided all US counties into three metropolitan and six nonmetropolitan county categories. PCPs were categorized into three specialty types: those that practice internal medicine, family medicine, and other PCP specialties. Both models were estimated using sample weights that reflect the oversampling of physicians in smaller states.
↵* P < .05.
↵† P < .01.
↵‡ P < .001.