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. Author manuscript; available in PMC: 2020 Aug 24.
Published in final edited form as: Am Econ J Econ Policy. 2019 Feb;11(1):192–221. doi: 10.1257/pol.20150421

Table 1—

Primary Variables and Sample Distribution

Variable Mean Individual standard deviation Area average standard deviation p-value
Panel A. Spending and utilization
Two-year end-of-life spending $55,194 $10,634
Average EOL spending $14,409 $3,983
Hip fracture patient spending $52,282 $4,882
Panel B. Patient variables (N = 1,516)
Have unneeded tests 73% 45% 11% <0.01
See unneeded cardiologist 56% 50% 14% <0.01
Aggressive patient preferences ratio 8.0% 27% 7.0% <0.01
Comfort patient preferences ratio 48% 50% 13% <0.01
Panel C. Primary care physician variables (N = 570 in restricted sample)
Cowboy 23% 42% 27% <0.01
Comforter 44% 50% 28% <0.01
Follow-up low 8.8% 28% 19% <0.01
Follow-up high 4.4% 20% 6.4% <0.01
Panel D. Cardiologist variables (N = 415 in restricted sample)
Cowboy 26% 44% 20% <0.01
Comforter 27% 45% 23% <0.01
Follow-up low 1.4% 12% 6.3%
Follow-up high 21% 41% 22% <0.01
Panel E. All physicians (N = 985 in restricted sample)
Cowboy 24% 43% 15% <0.01
Comforter 37% 48% 18% <0.01
Follow-up low 5.7% 23% 8.6% <0.01
Follow-up high 12% 32% 12% <0.01
Panel F. Organizational and financial variables
Reimbursement
 Fraction Medicare patients 42% 22%
 Fraction Medicaid patients 10% 13%
 Fraction capitated patients 15% 25%
Organizational factors
 Solo or two-person practice 29% 46%
 Single/multi speciality group practice 57% 50%
 Group/staff HMO or hospital-based practice 13% 33%
General controls
 Physician age 53 10
 Male 81% 39%
 Board certified 88% 33%
 Weekly patient days 2.9 1.5
 Cardiologists per 100k (N = 74, HRR-level) 6.8 1.9
Responsiveness factors
 Responds to referrer expectations (cardiologists only) 31% 46%
 Responds to colleague expectations 38% 49%
 Responds to patient expectations 54% 50%
 Responds to malpractice concerns 39% 49%
 Responds to practice financial incentives 9% 29%

Notes: The table shows means for the (restricted) primary analysis sample. The p-value in the last column is for the null hypothesis of no excess variance across areas and is taken from a bootstrap of patient or physician responses across areas. For each of 1,000 simulations, we draw patients or providers randomly (with replacement) and calculate the simulated area average and the standard deviation of that area average. The empirical distribution of the standard deviation of the area average is used to form the p-value for the actual area average.