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Accessible Unlicensed Requires Authentication Published by De Gruyter March 4, 2016

Evidence of Inefficiencies in Practice Patterns: Regional Variation in Medicare Medical and Drug Spending

Melinda Buntin and Tamara Hayford

Abstract

Several studies have explored the causes and magnitude of geographic variation in Medicare spending and service use, but most of these studies have not taken into account that pharmaceuticals may substitute for medical service use. We address this issue using Medicare medical and pharmaceutical administrative claims data to explore the correlation between medical and pharmaceutical spending and utilization; we also examine medical and pharmaceutical use for subsets of the Medicare population with certain chronic conditions often treated with drugs. Beneficiary-level regressions with controls for health status and demographics were used to construct standardized medical spending and pharmaceutical spending and utilization measures for each region and patient cohort. Areas with higher medical spending tend to have higher pharmaceutical spending in general. However, areas with higher medical spending also tend to have lower pharmaceutical spending for conditions for which prescription drugs may substitute for additional medical care. Both of these patterns are consistent with less efficient medical practices in higher-spending areas. Likewise, more expensive drugs and more broad-spectrum antibiotics, which are often considered discretionary and overused, are more likely to be prescribed in higher-spending areas. Our results suggest that care may be provided more efficiently in some regions than in others. However, additional research is needed to investigate relationships between spending and health care outcomes, and what types of policies may create incentives for higher-spending regions to reduce spending without a loss in quality.

JEL Classification: I1; I180

Acknowledgments

We are grateful to Katherine Baicker, Jessica Banthin, Linda Bilheimer, Julie Bynum, and John Graves for many helpful comments. We are also grateful to Alexia Diorio and Bobby Goodrich for excellent research assistance

Appendix

Table 1:

Panel A; Underlying Regression Results: All Elderly Cohort.

All elderlyOverall medical spendOverall drug spendOverall drug useBrand shareAntibiotic spend6-months mortality1-year mortality2-years mortality
Age 70–75–1005.60–127.190.230.00–2.160.000.000.00
(<0.0001)(<0.0001)(0.0088)(<0.0001)(<0.0001)(0.139)(0.275)(0.3845)
Age 75–80–1848.20–138.531.42–0.01–2.720.000.010.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 80–85–2255.01–112.463.39–0.02–2.300.010.030.06
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 85–90–2733.32–89.165.54–0.03–1.080.040.080.15
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0076)(<0.0001)(<0.0001)(<0.0001)
Age 90–95–3360.25–104.097.19–0.054.980.090.150.26
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 95+–4011.28–280.356.25–0.0714.570.150.240.41
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Male–506.89276.661.840.005.410.010.010.03
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Black1076.77–519.03–7.50–0.02–20.10–0.01–0.01–0.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Hispanic–786.76–709.48–10.19–0.01–11.56–0.02–0.03–0.05
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Asian–3602.48–342.02–7.530.03–4.22–0.02–0.04–0.06
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Enhanced Part D Plan291.30–143.18–3.08–0.010.120.000.000.00
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.7069)(0.4985)(0.1813)(0.2122)
Coverage in donut hole1161.201394.8019.730.018.800.000.010.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Dually eligible2023.321007.0812.12–0.0116.650.020.030.05
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Low-income subsidy program–732.75683.418.690.003.690.000.010.01
(<0.0001)(<0.0001)(<0.0001)(0.1617)(<0.0001)(0.001)(<0.0001)(<0.0001)
Log risk score (medical)11128.000.040.060.10
(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Log risk score (drug)2825.4847.76–0.0939.75
(<0.0001)(<0.0001)(<0.0001)(<0.0001)

Table 1:

Panel B; Underlying Regression Results: No-HCC Cohort.

No HCCOverall medical spendOverall drug spendOverall drug useBrand shareAntibiotic spend6-months mortality1-year mortality2-years mortality
Age 70–75–390.66–144.77–0.990.00–3.920.000.000.00
(<0.0001)(<0.0001)(<0.0001)(0.6083)(<0.0001)(0.2433)(0.0257)(<0.0001)
Age 75–80–376.63–59.110.67–0.01–4.250.010.010.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 80–8522.5376.553.24–0.01–4.300.020.030.06
(0.7915)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 85–90667.71257.076.36–0.03–3.510.040.070.13
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 90–951569.45377.849.18–0.042.110.080.140.26
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0082)(<0.0001)(<0.0001)(<0.0001)
Age 95+1815.50325.2210.17–0.0611.550.140.240.41
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Male230.33162.020.940.001.830.010.010.02
(<0.0001)(<0.0001)(<0.0001)(0.0522)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Black–201.99–397.27–4.41–0.03–13.820.000.00–0.01
(0.0423)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0213)(0.0037)(0.0026)
Hispanic–1234.08–512.11–7.38–0.03–6.73–0.01–0.02–0.04
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Asian–2710.04–139.40–4.370.02–1.94–0.01–0.02–0.04
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0191)(<0.0001)(<0.0001)(<0.0001)
Enhanced Part D plan21.07–53.21–1.52–0.010.490.000.000.00
(0.714)(<0.0001)(<0.0001)(<0.0001)(0.1402)(0.9015)(0.4493)(0.5735)
Coverage in donut hole1522.941257.5117.770.018.660.000.010.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Dually eligible1463.74517.116.16–0.037.540.020.030.04
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Low-income subsidy program–156.25321.915.09–0.021.640.000.010.02
(0.1417)(<0.0001)(<0.0001)(<0.0001)(0.0074)(<0.0001)(<0.0001)(<0.0001)
Log risk score (medical)3803.520.000.000.01
(<0.0001)(0.1962)(0.0043)(<0.0001)
Log risk score (drug)1280.1127.31–0.0912.85
(<0.0001)(<0.0001)(<0.0001)(<0.0001)

Table 1:

Panel C; Underlying Regression Results: CHF Cohort.

CHFOverall medical spendOverall drug spendOverall drug useBrand shareAntibiotic spendDisease-specific drug spendDisease-specific drug use6-months mortality1-year mortality2-years mortality
Age 70–75–1085.90–223.50–0.280.00–1.768.640.510.010.010.02
(<0.0001)(<0.0001)(0.4271)(0.8523)(0.1916)(0.029)(<0.0001)(0.0005)(<0.0001)(<0.0001)
Age 75–80–2399.71–411.19–0.600.00–4.2212.220.850.020.040.06
(<0.0001)(<0.0001)(0.0796)(0.017)(0.0014)(0.0016)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 80–85–3028.12–593.29–0.70–0.01–4.38–0.280.860.040.070.12
(<0.0001)(<0.0001)(0.0421)(<0.0001)(0.0009)(0.9418)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 85–90–4712.50–672.950.02–0.02–3.46–2.911.550.070.130.22
(<0.0001)(<0.0001)(0.9642)(<0.0001)(0.0144)(0.483)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 90–95–5570.42–740.54–0.02–0.033.20–26.421.280.130.210.34
(<0.0001)(<0.0001)(0.9647)(<0.0001)(0.0644)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 95+–7615.14–915.63–3.62–0.0414.75–67.84–0.260.180.290.45
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.3025)(<0.0001)(<0.0001)(<0.0001)
Male–1262.7688.81–1.340.017.38–43.01–0.750.020.030.04
(<0.0001)(0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Black4075.90–605.10–12.64–0.01–25.1224.85–0.37–0.01–0.02–0.03
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0046)(<0.0001)(<0.0001)(<0.0001)
Hispanic887.20–743.59–11.780.00–14.25–38.39–1.96–0.03–0.03–0.05
(0.0775)(<0.0001)(<0.0001)(0.1716)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Asian–4877.4261.34–7.880.050.0454.98–1.92–0.03–0.05–0.07
(<0.0001)(0.4464)(<0.0001)(<0.0001)(0.9881)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Enhanced Part D plan741.44–298.23–5.96–0.01–1.67–49.40–1.600.000.000.00
(0.0055)(<0.0001)(<0.0001)(<0.0001)(0.2055)(<0.0001)(<0.0001)(0.7915)(0.8823)(0.3792)
Coverage in donut hole1187.201394.2421.550.0210.17129.884.450.010.020.03
(0.0002)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0012)(<0.0001)(<0.0001)
Dually eligible3828.931139.3615.72–0.0124.94–22.10–0.350.020.040.06
(<0.0001)(<0.0001)(<0.0001)(0.0003)(<0.0001)(<0.0001)(0.0404)(<0.0001)(<0.0001)(<0.0001)
Low-income subsidy program–806.51792.569.490.013.5752.851.940.010.010.01
(0.0244)(<0.0001)(<0.0001)(<0.0001)(0.0435)(<0.0001)(<0.0001)(0.0554)(0.0309)(0.053)
Log risk score (medical)21917.000.080.120.18
(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Log risk score (drug)4456.2659.890.0284.7852.811.96
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)

Table 1:

Panel D; Underlying Regression Results: Diabetes Cohort.

DiabetesOverall medical spendOverall drug spendOverall drug useBrand shareAntibiotic spendDisease-specific drug spendDisease-specific drug use6-months mortality1-year mortality2-years mortality
Age 70–75–1223.18–161.21–0.100.00–1.46–66.67–0.410.000.000.01
(<0.0001)(<0.0001)(0.623)(0.1936)(0.0344)(<0.0001)(<0.0001)(0.1191)(0.0068)(<0.0001)
Age 75–80–2346.01–257.770.170.00–1.47–165.39–1.250.010.020.03
(<0.0001)(<0.0001)(0.4242)(0.0151)(0.0405)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 80–85–3189.72–295.901.32–0.01–0.53–235.60–2.030.020.040.08
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.4957)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 85–90–4166.41–342.252.10–0.022.54–314.45–2.900.060.090.17
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0068)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 90–95–5812.00–429.481.94–0.039.64–393.81–3.890.100.170.28
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Age 95+–7212.84–750.14–2.19–0.0416.48–455.85–4.820.150.250.41
(<0.0001)(<0.0001)(0.0057)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Male–773.64316.280.460.018.6166.050.300.010.020.03
(<0.0001)(<0.0001)(0.0019)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Black1845.64–586.92–10.36–0.01–19.08–89.75–1.05–0.01–0.01–0.02
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Hispanic57.90–757.95–11.370.00–9.99–25.94–0.17–0.01–0.03–0.04
(0.832)(<0.0001)(<0.0001)(0.0298)(<0.0001)(0.0167)(0.1076)(<0.0001)(<0.0001)(<0.0001)
Asian–2957.62–110.34–7.130.051.90–5.100.38–0.02–0.03–0.05
(<0.0001)(0.0076)(<0.0001)(<0.0001)(0.2067)(0.6631)(0.0012)(<0.0001)(<0.0001)(<0.0001)
Enhanced Part D plan636.75–267.35–4.93–0.010.24–65.85–0.640.000.000.00
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.7575)(<0.0001)(<0.0001)(0.6655)(0.8898)(0.9322)
Coverage in donut hole790.141435.8321.690.026.23374.053.440.000.010.01
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0245)(0.0008)(<0.0001)
Dually eligible2339.671145.4114.600.0019.71112.671.260.020.030.04
(<0.0001)(<0.0001)(<0.0001)(0.0172)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Low-income subsidy program–626.30926.2311.120.024.93212.071.880.000.010.01
(0.0028)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.0233)(0.0007)(<0.0001)
Log risk score (medical)16509.000.050.080.14
(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Log risk score (drug)4306.2959.67–0.0279.64126.19–1.70
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)

Table 1:

Panel E; Underlying Regression Results: Mental Health Cohort.

Mental healthOverall medical spendOverall drug spendOverall drug useBrand shareAntibiotic spendDisease-specific drug spendDisease-specific drug use6-months mortality1-year mortality2-years mortality
Age 70–75–304.09–264.171.430.001.42–232.23–0.470.010.010.02
(0.4101)(<0.0001)(0.0108)(0.8752)(0.5106)(<0.0001)(0.0015)(0.0008)(0.008)(<0.0001)
Age 75–80–1024.18–443.152.030.002.21–284.96–0.190.020.040.07
(0.0086)(<0.0001)(0.0006)(0.4298)(0.3311)(<0.0001)(0.2208)(<0.0001)(<0.0001)(<0.0001)
Age 80–85–2551.64–634.002.100.004.75–440.08–0.270.040.070.14
(<0.0001)(<0.0001)(0.0007)(0.9491)(0.0462)(<0.0001)(0.1004)(<0.0001)(<0.0001)(<0.0001)
Age 85–90–3936.68–994.851.54–0.028.80–631.76–0.400.080.130.24
(<0.0001)(<0.0001)(0.0331)(<0.0001)(0.0015)(<0.0001)(0.0375)(<0.0001)(<0.0001)(<0.0001)
Age 90–95–6037.45–1255.040.44–0.0311.57–727.23–0.540.130.210.36
(<0.0001)(<0.0001)(0.664)(<0.0001)(0.0027)(<0.0001)(0.0405)(<0.0001)(<0.0001)(<0.0001)
Age 95+–6648.08–1618.66–1.07–0.0631.80–950.37–1.060.170.280.48
(<0.0001)(<0.0001)(0.5511)(<0.0001)(<0.0001)(<0.0001)(0.0257)(<0.0001)(<0.0001)(<0.0001)
Male–330.45336.50–0.940.015.6925.12–1.020.020.030.05
(0.2659)(<0.0001)(0.0367)(<0.0001)(0.001)(0.3153)(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Black1620.37–861.50–12.02–0.02–28.09–125.26–2.78–0.01–0.02–0.03
(0.0007)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(0.002)(<0.0001)(0.0007)(0.0002)(<0.0001)
Hispanic251.31–836.35–10.350.01–16.69–478.16–3.15–0.02–0.04–0.05
(0.7384)(<0.0001)(<0.0001)(0.0099)(0.0002)(<0.0001)(<0.0001)(0.0008)(<0.0001)(<0.0001)
Asian–3662.34–1072.06–12.440.03–13.34–580.30–3.31–0.02–0.03–0.05
(0.0016)(<0.0001)(<0.0001)(0.0003)(0.05)(<0.0001)(<0.0001)(0.1091)(0.0242)(0.0006)
Enhanced Part D Plan259.13–617.05–6.03–0.01–2.42–200.06–0.770.000.000.00
(0.5968)(<0.0001)(<0.0001)(0.0025)(0.3997)(<0.0001)(<0.0001)(0.7957)(0.69)(0.9781)
Coverage in donut hole1363.931761.2822.700.017.74414.863.140.000.010.03
(0.0181)(<0.0001)(<0.0001)(0.0758)(0.0225)(<0.0001)(<0.0001)(0.4586)(0.0383)(0.0003)
Dually eligible2907.851840.6520.53–0.0122.13952.064.800.020.040.08
(<0.0001)(<0.0001)(<0.0001)(0.0662)(<0.0001)(<0.0001)(<0.0001)(0.0002)(<0.0001)(<0.0001)
Low-income subsidy program–2319.68906.427.360.01–1.77385.211.350.000.000.00
(0.0014)(<0.0001)(<0.0001)(0.0321)(0.6778)(<0.0001)(<0.0001)(0.7632)(0.9049)(0.7895)
Log risk score (medical)20257.000.060.100.15
(<0.0001)(<0.0001)(<0.0001)(<0.0001)
Log risk score (drug)4450.9665.51–0.0573.11245.082.14
(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)(<0.0001)

Table 2:

Correlations between Non-Drug Medical Expenditures and Various Drug-Related Utilization Measures (Adjustments to expenditure and utilization measures do not include risk scores, LIS status, or Dual Eligibility).

All elderlyHealthyCHFDiabetesMental health
Overall drug spending0.8600.8280.7640.8000.556
(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***
Overall drug use0.8150.8460.7350.7240.575
(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***
Brand share0.7670.7670.7420.7420.577
(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***
Antibiotic spending0.7930.7010.7030.7280.553
(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***(<0.0001)***
Disease-specific spendingN/AN/A0.6400.5990.276
(<0.0001)***(<0.0001)***(<0.0001)***
Disease-specific useN/AN/A0.5900.6050.345
(<0.0001)***(<0.0001)***(<0.0001)***

Adjusted medical expenditures and drug-related utilization measures are constructed to reflect average demographic and health status characteristics across the sample. Source: author analysis of 2008 Medicare claims data. The healthy cohort includes only beneficiaries without any HCCs from the CMS-HCC Medicare Advantage risk adjustment model.

Table 3:

Correlations between Share of the Population in a Cohort and Non-Drug Expenditures, Adjusted Mortality Rates (Adjustments to expenditure, utilization, and mortality measures do not include risk scores, LIS status, or Dual Eligibility).

HealthyCHFDiabetesMental health
Non-drug medical expenditures–0.0630.0200.0950.035
(0.266)(0.723)(0.092)*(0.531)
Six-month mortality rate–0.0330.0590.0930.081
(0.555)(0.293)(0.097)*(0.152)
One-year mortality rate–0.0400.0070.1120.094
(0.478)(0.899)(0.047)**(0.096)*
Two-year mortality rate–0.0260.0510.1370.099
(0.640)(0.363)(0.015)**(0.079)*

Adjusted medical expenditures, drug-related utilization, and mortality measures are constructed to reflect average demographic and health status characteristics across the sample. Source: author analysis of 2008 Medicare claims data. The healthy cohort includes only beneficiaries without any HCCs from the CMS-HCC Medicare Advantage risk adjustment model.

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Article note:

The views expressed in this paper should not be interpreted as those of the Congressional Budget Office (CBO). This paper has not been subject to CBO’s regular review and editing process.

Published Online: 2016-3-4
Published in Print: 2016-12-1

©2016 Walter de Gruyter GmbH, Berlin/Boston