Does Prescription Drug Adherence Reduce Hospitalizations and Costs?
We estimate the impact of diabetic drug adherence on hospitalizations, ER visits, and hospital costs, using insurance claims from MarketScan® employer data. However, it is often difficult to measure the impact of drug adherence on hospitalizations since both adherence and hospitalizations may be correlated with unobservable patient severity. We control for such unobservables using propensity score methods and instrumental variables for adherence such as drug coinsurance levels and direct-to- consumer-advertising. We find a significant bias due to unobservable severity in that patients with more severe health are more apt to comply with medications. Thus, the relationship between adherence and hospitalization will be underestimated if one does not control for unobservable severity. Overall, we find that increasing diabetic drug adherence from 50% to 100% reduced the hospitalization rate by 23.3% (p=0.02) from 15% to 11.5%. ER visits are reduces by 46.2% (p=.04) from 17.3% to 9.3%. While such an increase in adherence increases diabetic drug spending by $776 a year per diabetic, the annual cost savings for averted hospitalizations are $886 per diabetic, a cost offset of $110 (p=0.02), or $1.14 per $1 spent on drugs.
|Date of creation:||Jan 2010|
|Date of revision:|
|Publication status:||published as Does prescription drug adherence reduce hospitalizations and costs? The case of diabetes. Encinosa, W., Bernard, D., Dor, A. "Does prescription drug adherence reduce hospitalizations and costs? The case of diabetes." Advances in Health Economics and Health Services Research, Vol. 22 151-173. Emerald Group Publishing Limited, Apr 2010.|
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- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002.
"Instrumental variables and GMM: Estimation and testing,"
Boston College Working Papers in Economics
545, Boston College Department of Economics, revised 14 Feb 2003.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," North American Stata Users' Group Meetings 2003 05, Stata Users Group.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," United Kingdom Stata Users' Group Meetings 2003 02, Stata Users Group.
- Avi Dor & William Encinosa, 2010. "How Does Cost-Sharing Affect Drug Purchases? Insurance Regimes in the Private Market for Prescription Drugs," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 19(3), pages 545-574, 09.
- Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
- Cragg, John G, 1983. "More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form," Econometrica, Econometric Society, vol. 51(3), pages 751-63, May.
- Partha Deb & Pravin K. Trivedi & David M. Zimmer, 2009.
"Dynamic Cost-offsets of Prescription Drug Expenditures: Panel Data Analysis Using a Copula-based Hurdle Model,"
NBER Working Papers
15191, National Bureau of Economic Research, Inc.
- Deb P & Trivedi PK & Zimmer DM, 2009. "Dynamic Cost-offsets of Prescription Drug Expenditures: Panel Data Analysis Using a Copula-based Hurdle Model," Health, Econometrics and Data Group (HEDG) Working Papers 09/15, HEDG, c/o Department of Economics, University of York.
- Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
- Dehejia, R.H. & Wahba, S., 1998.
"Propensity Score Matching Methods for Non-Experimental Causal Studies,"
1998_02, Columbia University, Department of Economics.
- Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
- Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity score matching methods for non-experimental causal studies," Discussion Papers 0102-14, Columbia University, Department of Economics.
- Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
- Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
- Edwin Leuven & Barbara Sianesi, 2003. "PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing," Statistical Software Components S432001, Boston College Department of Economics, revised 19 Jan 2015.
- Amitabh Chandra & Jonathan Gruber & Robin McKnight, 2007. "Patient Cost-Sharing, Hospitalization Offsets, and the Design of Optimal Health Insurance for the Elderly," NBER Working Papers 12972, National Bureau of Economic Research, Inc.
- Gaynor Martin & Li Jian & Vogt William B, 2007. "Substitution, Spending Offsets, and Prescription Drug Benefit Design," Forum for Health Economics & Policy, De Gruyter, vol. 10(2), pages 1-33, July.
- Baoping Shang & Dana P. Goldman, 2007. "Prescription Drug Coverage and Elderly Medicare Spending," NBER Working Papers 13358, National Bureau of Economic Research, Inc.
- Avi Dor, 2004. "Optimal Price Rules, Administered Prices and Suboptimal Prevention: Evidence from a Medicare Program," Journal of Regulatory Economics, Springer, vol. 25(1), pages 81-104, January.
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