Attributing medical spending to conditions: A comparison of methods
| Autor: | Kassandra L. Messer, David M. Cutler, Trivellore E. Raghunathan, Kaushik Ghosh, Susan T. Stewart, Irina Bondarenko, Allison B. Rosen |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Health Care Providers Cancer Treatment Social Sciences Cardiovascular Medicine Lung and Intrathoracic Tumors 0302 clinical medicine Medical Conditions Endocrinology Cost of Illness Medicine and Health Sciences 030212 general & internal medicine Medical Personnel Multidisciplinary 030503 health policy & services Regression analysis Regression Professions Oncology Cardiovascular Diseases Costs and Cost Analysis Regression Analysis Medicine Female 0305 other medical science Psychology Cancer Screening Research Article Endocrine Disorders Political Science Science MEDLINE Cardiology Beneficiary Public Policy Medicare Cost burden 03 medical and health sciences Insurance Claim Review Diagnostic Medicine Physicians Cancer Detection and Diagnosis Diabetes Mellitus Humans Set (psychology) Propensity Score Aged Actuarial science Cancers and Neoplasms United States Health Care Metabolic Disorders Propensity score matching People and Places Population Groupings Attribution |
| Zdroj: | PLoS ONE, Vol 15, Iss 8, p e0237082 (2020) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes total spending for a person over a year to their cumulative set of health conditions. Traditionally, this has been done through regression analysis. This paper has two contributions. First, we develop a new cost attribution method to attribute spending to conditions using a more flexible attribution approach, based on propensity score analysis. Second, we compare the propensity score approach to the claims-based approach and the regression approach in a common set of beneficiaries age 65 and older in the 2009 Medicare Current Beneficiary Survey. Our estimates show that the three methods have important differences in spending allocation and that the propensity score model likely offers the best theoretical and empirical combination. |
| Databáze: | OpenAIRE |
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