Institutional Affiliation: University of Michigan
|Attributing Medical Spending to Conditions: A Comparison of Methods|
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Partitioning medical spending into conditions is essential to understanding the cost burden of medical care. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition listed as its cause. The second decomposes total spending for a person over a year to the cumulative set of conditions they have. Traditionally, this has been done through regression analysis. This paper makes two contributions. First, we develop a new method to attribute spending to conditions using propensity score models. Second, we compare the claims attribution approach to the regression approach and our propensity score stratification method in a common set of beneficiaries age 65 and over drawn from the 2009 Medicare Current Beneficiary Surve...
|Strengthening National Data to Better Measure What We Are Buying in Health Care: Reconciling National Health Expenditures with Detailed Survey Data|
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As health care financing, organization, and delivery innovations proliferate, the need for comprehensive, detailed data on medical spending has never been more apparent. This study builds on previous work to provide a more comprehensive accounting of medical spending at the individual level than has been done in the past. We account for spending by the entire population: the civilian, non-institutionalized population that is the subject of past studies, as well as high medical spenders, the institutionalized, the incarcerated, and active-duty military personnel. We use within-imputation and other adjustments to build a micro dataset and reconcile survey data based on our estimate of medical spending to the National Health Expenditure Accounts (NHEA). The micro dataset we build can be used ...