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Attributing medical spending to conditions: A comparison of methods.

ABSTRACT: 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.

SUBMITTER: Ghosh K

PROVIDER: S-EPMC7416958 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Attributing medical spending to conditions: A comparison of methods.

Ghosh Kaushik K Bondarenko Irina I Messer Kassandra L KL Stewart Susan T ST Raghunathan Trivellore T Rosen Allison B AB Cutler David M DM

PloS one 20200810 8

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 ...[more]

PMID: 32776954

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Project description:ObjectiveTo evaluate whether longer term participation in the bundled payments for care initiative (BPCI) for medical conditions in the United States, which held hospitals financially accountable for all spending during an episode of care from hospital admission to 90 days after discharge, was associated with changes in spending, mortality, or health service use.DesignQuasi-experimental difference-in-differences analysis.SettingUS hospitals participating in bundled payments for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease (COPD), or pneumonia, and propensity score matched to non-participating hospitals.Participants238 hospitals participating in the Bundled Payments for Care Improvement initiative (BPCI) and 1415 non-BPCI hospitals. 226 BPCI hospitals were matched to 700 non-BPCI hospitals.Main outcome measuresPrimary outcomes were total spending on episodes and death 90 days after discharge. Secondary outcomes included spending and use by type of post-acute care. BPCI and non-BPCI hospitals were compared by patient, hospital, and hospital market characteristics. Market characteristics included population size, competitiveness, and post-acute bed supply.ResultsIn the 226 BPCI hospitals, episodes of care totaled 261 163 in the baseline period and 93 562 in the treatment period compared with 211 208 and 78 643 in the 700 matched non-BPCI hospitals, respectively, with small differences in hospital and market characteristics after matching. Differing trends were seen for some patient characteristics (eg, mean age change -0.3 years at BPCI hospitals v non- BPCI hospitals, P<0.001). In the adjusted analysis, participation in BPCI was associated with a decrease in total episode spending (-1.2%, 95% confidence interval -2.3% to -0.2%). Spending on care at skilled nursing facilities decreased (-6.3%, -10.0% to -2.5%) owing to a reduced number of facility days (-6.2%, -9.8% to -2.6%), and home health spending increased (4.4%, 1.4% to 7.5%). Mortality at 90 days did not change (-0.1 percentage points, 95% confidence interval -0.5 to 0.2 percentage points).ConclusionsIn this longer term evaluation of a large national programme on medical bundled payments in the US, participation in bundles for four common medical conditions was associated with savings at three years. The savings were generated by practice changes that decreased use of high intensity care after hospital discharge without affecting quality, which also suggests that bundles for medical conditions could require multiple years before changes in savings and practice emerge.

Project description:ObjectiveTo estimate the relationship between variations in medical spending and health outcomes of the elderly.Data sources1992-2002 Medicare Current Beneficiary Surveys.Study designWe used instrumental variable (IV) estimation to identify the relationships between alternative measures of elderly Medicare beneficiaries' medical spending over a 3-year observation period and health status, measured by the Health and Activity Limitation Index (HALex) and survival status at the end of the 3 years. We used the Dartmouth Atlas End-of-Life Expenditure Index defined for hospital referral regions in 1996 as the exogenous identifying variable to construct the IVs for medical spending.Data collection/extraction methodsThe analysis sample includes 17,438 elderly (age >64) beneficiaries who entered the Medicare Current Beneficiary Survey in the fall of each year from 1991 to 1999, were not institutionalized at baseline, stayed in fee-for-service Medicare for the entire observation period, and survived for at least 2 years. Measures of baseline health were constructed from information obtained in the fall of the year the person entered the survey, and changes in health were from subsequent interviews over the entire observation period. Medicare and total medical spending were constructed from Medicare claims and self-reports of other spending over the entire observation period.Principal findingsIV estimation results in a positive and statistically significant relationship between medical spending and better health: 10 percent greater medical spending over the prior 3 years (mean=U.S.$2,709) is associated with a 1.9 percent larger HALex value (p=.045; range 1.2-2.2 percent depending on medical spending measure) and a 1.5 percent greater survival probability (p=.039; range 1.2-1.7 percent).ConclusionsOn average, greater medical spending is associated with better health status of Medicare beneficiaries, implying that across-the-board reductions in Medicare spending may result in poorer health for some beneficiaries.

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Attributing medical spending to conditions: A comparison of methods.

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Attributing medical spending to conditions: A comparison of methods.

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