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Attributing medical spending to conditions: A comparison of methods
- Source :
- PLoS ONE, Vol 15, Iss 8, p e0237082 (2020), PLoS ONE
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
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.
- Subjects :
- 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
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....e1ae7c42e97dd1649945e8551e2789c5