Regional Growth in Medicare Spending, 1992-2010.
Ontology highlight
ABSTRACT: Objective
To determine if regions with high Medicare expenditures in a given setting remain high cost over time.Data sources/study setting
One hundred percent of national Medicare Parts A and B fee-for-service beneficiary claims data and enrollment for 1992-2010.Study design
Patients are classified into regions. Claims are price-standardized. Risk adjustment is performed at the beneficiary level using the CMS Hierarchical Condition Categories model. Correlation analyses are conducted.Data collection/extraction methods
The data were obtained through a contract with CMS for a study performed for the Institute of Medicine.Principal findings
High-cost regions in 1992 are likely to remain high cost in 2010. Stability in regional spending is highest in the home health, inpatient hospital, and outpatient hospital settings over this time period. Despite the persistence of a region's relative spending over time, a region's spending levels in all settings except home health tend to regress toward the mean.Conclusions
Relatively high-cost regions tend to remain so over long periods of time, even after controlling for patient health status and geographic price variation, suggesting that the observed effect reflects real differences in practice patterns.
SUBMITTER: Chicklis C
PROVIDER: S-EPMC4600362 | biostudies-literature | 2015 Oct
REPOSITORIES: biostudies-literature
Publications
Regional Growth in Medicare Spending, 1992-2010.
Chicklis Camille C MaCurdy Thomas T Bhattacharya Jay J Shafrin Jason J Zaidi Sajid S Rogers Daniel D
Health services research 20150212 5
<h4>Objective</h4>To determine if regions with high Medicare expenditures in a given setting remain high cost over time.<h4>Data sources/study setting</h4>One hundred percent of national Medicare Parts A and B fee-for-service beneficiary claims data and enrollment for 1992-2010.<h4>Study design</h4>Patients are classified into regions. Claims are price-standardized. Risk adjustment is performed at the beneficiary level using the CMS Hierarchical Condition Categories model. Correlation analyses a ...[more]
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