Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment.
Despite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5156342?pdf=render |
| _version_ | 1818241791901564928 |
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| author | Barry L Rosenberg Joshua A Kellar Anna Labno David H M Matheson Michael Ringel Paige VonAchen Richard I Lesser Yue Li Justin B Dimick Atul A Gawande Stefan H Larsson Hamilton Moses |
| author_facet | Barry L Rosenberg Joshua A Kellar Anna Labno David H M Matheson Michael Ringel Paige VonAchen Richard I Lesser Yue Li Justin B Dimick Atul A Gawande Stefan H Larsson Hamilton Moses |
| author_sort | Barry L Rosenberg |
| collection | DOAJ |
| description | Despite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in an all-payer population before and after risk-adjustment.We used information from 16 independent data sources, including 22 million all-payer inpatient admissions from the Healthcare Cost and Utilization Project (which covers regions where 50% of the U.S. population lives) to analyze 24 inpatient mortality, inpatient safety, and prevention outcomes. We compared outcome variation at state, hospital referral region, hospital service area, county, and hospital levels. Risk-adjusted outcomes were calculated after adjusting for population factors, co-morbidities, and health system factors. Even after risk-adjustment, there exists large geographical variation in outcomes. The variation in healthcare outcomes exceeds the well publicized variation in US healthcare costs. On average, we observed a 2.1-fold difference in risk-adjusted mortality outcomes between top- and bottom-decile hospitals. For example, we observed a 2.3-fold difference for risk-adjusted acute myocardial infarction inpatient mortality. On average a 10.2-fold difference in risk-adjusted patient safety outcomes exists between top and bottom-decile hospitals, including an 18.3-fold difference for risk-adjusted Central Venous Catheter Bloodstream Infection rates. A 3.0-fold difference in prevention outcomes exists between top- and bottom-decile counties on average; including a 2.2-fold difference for risk-adjusted congestive heart failure admission rates. The population, co-morbidity, and health system factors accounted for a range of R2 between 18-64% of variability in mortality outcomes, 3-39% of variability in patient safety outcomes, and 22-70% of variability in prevention outcomes.The amount of variability in health outcomes in the U.S. is large even after accounting for differences in population, co-morbidities, and health system factors. These findings suggest that: 1) additional examination of regional and local variation in risk-adjusted outcomes should be a priority; 2) assumptions of uniform hospital quality that underpin rationale for policy choices (such as narrow insurance networks or antitrust enforcement) should be challenged; and 3) there exists substantial opportunity for outcomes improvement in the US healthcare system. |
| first_indexed | 2024-12-12T13:34:57Z |
| format | Article |
| id | doaj.art-bba07b10519b47cbb5b663f87bd3d55e |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T13:34:57Z |
| publishDate | 2016-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-bba07b10519b47cbb5b663f87bd3d55e2022-12-22T00:22:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-011112e016676210.1371/journal.pone.0166762Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment.Barry L RosenbergJoshua A KellarAnna LabnoDavid H M MathesonMichael RingelPaige VonAchenRichard I LesserYue LiJustin B DimickAtul A GawandeStefan H LarssonHamilton MosesDespite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in an all-payer population before and after risk-adjustment.We used information from 16 independent data sources, including 22 million all-payer inpatient admissions from the Healthcare Cost and Utilization Project (which covers regions where 50% of the U.S. population lives) to analyze 24 inpatient mortality, inpatient safety, and prevention outcomes. We compared outcome variation at state, hospital referral region, hospital service area, county, and hospital levels. Risk-adjusted outcomes were calculated after adjusting for population factors, co-morbidities, and health system factors. Even after risk-adjustment, there exists large geographical variation in outcomes. The variation in healthcare outcomes exceeds the well publicized variation in US healthcare costs. On average, we observed a 2.1-fold difference in risk-adjusted mortality outcomes between top- and bottom-decile hospitals. For example, we observed a 2.3-fold difference for risk-adjusted acute myocardial infarction inpatient mortality. On average a 10.2-fold difference in risk-adjusted patient safety outcomes exists between top and bottom-decile hospitals, including an 18.3-fold difference for risk-adjusted Central Venous Catheter Bloodstream Infection rates. A 3.0-fold difference in prevention outcomes exists between top- and bottom-decile counties on average; including a 2.2-fold difference for risk-adjusted congestive heart failure admission rates. The population, co-morbidity, and health system factors accounted for a range of R2 between 18-64% of variability in mortality outcomes, 3-39% of variability in patient safety outcomes, and 22-70% of variability in prevention outcomes.The amount of variability in health outcomes in the U.S. is large even after accounting for differences in population, co-morbidities, and health system factors. These findings suggest that: 1) additional examination of regional and local variation in risk-adjusted outcomes should be a priority; 2) assumptions of uniform hospital quality that underpin rationale for policy choices (such as narrow insurance networks or antitrust enforcement) should be challenged; and 3) there exists substantial opportunity for outcomes improvement in the US healthcare system.http://europepmc.org/articles/PMC5156342?pdf=render |
| spellingShingle | Barry L Rosenberg Joshua A Kellar Anna Labno David H M Matheson Michael Ringel Paige VonAchen Richard I Lesser Yue Li Justin B Dimick Atul A Gawande Stefan H Larsson Hamilton Moses Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. PLoS ONE |
| title | Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. |
| title_full | Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. |
| title_fullStr | Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. |
| title_full_unstemmed | Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. |
| title_short | Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment. |
| title_sort | quantifying geographic variation in health care outcomes in the united states before and after risk adjustment |
| url | http://europepmc.org/articles/PMC5156342?pdf=render |
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