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Войти в исследования Medical care · 2020
Comorbidity Assessment Is Uneven Across Veterans Health Administration and Medicare for the Same Patient: Implications for Risk Adjustment.
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Gidwani-Marszowski Risha, Boothroyd Derek, Needleman Jack, Illarmo Samantha, Asch Steven M
Аннотация
OBJECTIVE: Compare comorbidity identification in Medicare and Veterans Health Administration (VA) data for the purposes of risk adjustment.
DATA SOURCES: Analysis of Medicare and VA datasets for dually-enrolled Veterans receiving care in both settings, fiscal years 2010-2014.
STUDY DESIGN: A retrospective analysis of administrative data for a national sample of cancer decedents.
DATA EXTRACTION METHODS: Comorbidities were evaluated using Elixhauser and Charlson coding algorithms.
PRINCIPAL FINDINGS: Clinical comorbidities were more likely to be recorded in Medicare than in VA datasets. Of 42 comorbidities, 36 (86%) were recorded at a different frequency. For example, congestive heart failure was recorded for 22.0% of patients in Medicare data and for 11.3% of patients in VA data (P<0.001).
CONCLUSION: There are large differences in comorbidity assessment across VA and Medicare administrative data for the same patient, posing challenges for risk adjustment.
DATA SOURCES: Analysis of Medicare and VA datasets for dually-enrolled Veterans receiving care in both settings, fiscal years 2010-2014.
STUDY DESIGN: A retrospective analysis of administrative data for a national sample of cancer decedents.
DATA EXTRACTION METHODS: Comorbidities were evaluated using Elixhauser and Charlson coding algorithms.
PRINCIPAL FINDINGS: Clinical comorbidities were more likely to be recorded in Medicare than in VA datasets. Of 42 comorbidities, 36 (86%) were recorded at a different frequency. For example, congestive heart failure was recorded for 22.0% of patients in Medicare data and for 11.3% of patients in VA data (P<0.001).
CONCLUSION: There are large differences in comorbidity assessment across VA and Medicare administrative data for the same patient, posing challenges for risk adjustment.