Development and validation of novel multimorbidity indices for older adults
Background Measuring multimorbidity in claims data is used for risk adjustment and identifying populations at high risk for adverse events. Multimorbidity indices such as Charlson and Elixhauser scores have important limitations. We sought to create a better method of measuring multimorbidity using...
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Published in | Journal of the American Geriatrics Society (JAGS) Vol. 71; no. 1; pp. 121 - 135 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken, USA
John Wiley & Sons, Inc
01.01.2023
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Background
Measuring multimorbidity in claims data is used for risk adjustment and identifying populations at high risk for adverse events. Multimorbidity indices such as Charlson and Elixhauser scores have important limitations. We sought to create a better method of measuring multimorbidity using claims data by incorporating geriatric conditions, markers of disease severity, and disease‐disease interactions, and by tailoring measures to different outcomes.
Methods
Health conditions were assessed using Medicare inpatient and outpatient claims from subjects age 67 and older in the Health and Retirement Study. Separate indices were developed for ADL decline, IADL decline, hospitalization, and death, each over 2 years of follow‐up. We validated these indices using data from Medicare claims linked to the National Health and Aging Trends Study.
Results
The development cohort included 5012 subjects with median age 76 years; 58% were female. Claims‐based markers of disease severity and disease‐disease interactions yielded minimal gains in predictive power and were not included in the final indices. In the validation cohort, after adjusting for age and sex, c‐statistics for the new multimorbidity indices were 0.72 for ADL decline, 0.69 for IADL decline, 0.72 for hospitalization, and 0.77 for death. These c‐statistics were 0.02–0.03 higher than c‐statistics from Charlson and Elixhauser indices for predicting ADL decline, IADL decline, and hospitalization, and <0.01 higher for death (p < 0.05 for each outcome except death), and were similar to those from the CMS‐HCC model. On decision curve analysis, the new indices provided minimal benefit compared with legacy approaches. C‐statistics for both new and legacy indices varied substantially across derivation and validation cohorts.
Conclusions
A new series of claims‐based multimorbidity measures were modestly better at predicting hospitalization and functional decline than several legacy indices, and no better at predicting death. There may be limited opportunity in claims data to measure multimorbidity better than older methods. |
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Bibliography: | Funding information National Institute on Aging, Grant/Award Numbers: K24AG066998, P01AG066605, P30AG044281, R01AG052041, R01AG057751; U.S. Department of Veterans Affairs, Grant/Award Number: VA HSR&D IIR 15‐434 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Study concept and design: Michael A. Steinman, Bocheng Jing, Sachin J. Shah, Sei J. Lee, Kenneth E. Covinsky, Christine S. Ritchie, W. John Boscardin. Acquisition of subjects and/or data: Michael A. Steinman, Bocheng Jing, Anael Rizzo, Kenneth E. Covinsky, W. John Boscardin. Analysis and interpretation: Michael A. Steinman, Bocheng Jing, Sachin J. Shah, Anael Rizzo, Sei J. Lee, Kenneth E. Covinsky, Christine S. Ritchie, W. John Boscardin. Initial drafting of manuscript: Michael A. Steinman. Critical review of manuscript: Bocheng Jing, Sachin J. Shah, Anael Rizzo, Sei J. Lee, Kenneth E. Covinsky, Christine S. Ritchie, W. John Boscardin. AUTHOR CONTRIBUTIONS |
ISSN: | 0002-8614 1532-5415 1532-5415 |
DOI: | 10.1111/jgs.18052 |