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 inJournal of the American Geriatrics Society (JAGS) Vol. 71; no. 1; pp. 121 - 135
Main Authors Steinman, Michael A., Jing, Bocheng, Shah, Sachin J., Rizzo, Anael, Lee, Sei J., Covinsky, Kenneth E., Ritchie, Christine S., Boscardin, W. John
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.01.2023
Wiley Subscription Services, Inc
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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.
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
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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