Evidence map›Paper›PMID 36282202›Full record

ArticleJournal of the American Geriatrics Society2023

Development and validation of novel multimorbidity indices for older adults.

Michael A Steinman, Bocheng Jing, Sachin J Shah, Anael Rizzo, Sei J Lee, Kenneth E Covinsky, Christine S Ritchie, W John Boscardin

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Incomplete Ascertainment of Mortality in a Nationally Representative Longitudinal Study of Community-Living Older Americans.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Higher-Order Disease Interactions in Multimorbidity Measurement: Marginal Benefit Over Additive Disease Summation.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
  9. Observational
  10. Article
  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michael A SteinmanDivision of Geriatrics, UCSF, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-9564-9480
Bocheng JingDivision of Geriatrics, UCSF, San Francisco, California, USA.
Sachin J ShahDivision of Hospital Medicine, UCSF, San Francisco, California, USA.
Anael RizzoDivision of Geriatrics, UCSF, San Francisco, California, USA.
Sei J LeeDivision of Geriatrics, UCSF, San Francisco, California, USA.
Kenneth E CovinskyDivision of Geriatrics, UCSF, San Francisco, California, USA.
Christine S RitchieDivision of Palliative Care and Geriatric Medicine, Massachusetts General Hospital and the Mongan Institute Center for Aging and Serious Illness, Boston, MA, USA.
W John BoscardinDivision of Geriatrics, UCSF, San Francisco, California, USA.

Funding

VARC CoreP30AG044281 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Louise C. Walter · 2013 to 2026
$19.9M
Unnecessary and Harmful Medication Use in Older Adults with DementiaP01AG066605 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI R. Sean Morrison · 2020 to 2026
$17.7M
Prognostic calculators for patients with Alzheimers disease and related dementiasR01AG057751 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI LEE, SEI, SMITH, ALEXANDER KELIIMOEANU · 2018 to 2021
$1.5M
Creating a better index for measuring multimorbidity in older adultsR01AG052041 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI STEINMAN, MICHAEL A. · 2016 to 2018
$1.2M
Mentoring Patient-Oriented Research to Individualize Care for Hospitalized Older Adults with and without Alzheimer's Disease and Related DementiasK24AG066998 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Sei Lee · 2021 to 2026
$1.1M
Development and Validation of 10-Year Life Expectancy Calculators to Individualize Veterans’ Prevention DecisionsI01HX002135 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI LEE, SEI · 2018 to 2021
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HSRD VA I01 HX002135NIA NIH HHS K24 AG066998NIA NIH HHS K24AG066998NIA NIH HHS P01 AG066605NIA NIH HHS P01AG066605NIA NIH HHS P30 AG044281NIA NIH HHS P30AG044281NIA NIH HHS R01 AG052041NIA NIH HHS R01AG052041NIA NIH HHS R01 AG057751NIA NIH HHS R01AG057751U.S. Department of Veterans Affairs VA HSR&D IIR 15-434
6 · The paper itself

Abstract

backgroundMeasuring 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.

methodsHealth 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.

resultsThe 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.

conclusionsA 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.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsActivities of Daily LivingAgedAgingFemaleHumansMaleMedicareMultimorbidityUnited Statesclaims datafunctional impairmentmultimorbidityolder adultsprognostic models

Identifiers

PMID36282202
PMCPMC9870862

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.