Evidence map›Paper›PMID 37395654›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2023

Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality.

Ariela R Orkaby, Tianwen Huan, Orna Intrator, Shubing Cai, Andrea W Schwartz, Darryl Wieland, Daniel E Hall, Jose F Figueroa, Jordan B Strom, Dae H Kim and 2 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% of its field
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Frailty Screening Using the Risk Analysis Index: A User Guide.Joint Commission journal on quality and patient safety · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Evaluating Frailty Index Integrity: Insights from an International Network Study.medRxiv : the preprint server for health sciences · 2026
    Article
  6. What Do We Know About Prevention of Frailty in Women?American journal of lifestyle medicine · 2025
    Review
  7. Application of Claims-based Frailty Index to a Structured Electronic Health Record Data.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Accelerated biological aging and midlife frailty among U.S. military veterans.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Observational
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Preoperative diagnosis of frailty.The Journal of international medical research · 2024
    Review
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 7 institutions in 1 country.

Ariela R OrkabyNew England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, Boston, Massachusetts, USA.ORCID 0000-0002-4297-6306
Tianwen HuanGeriatrics and Extended Care Data and Analysis Center, Canandaigua VA Medical Center, Canandaigua, New York, USA.
Orna IntratorGeriatrics and Extended Care Data and Analysis Center, Canandaigua VA Medical Center, Canandaigua, New York, USA.
Shubing CaiGeriatrics and Extended Care Data and Analysis Center, Canandaigua VA Medical Center, Canandaigua, New York, USA.
Andrea W SchwartzNew England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, Boston, Massachusetts, USA.
Darryl WielandGeriatrics and Extended Care Data and Analysis Center, Canandaigua VA Medical Center, Canandaigua, New York, USA.
Daniel E HallCenter for Health Equity Research and Promotion; and Pittsburgh GRECC, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA.
Jose F FigueroaDepartment of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.
Jordan B StromDivision of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School Boston, Boston, Massachusetts, USA.ORCID 0000-0002-6592-6141
Dae H KimThe Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-7290-6838
Jane A DriverNew England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, Boston, Massachusetts, USA.ORCID 0000-0001-9759-4607
Bruce KinosianGeriatrics and Extended Care Data Analysis Center and Center for Health Equity Research and Promotion, Cpl. Michael J Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-2098-6340
Brigham and Women's Hospital · USCanandaigua VA Medical Center · USHarvard University · USBeth Israel Deaconess Medical Center · USDuke University · USPhiladelphia VA Medical Center · USUniversity of Pittsburgh · US

Funding

Harnessing the power of CTSA-CDRN data networks: Using social determinants of health, frailty and functional status to identify at-risk patients and improve risk adjustmentU01TR002393 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI SHIREMAN, PAULA K · 2018 to 2021
$3.1M
Identification of the Components of Frailty Using Administrative Data and Metabolite ProfilingK23HL144907 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI STROM, JORDAN BLAIR · 2019 to 2023
$1.0M
Mid-Career Mentoring Award For Patient-Oriented Research in Frailty and Health OutcomesK24AG073527 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI Dae Hyun Kim · 2022 to 2026
$862k
NCATS NIH HHS U01 TR002393NHLBI NIH HHS K23 HL144907NIA NIH HHS K24 AG073527
6 · The paper itself

Abstract

backgroundFrailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans.

methodsRetrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes.

resultsA total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78-0.80) or mortality (0.77-0.79).

conclusionsBased on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.

Indexed as

FrailtyVeteransAgedFemaleFrail ElderlyGeriatric AssessmentHumansInstitutionalizationMaleRetrospective Studies

Identifiers

PMID37395654
PMCPMC10613003
OpenAlexW4382919032

What OpenQuestion holds

Textmetadata
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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.