Evidence map›Paper›PMID 42274218›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2026

Validating ICD code case definitions for condition case ascertainment in multimorbidity measurement: a retrospective chart review.

Ashley J Kang, Chi-Hong Tseng, Melissa Y Wei

Abstract readValidation Study
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ashley J KangDivision of General Internal Medicine and Health Services Research, Department of Medicine, University of California at Los Angeles, Los Angeles, California, United States.
Chi-Hong TsengDivision of General Internal Medicine and Health Services Research, Department of Medicine, University of California at Los Angeles, Los Angeles, California, United States.ORCID 0000-0002-2549-6167
Melissa Y WeiDivision of General Internal Medicine and Health Services Research, Department of Medicine, University of California at Los Angeles, Los Angeles, California, United States.ORCID 0000-0001-5093-6040

Funding

New EHR-based multimorbidity index for diverse populations across the lifespan: development, validation, and applicationR01AG083370 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WEI, MELISSA · 2023 to 2025
$1.8M
National Institute on Aging at the National Institutes of Health 5R01AG083370NIA NIH HHS R01 AG083370
6 · The paper itself

Abstract

backgroundAccurate case ascertainment of chronic conditions is critical for research, clinical decision-making, and population health management, especially for older adults with high multimorbidity. However, validation of International Classification of Diseases (ICD)-based case definitions in the electronic health record (EHR) data remains limited. We sought to determine whether a single ICD code is sufficient for accurate identification of chronic conditions in the EHR, or whether multiple codes improve validity.

methodsPopulation-based retrospective chart review, 2013-2019, at large academic tertiary and quaternary care health system. Our sample included adults aged ≥18 years with ≥2 encounters within a 2-year period. We conducted gold-standard chart review to determine validity of using ≥1 or ≥2 ICD codes to identify 23 chronic conditions included in the validated multimorbidity-weighted index, specifically those lacking robust case definitions in EHR data. Validation statistics included positive predictive value (PPV), negative predictive value, Cohen's kappa, sensitivity, specificity, and percent sample size loss associated with stricter ≥2 ICD code case definitions.

resultsThe final analytic sample included 780 873 adults (mean [SD] age 47.7 [18.0] years, 56.9% female). For 22 of 23 conditions, use of ≥1 ICD code yielded a PPV ≥0.70. Requiring ≥2 ICD codes yielded minimal improvement in PPV but with substantial sample size loss that ranged from 16.8% to 64.5%.

conclusionsAt least one ICD code was sufficient to accurately identify most chronic conditions with high accuracy in the EHR over a multi-year timeframe. However, condition-specific validation remains essential, as performance varies by condition.

Indexed as

Electronic Health RecordsInternational Classification of DiseasesMultimorbidityAdultAgedChronic DiseaseFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesChart reviewChronic conditionsComorbidityElectronic health record dataMultimorbidity

Identifiers

PMID42274218
PMCPMC13372667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.