Evidence map›Paper›PMID 24159270›Full record

ArticlePerspectives in health information managemen2013

Exploration of ICD-9-CM coding of chronic disease within the Elixhauser Comorbidity Measure in patients with chronic heart failure.

Jennifer Hornung Garvin, Andrew Redd, Dan Bolton, Pauline Graham, Dominic Roche, Peter Groeneveld, Molly Leecaster, Shuying Shen, Mark G Weiner

Abstract read
In one paragraph

Article in Perspectives in health information managemen, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Observational
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. What Are the 30-day Readmission Rates Across Orthopaedic Subspecialties?Clinical orthopaedics and related research · 2016
    Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jennifer Hornung GarvinJennifer Hornung Garvin, PhD, MBA, RHIA, CTR, CPHQ, CCS, FAHIMA, is a core research investigator in the Informatics, Decision Enhancement, and Surveillance (IDEAS) Center at the Salt Lake City VA Healthcare System and an Associate Professor in the Department of Biomedical Informatics at the University of Utah School of Medicine in Salt Lake City, UT.
Andrew Redd
Dan Bolton
Pauline Graham
Dominic Roche
Peter Groeneveld
Molly Leecaster
Shuying Shen
Mark G Weiner

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionInternational Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes capture comorbidities that can be used to risk adjust nonrandom patient groups. We explored the accuracy of capturing comorbidities associated with one risk adjustment method, the Elixhauser Comorbidity Measure (ECM), in patients with chronic heart failure (CHF) at one Veterans Affairs (VA) medical center. We explored potential reasons for the differences found between the original codes assigned and conditions found through retrospective review.

methodsThis descriptive, retrospective study used a cohort of patients discharged with a principal diagnosis coded as CHF from one VA medical center in 2003. One admission per patient was used in the study; with multiple admissions, only the first admission was analyzed. We compared the assignment of original codes assigned to conditions found in a retrospective, manual review of the medical record conducted by an investigator with coding expertise as well as by physicians. Members of the team experienced with assigning ICD-9-CM codes and VA coding processes developed themes related to systemic reasons why chronic conditions were not coded in VA records using applied thematic techniques.

resultsIn the 181-patient cohort, 388 comorbid conditions were identified; 305 of these were chronic conditions, originally coded at the time of discharge with an average of 1.7 comorbidities related to the ECM per patient. The review by an investigator with coding expertise revealed a total of 937 comorbidities resulting in 618 chronic comorbid conditions with an average of 3.4 per patient; physician review found 872 total comorbidities with 562 chronic conditions (average 3.1 per patient). The agreement between the original and the retrospective coding review was 88 percent. The kappa statistic for the original and the retrospective coding review was 0.375 with a 95 percent confidence interval (CI) of 0.352 to 0.398. The kappa statistic for the retrospective coding review and physician review was 0.849 (CI, 0.823-0.875). The kappa statistic for the original coding and the physician review was 0.340 (CI, 0.316-0.364). Several systemic factors were identified, including familiarity with inpatient VA and non-VA guidelines, the quality of documentation, and operational requirements to complete the coding process within short time frames and to identify the reasons for movement within a given facility.

conclusionComorbidities within the ECM representing chronic conditions were significantly underrepresented in the original code assignment. Contributing factors potentially include prioritization of codes related to acute conditions over chronic conditions; coders' professional training, educational level, and experience; and the limited number of codes allowed in initial coding software. This study highlights the need to evaluate systemic causes of underrepresentation of chronic conditions to improve the accuracy of risk adjustment used for health services research, resource allocation, and performance measurement.

Indexed as

Clinical CodingInternational Classification of DiseasesVeteransAdultAgedAged, 80 and overChronic DiseaseComorbidityFemaleHeart FailureHospitals, VeteransHumansMaleMiddle AgedRetrospective Studiesadverse drug eventscomorbiditycomplicationsheart failureInternational Classification of Diseasesrisk adjustmentveterans

Identifiers

PMID24159270
PMCPMC3797549

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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.