The DOI matches its Crossref record.
Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease
Abstract
In administrative databases the International Classification of Diseases, Version 9, Clinical Modification (ICD-9-CM) is often used to identify patients with specific diagnoses. However, certain conditions may not be accurately reflected by the ICD-9 codes. We assessed the accuracy of ICD-9 coding for cerebrovascular disease by comparing ICD-9 codes in an administrative database with clinical findings ascertained from medical record abstractions. We selected patients with ICD-9 diagnostic codes of 433 through 436 (in either the primary or secondary positions) from an administrative database of patients hospitalized in five academic medical centers in 1992. Medical records of the selected patients were reviewed by trained medical abstractors, and the patients' clinical conditions during the admission (stroke, TIA, asymptomatic) were recorded, as well as any history of cerebrovascular symptoms. Results of the medical record review were compared with the ICD-9 codes from the administrative database. More than 85% of those patients with the ICD-9 code 433 were asymptomatic for the index admission. More than one-third of these asymptomatic patients did not undergo either cerebral angiography or carotid endarterectomy. For ICD-9 code 434, 85% of patients were classified as having a stroke and for ICD-9 code 435, 77% had TIAs. For code 436, 77% of patients were classified as having strokes. Limiting the identifying ICD-9 code to the primary position increased the likelihood of agreement with the medical record review. The ICD-9 coding scheme may be inaccurate in the classification of patients with ischemic cerebrovascular disease. Its limitations must be recognized in the analyses of administrative databases selected by using ICD-9 codes 433 through 436.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Gage, B. F., Waterman, A. D., Shannon, W., Boechler, M., Rich, M. W., & Radford, M. J. (2001) · JAMA · doi:10.1001/jama.285.22.2864 · Cited by 4,832
Validating Administrative Data in Stroke Research
Tirschwell, D. L., & Longstreth, W. T. (2002) · Stroke · doi:10.1161/01.str.0000032240.28636.bd · Cited by 658
Mortality after the Hospitalization of a Spouse
Christakis, N. A., & Allison, P. D. (2006) · New England Journal of Medicine · doi:10.1056/nejmsa050196 · Cited by 501
Fang, M. C., Singer, D. E., Chang, Y., Hylek, E. M., Henault, L. E., Jensvold, N. G., & Go, A. S. (2005) · Circulation · doi:10.1161/circulationaha.105.553438 · Cited by 469
Validity of diagnostic codes for acute stroke in administrative databases: a systematic review.
McCormick, N., Bhole, V., Lacaille, D., & Avina-Zubieta, J. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135834 · Cited by 414
Metadata
- Authors
- Benesch, C., Witter, D. M., Wilder, A. L., Duncan, P. W., Samsa, G. P., & Matchar, D. B.
- Venue
- Neurology
- Published
- 1997-09
- Volume
- 49
- Issue
- 3
- Pages
- 660-664
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2004198484
- Cited by
- 331
- References
- 0
- FWCI
- 27.31
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease. https://app.cochat.ai/papers/10.1212/wnl.49.3.660
- The paper
- Benesch, C., Witter, D. M., Wilder, A. L., Duncan, P. W., Samsa, G. P., & Matchar, D. B. (1997). Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease. Neurology. https://doi.org/10.1212/wnl.49.3.660
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.