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Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke: effect of modifier codes.

Publication ,  Journal Article
Goldstein, LB
Published in: Stroke
August 1998

BACKGROUND AND PURPOSE: Discharge ICD-9-CM (International Classification of Diseases, 9th Revision, Clinical Modification) codes have been used to identify patients with acute stroke for epidemiological, quality of care, and cost studies. The aim of this study was to determine if the accuracy of the primary ICD-9-CM codes for ischemic stroke is improved by modifier codes and how specific codes reflect stroke subtype diagnoses. METHODS: Available hospital charts for all patients discharged from a single hospital between May 1995 and June 1997 with ICD-9-CM codes 433 (occlusion and stenosis of precerebral arteries), 434 (occlusion of cerebral arteries), or 436 (acute but ill-defined cerebrovascular disease) listed in the first position were reviewed. The primary discharge diagnosis was verified, and a presumed stroke subtype was assigned on the basis of information provided in the medical record. RESULTS: Charts were available for 175 of the 198 identified patients (88%). Of these, 61% had an acute ischemic stroke (code 433, 4%; 434, 82%; 436, 79%) with the remaining patients having other conditions. Of the 130 patients with a modifier code indicating cerebral infarction, 79% had an acute stroke; of the 45 patients with a modifier code indicating an absence of cerebral infarction, 7% had acute stroke (sensitivity, 0.97; specificity, 0.60). The codes with the highest proportions of ischemic stroke cases were 434.11 (embolic occlusion of cerebral arteries with infarction, 85%), 434.91 (unspecified occlusion of precerebral arteries with infarction, 82%), and 436 (79%), with a combined sensitivity of 0.81 and specificity of 0.90. On review, 73% of patients with code 434.11 had embolic strokes, and 47% of those with code 436 had an identified stroke cause. Of patients with code 434.91, 39% had stroke of uncertain cause, 25% "lacunar," 17% atherothrombosis, and 15% embolism. CONCLUSIONS: Despite the use of modifier codes, 15% to 20% of patients with the indicated primary ICD-9-CM codes have conditions other than acute ischemic stroke. Although the proportion of patients with acute stroke increased from 61% to 79% with the use of modifier codes, the inclusion of modifier codes did not have an appreciable effect on the accuracy of the coding if patients with code 433 are excluded. Assignment of presumed ischemic stroke subtype is particularly inaccurate.

Duke Scholars

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Published In

Stroke

DOI

ISSN

0039-2499

Publication Date

August 1998

Volume

29

Issue

8

Start / End Page

1602 / 1604

Location

United States

Related Subject Headings

  • Neurology & Neurosurgery
  • Incidence
  • Humans
  • Diagnosis-Related Groups
  • Cerebrovascular Disorders
  • Cerebral Infarction
  • Brain Ischemia
  • Acute Disease
  • 4201 Allied health and rehabilitation science
  • 3209 Neurosciences
 

Citation

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Goldstein, L. B. (1998). Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke: effect of modifier codes. Stroke, 29(8), 1602–1604. https://doi.org/10.1161/01.str.29.8.1602
Goldstein, L. B. “Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke: effect of modifier codes.Stroke 29, no. 8 (August 1998): 1602–4. https://doi.org/10.1161/01.str.29.8.1602.
Goldstein, L. B. “Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke: effect of modifier codes.Stroke, vol. 29, no. 8, Aug. 1998, pp. 1602–04. Pubmed, doi:10.1161/01.str.29.8.1602.

Published In

Stroke

DOI

ISSN

0039-2499

Publication Date

August 1998

Volume

29

Issue

8

Start / End Page

1602 / 1604

Location

United States

Related Subject Headings

  • Neurology & Neurosurgery
  • Incidence
  • Humans
  • Diagnosis-Related Groups
  • Cerebrovascular Disorders
  • Cerebral Infarction
  • Brain Ischemia
  • Acute Disease
  • 4201 Allied health and rehabilitation science
  • 3209 Neurosciences