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The hazards of stroke case selection using administrative data.

Publication ,  Journal Article
Reker, DM; Rosen, AK; Hoenig, H; Berlowitz, DR; Laughlin, J; Anderson, L; Marshall, CR; Rittman, M
Published in: Med Care
February 2002

BACKGROUND: Administrative data and ICD-9-CM diagnostic codes are frequently used in research efforts to evaluate risk adjusted patient outcomes, particularly mortality. Varying ICD-9-CM sampling algorithms have been used to identify stroke patients. OBJECTIVES: This study evaluates the effects of different sampling strategies (one high sensitivity and one high specificity) on modeling stroke mortality as a performance indicator. RESEARCH DESIGN: Risk adjustment models were developed for two stroke cohorts identified using differing ICD-9-CM algorithms. Standard mortality ratios were calculated in a validation sample as network performance measures and compared across the two stroke samples. SUBJECTS: VHA inpatients with stroke during years 1997 (model development) and 1998 (model validation) were selected from the Patient Treatment File based on cerebrovascular diagnostic codes. MEASURES: Patient mortality within 30 days of admission. RESULTS: The model development and validation for each stroke sampling method produced consistent results: c-statistics 0.74 to 0.75, R2 0.07 to 0.09, concordance 73% to 74%. However, ranking differences in network performance varied by 5 or more positions for 7 of the 22 patient networks. CONCLUSIONS: These findings highlight a potential problem when using administrative data to assess stroke mortality. In the absence of an agreed upon definition of stroke patients, results of provider profiling will vary depending on the ICD-9 algorithm used.

Duke Scholars

Published In

Med Care

DOI

ISSN

0025-7079

Publication Date

February 2002

Volume

40

Issue

2

Start / End Page

96 / 104

Location

United States

Related Subject Headings

  • Veterans
  • United States
  • Stroke
  • Sensitivity and Specificity
  • Risk Adjustment
  • Retrospective Studies
  • Management Information Systems
  • Logistic Models
  • Humans
  • Health Services Research
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Reker, D. M., Rosen, A. K., Hoenig, H., Berlowitz, D. R., Laughlin, J., Anderson, L., … Rittman, M. (2002). The hazards of stroke case selection using administrative data. Med Care, 40(2), 96–104. https://doi.org/10.1097/00005650-200202000-00004
Reker, Dean M., Amy K. Rosen, Helen Hoenig, Dan R. Berlowitz, Judith Laughlin, Leigh Anderson, Clifford R. Marshall, and Maude Rittman. “The hazards of stroke case selection using administrative data.Med Care 40, no. 2 (February 2002): 96–104. https://doi.org/10.1097/00005650-200202000-00004.
Reker DM, Rosen AK, Hoenig H, Berlowitz DR, Laughlin J, Anderson L, et al. The hazards of stroke case selection using administrative data. Med Care. 2002 Feb;40(2):96–104.
Reker, Dean M., et al. “The hazards of stroke case selection using administrative data.Med Care, vol. 40, no. 2, Feb. 2002, pp. 96–104. Pubmed, doi:10.1097/00005650-200202000-00004.
Reker DM, Rosen AK, Hoenig H, Berlowitz DR, Laughlin J, Anderson L, Marshall CR, Rittman M. The hazards of stroke case selection using administrative data. Med Care. 2002 Feb;40(2):96–104.

Published In

Med Care

DOI

ISSN

0025-7079

Publication Date

February 2002

Volume

40

Issue

2

Start / End Page

96 / 104

Location

United States

Related Subject Headings

  • Veterans
  • United States
  • Stroke
  • Sensitivity and Specificity
  • Risk Adjustment
  • Retrospective Studies
  • Management Information Systems
  • Logistic Models
  • Humans
  • Health Services Research