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Development of administrative data algorithms to identify patients with critical limb ischemia.
Bekwelem, Wobo; Bengtson, Lindsay G S; Oldenburg, Niki C; Winden, Tamara J; Keo, Hong H; Hirsch, Alan T; Duval, Sue.
Afiliación
  • Bekwelem W; Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
  • Bengtson LG; Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA.
  • Oldenburg NC; Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
  • Winden TJ; Center for Healthcare Research and Innovation, Allina Health, Minneapolis, MN, USA.
  • Keo HH; Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA Division of Angiology, Kantonsspital Aarau AG, Aarau, Switzerland.
  • Hirsch AT; Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
  • Duval S; Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA sueduval@umn.edu.
Vasc Med ; 19(6): 483-90, 2014 Dec.
Article en En | MEDLINE | ID: mdl-25447239
ABSTRACT
Administrative data have been used to identify patients with various diseases, yet no prior study has determined the utility of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-based codes to identify CLI patients. CLI cases (n=126), adjudicated by a vascular specialist, were carefully defined and enrolled in a hospital registry. Controls were frequency matched to cases on age, sex and admission date in a 21 ratio. ICD-9-CM codes for all patients were extracted. Algorithms were developed using frequency distributions of these codes, risk factors and procedures prevalent in CLI. The sensitivity for each algorithm was calculated and applied within the hospital system to identify CLI patients not included in the registry. Sensitivity ranged from 0.29 to 0.92. An algorithm based on diagnosis and procedure codes exhibited the best overall performance (sensitivity of 0.92). Each algorithm had differing CLI identification characteristics based on patient location. Administrative data can be used to identify CLI patients within a health system. The algorithms, developed from these data, can serve as a tool to facilitate clinical care, research, quality improvement, and population surveillance.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Sistema de Registros / Extremidades / Enfermedad Arterial Periférica / Isquemia Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Vasc Med Asunto de la revista: ANGIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Sistema de Registros / Extremidades / Enfermedad Arterial Periférica / Isquemia Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Vasc Med Asunto de la revista: ANGIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos