title: Development of administrative data algorithms to identify patients with critical limb ischemia.
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 2:1 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.
authors.affiliation: Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
authors.forename: Wobo
authors.initials: W
authors.lastname: Bekwelem
authors.affiliation: Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA.
authors.forename: Lindsay G S
authors.initials: LG
authors.lastname: Bengtson
authors.affiliation: Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
authors.forename: Niki C
authors.initials: NC
authors.lastname: Oldenburg
authors.affiliation: Center for Healthcare Research and Innovation, Allina Health, Minneapolis, MN, USA.
authors.forename: Tamara J
authors.initials: TJ
authors.lastname: Winden
authors.affiliation: Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA Division of Angiology, Kantonsspital Aarau AG, Aarau, Switzerland.
authors.forename: Hong H
authors.initials: HH
authors.lastname: Keo
authors.affiliation: Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA.
authors.forename: Alan T
authors.initials: AT
authors.lastname: Hirsch
authors.affiliation: Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN, USA sueduval@umn.edu.
authors.forename: Sue
authors.initials: S
authors.lastname: Duval
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005121:Extremities / Q000098:blood supply*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D007511:Ischemia / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D058729:Peripheral Arterial Disease / Q000175:diagnosis*; D012042:Registries; D012307:Risk Factors
keywords: administrative data; critical limb ischemia; peripheral artery disease; registries