Development of administrative data algorithms to identify patients with critical limb ischemia

被引:25
作者
Bekwelem, Wobo [1 ,2 ]
Bengtson, Lindsay G. S. [3 ]
Oldenburg, Niki C. [1 ,2 ]
Winden, Tamara J. [4 ]
Keo, Hong H. [3 ,5 ]
Hirsch, Alan T. [1 ,2 ]
Duval, Sue [1 ,2 ]
机构
[1] Univ Minnesota, Sch Med, Lillehei Heart Inst, Minneapolis, MN 55455 USA
[2] Univ Minnesota, Sch Med, Div Cardiovasc, Minneapolis, MN 55455 USA
[3] Univ Minnesota, Sch Publ Hlth, Div Epidemiol & Community Hlth, Minneapolis, MN 55455 USA
[4] Allina Hlth, Ctr Healthcare Res & Innovat, Minneapolis, MN USA
[5] Kantonsspital Aarau AG, Div Angiol, Aarau, Switzerland
关键词
peripheral artery disease; registries; administrative data; critical limb ischemia; PERIPHERAL ARTERIAL-DISEASE; CLAIMS DATA; PERFORMANCE-MEASURES; QUALITY IMPROVEMENT; AMPUTATION; MORTALITY; INTERVENTIONS; SURGERY; EVENTS; IMPACT;
D O I
10.1177/1358863X14559589
中图分类号
R6 [外科学];
学科分类号
1002 ; 100210 ;
摘要
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.
引用
收藏
页码:483 / 490
页数:8
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