Hilary K Brown1, Adele Carty2, Susan M Havercamp3, Susan Parish4, Yona Lunsky5. 1. Interdisciplinary Centre for Health & Society, University of Toronto Scarborough, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Women's College Research Institute, Women's College Hospital, Toronto, Canada. Electronic address: hk.brown@utoronto.ca. 2. Dalla Lana School of Public Health, University of Toronto, Toronto, Canada. 3. Center for Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, United States. 4. College of Health Professions, Virginia Commonwealth University, Richmond, VA, United States. 5. Department of Psychiatry, University of Toronto, Toronto, Canada; Centre for Addiction & Mental Health, Toronto, Canada.
Abstract
BACKGROUND: Women with disabilities experience significant health disparities. A barrier to progress in addressing these disparities is the lack of population-based data on their health outcomes, which are needed to plan health care delivery systems. Administrative health data are increasingly being used to measure the health of entire populations, but these data may only capture impairment and not activity and participation restrictions. OBJECTIVE: We conducted a systematic review to identify and appraise existing literature on the development and validation of algorithms to identify reproductive-aged women with physical and sensory disabilities in administrative health data. METHODS: We searched Medline, EMBASE, CINAHL, PsycINFO, and Scopus from inception to April 2019 for studies of the development and/or validation of algorithms using diagnostic, procedural, or prescription codes to identify physical and sensory disabilities in administrative health data. Study and algorithm characteristics were extracted and quality was assessed using standardized instruments. RESULTS: Of 14,073 articles initially identified, we reviewed 6 articles representing 2 unique algorithms. One algorithm aimed to correlate diagnoses, procedure codes, and prescriptions with ability to access routine care as an indicator of functional limitation. The other algorithm used diagnostic and procedure codes to identify use of mobility-assistive devices to measure functional limitation. Only one algorithm was validated against self-reported disability. CONCLUSIONS: Our findings underscore the need to strengthen current methods to identify disability in administrative health data, including linkage with other sources of information on functional limitations, so that population-based data can be used to optimize health care for women with disabilities.
BACKGROUND:Women with disabilities experience significant health disparities. A barrier to progress in addressing these disparities is the lack of population-based data on their health outcomes, which are needed to plan health care delivery systems. Administrative health data are increasingly being used to measure the health of entire populations, but these data may only capture impairment and not activity and participation restrictions. OBJECTIVE: We conducted a systematic review to identify and appraise existing literature on the development and validation of algorithms to identify reproductive-aged women with physical and sensory disabilities in administrative health data. METHODS: We searched Medline, EMBASE, CINAHL, PsycINFO, and Scopus from inception to April 2019 for studies of the development and/or validation of algorithms using diagnostic, procedural, or prescription codes to identify physical and sensory disabilities in administrative health data. Study and algorithm characteristics were extracted and quality was assessed using standardized instruments. RESULTS: Of 14,073 articles initially identified, we reviewed 6 articles representing 2 unique algorithms. One algorithm aimed to correlate diagnoses, procedure codes, and prescriptions with ability to access routine care as an indicator of functional limitation. The other algorithm used diagnostic and procedure codes to identify use of mobility-assistive devices to measure functional limitation. Only one algorithm was validated against self-reported disability. CONCLUSIONS: Our findings underscore the need to strengthen current methods to identify disability in administrative health data, including linkage with other sources of information on functional limitations, so that population-based data can be used to optimize health care for women with disabilities.
Authors: Susel Góngora Alonso; Isabel de la Torre-Díez; Sofiane Hamrioui; Miguel López-Coronado; Diego Calvo Barreno; Lola Morón Nozaleda; Manuel Franco Journal: J Med Syst Date: 2018-07-21 Impact factor: 4.460
Authors: Lesley A Tarasoff; Yona Lunsky; Simon Chen; Astrid Guttmann; Susan M Havercamp; Susan L Parish; Simone N Vigod; Adele Carty; Hilary K Brown Journal: J Womens Health (Larchmt) Date: 2020-07-14 Impact factor: 2.681