Identifying reproductive-aged women with physical and sensory disabilities in administrative health data: A systematic review. Issue 3 (July 2020)

• Record Type: Journal Article
• Authors: Brown, Hilary K.; Carty, Adele; Havercamp, Susan M.; Parish, Susan; Lunsky, Yona
• Is Part Of: Disability and health journal. Volume 13:Issue 3(2020)
• Publication Date: 2020-07
• Subjects: Algorithms -- Databases -- Disabled persons -- Registries; People with disabilities -- Health and hygiene -- Periodicals; Health education -- Periodicals; Disabled Persons -- Periodicals; Health Education -- Periodicals; Electronic journals; 362.4
• DOI: 10.1016/j.dhjo.2020.100909
• Languages: English
• ISSNs: 1936-6574

Abstract

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.