Code sets for respiratory symptoms in electronic health records research: a systematic review protocol. Issue 3 (3rd March 2019)

• Record Type: Journal Article
• Authors: Jayatunga, Wikum; Stone, Philip; Aldridge, Robert W; Quint, Jennifer K; George, Julie
• Is Part Of: BMJ open. Volume 9:Issue 3(2019)
• Publication Date: 2019-03-03
• Subjects: electronic health records -- coding -- clinical coding -- respiratory -- symptoms -- code sets; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2018-025965
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Introduction: Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory conditions, which result in significant morbidity worldwide. These conditions are associated with a range of non-specific symptoms, which in themselves are a target for health research. Such research is increasingly being conducted using electronic health records (EHRs), but computable phenotype definitions, in the form of code sets or code lists, are required to extract structured data from these large routine databases in a systematic and reproducible way. The aim of this protocol is to specify a systematic review to identify code sets for respiratory symptoms in EHRs research. Methods and analysis: MEDLINE and Embase databases will be searched using terms relating to EHRs, respiratory symptoms and use of code sets. The search will cover all English-language studies in these databases between January 1990 and December 2017. Two reviewers will independently screen identified studies for inclusion, and key data will be extracted into a uniform table, facilitating cross-comparison of codes used. Disagreements between the reviewers will be adjudicated by a third reviewer. This protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. Ethics and dissemination: As a review of previously published studies, no ethical approval is required. The results of this review will be submitted to a peer-reviewed journal for publication and can be used in future research into respiratory symptoms that uses electronic healthcare databases. PROSPERO registration number: CRD42018100830.