Dedman, D;
Cabecinha, M;
Williams, R;
Evans, SJW;
Bhaskaran, K;
Douglas, IJ;
(2020)
Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies.
BMJ Open
, 10
(10)
, Article e037405. 10.1136/bmjopen-2020-037405.
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Abstract
OBJECTIVE: To identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources. DESIGN: A systematic review of published studies. DATA SOURCES: Pubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening. STUDY SELECTION: Observational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases. RESULTS: 6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies. CONCLUSIONS: Comparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.
| Type: | Article |
|---|---|
| Title: | Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1136/bmjopen-2020-037405 |
| Publisher version: | https://doi.org/https://doi.org/10.1136/bmjopen-20... |
| Language: | English |
| Additional information: | This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
| Keywords: | epidemiology, public health, statistics & research methods |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10114741 |
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