Data Linkage: A powerful research tool with potential problems
Open Access
- 22 December 2010
- journal article
- Published by Springer Science and Business Media LLC in BMC Health Services Research
- Vol. 10 (1), 346
- https://doi.org/10.1186/1472-6963-10-346
Abstract
Policy makers, clinicians and researchers are demonstrating increasing interest in using data linked from multiple sources to support measurement of clinical performance and patient health outcomes. However, the utility of data linkage may be compromised by sub-optimal or incomplete linkage, leading to systematic bias. In this study, we synthesize the evidence identifying participant or population characteristics that can influence the validity and completeness of data linkage and may be associated with systematic bias in reported outcomes. A narrative review, using structured search methods was undertaken. Key words "data linkage" and Mesh term "medical record linkage" were applied to Medline, EMBASE and CINAHL databases between 1991 and 2007. Abstract inclusion criteria were; the article attempted an empirical evaluation of methodological issues relating to data linkage and reported on patient characteristics, the study design included analysis of matched versus unmatched records, and the report was in English. Included articles were grouped thematically according to patient characteristics that were compared between matched and unmatched records. The search identified 1810 articles of which 33 (1.8%) met inclusion criteria. There was marked heterogeneity in study methods and factors investigated. Characteristics that were unevenly distributed among matched and unmatched records were; age (72% of studies), sex (50% of studies), race (64% of studies), geographical/hospital site (93% of studies), socio-economic status (82% of studies) and health status (72% of studies). A number of relevant patient or population factors may be associated with incomplete data linkage resulting in systematic bias in reported clinical outcomes. Readers should consider these factors in interpreting the reported results of data linkage studies.Keywords
This publication has 54 references indexed in Scilit:
- A survey of Australian clinical registries: can quality of care be measured?Internal Medicine Journal, 2011
- Measuring the accuracy and completeness of linking certificates for deliveries to the same womanPaediatric and Perinatal Epidemiology, 2007
- Repeat adverse drug reactions causing hospitalization in older Australians: a population‐based longitudinal study 1980–2003British Journal of Clinical Pharmacology, 2006
- Cross sectional survey of multicentre clinical databases in the United KingdomBMJ, 2004
- Directory of clinical databases: improving and promoting their useQuality and Safety in Health Care, 2003
- Linking Birth Certificates with Medicaid Data To Enhance Population Health AssessmentJournal of Public Health Management and Practice, 2002
- Health services research using linked records: who consents and what is the gain?Australian and New Zealand Journal of Public Health, 2001
- Health services research using linked records: who consents and what is the gain?Australian and New Zealand Journal of Public Health, 2001
- Investigation of bias after data linkage of hospital admissions data to police road traffic crash reportsInjury Prevention, 2001
- Client and Birth Record Linkage: A Method, Biases, and LessonsEvaluation Practice, 1996