Abstract
BackgroundPolicy 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.MethodsA 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. 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.ResultsThe 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).ConclusionA 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.
Highlights
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
The purpose of this study was to synthesize the evidence through a structured narrative review of patient or population characteristics that may be associated with changes in sensitivity and specificity of data linkage, thereby introducing systematic bias into reported outcomes
All articles were grouped thematically according to patient or population characteristics that were compared in matched and unmatched records
Summary
Clinicians and researchers are demonstrating increasing interest in using data linked from multiple sources to support measurement of clinical performance and patient health outcomes. A search by one of the authors (MAB) of the term “data linkage” and of the heading “medical record linkage” in study abstracts and titles on Medline identified only 161 studies between 1992 and 1997, compared to 951 studies between 2002 and 2007. This proliferation of data linkage is reflected in the establishment of data linkage research centres and initiatives in Australia [8,9], North America [10,11] and the United Kingdom [12,13]
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