Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Dec 22:10:346.
doi: 10.1186/1472-6963-10-346.

Data linkage: a powerful research tool with potential problems

Megan A Bohensky  1 , Damien Jolley, Vijaya Sundararajan, Sue Evans, David V Pilcher, Ian Scott, Caroline A Brand
Affiliations

Data linkage: a powerful research tool with potential problems

Megan A Bohensky et al. BMC Health Serv Res. .

Abstract

Background: 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.

Methods: 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.

Results: 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).

Conclusion: 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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Flow diagram of included and excluded studies.
See this image and copyright information in PMC

References

    1. Institute of Medicine Committee on Quality of Health in America. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington DC: National Academies Press; 2001. pp. 1–337. - PubMed
    1. Canadian Institute for Health Information. Health Care In Canada 2004. Ottawa, CA: CIHI; 2004.
    1. The Bristol Royal Infirmary Inquiry. The Report of the Public Inquiry into children's heart surgery at the Bristol Royal Infirmary1984-1995. London, U.K. 2001.
    1. National Health and Hospitals Reform Commission (Australia). Australia. Dept. of Health and Ageing. A healthier future for all Australians final report June 2009. Canberra, A.C.T.: Dept. of Health and Ageing; 2009. - PubMed
    1. Winglee M, Valliant R, Scheuren F. A case study in record linkage. Survey Methodology. 2005;31(1):3–11.

Publication types

MeSH terms

LinkOut - more resources