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Quality of administrative health databases in Canada: A scoping review

Publisher

CANADIAN PUBLIC HEALTH ASSOC
DOI: 10.17269/CJPH.107.5244

Keywords

Data linkage; administrative health database; diagnosis codes; validation studies; review study

Funding

  1. Manitoba Health Research Chair
  2. University of Saskatchewan Centennial Research Chair
  3. Alberta Innovate Health Solution

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OBJECTIVE: Administrative health databases are increasingly used to conduct population-based health research and surveillance; this has resulted in a corresponding growth in studies about their quality. Our objective was to describe the characteristics of published Canadian studies about administrative health database quality. METHODS: PubMed, Scopus, and Google Advanced were searched, along with websites of relevant organizations. English-language studies that evaluated the quality of one or more Canadian administrative health databases between 2004 and 2014 were selected for inclusion. Extracted information included data quality concepts and measures, year and type of publication, type of database, and geographic origin. SYNTHESIS: More than 3,000 publications were identified from the search. Twelve reports and 144 peer-reviewed papers were included. The majority (53.5%) of peer-review publications used databases from Ontario and Alberta, while 67% of the non-peer-review publications used data from multiple provinces/ territories. Almost all peer-reviewed papers (97.2%) were validation studies. Hospital discharge abstracts and physician billing claims were the most frequently validated databases. Approximately half of the publications (53.0%) validated case definitions and 37.7% focused on a chronic physical health condition. CONCLUSION: Gaps in the Canadian administrative data quality literature include a limited number of studies evaluating data from the Maritimes and across multiple jurisdictions, newer data sources, validating methods for identifying individuals with mental illness, and assessing the completeness and serviceability of the data. Data quality studies can aid researchers to understand the strengths and limitations of the data.

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