Abstract
BackgroundHealth administrative data is increasingly being used for chronic disease surveillance. This study explored agreement between administrative and survey data for ascertainment of seven key chronic diseases, using individually linked data from a large population of individuals in Ontario, Canada.MethodsAll adults who completed any one of three cycles of the Canadian Community Health Survey (2001, 2003 or 2005) and agreed to have their responses linked to provincial health administrative data were included. The sample population included 85,549 persons. Previously validated case definitions for myocardial infarction, asthma, diabetes, chronic lung disease, stroke, hypertension and congestive heart failure based on hospital and physician billing codes were used to identify cases in health administrative data and these were compared with self-report of each disease from the survey. Concordance was measured using the Kappa statistic, percent positive and negative agreement and prevalence estimates.ResultsAgreement using the Kappa statistic was good or very good (kappa range: 0.66-0.80) for diabetes and hypertension, moderate for myocardial infarction and asthma and poor or fair (kappa range: 0.29-0.36) for stroke, congestive heart failure and COPD. Prevalence was higher in health administrative data for all diseases except stroke and myocardial infarction. Health Utilities Index scores were higher for cases identified by health administrative data compared with self-reported data for some chronic diseases (acute myocardial infarction, stroke, heart failure), suggesting that administrative data may pick up less severe cases.ConclusionsIn the general population, discordance between self-report and administrative data was large for many chronic diseases, particularly disease with low prevalence, and differences were not easily explained by individual and disease characteristics.
Highlights
Health administrative data is increasingly being used for chronic disease surveillance
We found for some conditions cases identified by administrative data had higher median Health Utilities Index (HUI) scores compared with self-report cases across all diseases
Population based data is a powerful tool for chronic disease surveillance
Summary
Health administrative data is increasingly being used for chronic disease surveillance. This study explored agreement between administrative and survey data for ascertainment of seven key chronic diseases, using individually linked data from a large population of individuals in Ontario, Canada. While multiple data sources have been used to identify persons with chronic diseases— including population health surveys, disease registries, research using these data will depend on the identification, measurement of these errors, and correction or discussion of biased results. A few studies have explored the accuracy of administrative data compared with self-report of chronic conditions across chronic conditions [9,10] Agreement between these sources is higher for chronic diseases that are welldefined and require ongoing management, such as diabetes, and is lower for poorly defined diseases such as congestive heart failure [9,10]. Worsening comorbidity, measured by number of chronic conditions, appears to be associated with lower agreement— for those diseases where agreement is already poor [11,12]
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