Andrea Gruneir1, Lauren E Griffith2, Kathryn Fisher3, Richard Perez4, Lindsay Favotto5, Christopher Patterson6, Maureen Markle-Reid7, Jenny Ploeg3, Ross Upshur8. 1. Department of Family Medicine, University of Alberta, Edmonton, Alberta, Canada; ICES, Toronto, Ontario, Canada; Women's College Research Institute, Women's College Hospital, Toronto, Ontario, Canada. Electronic address: gruneir@ualberta.ca. 2. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada. 3. School of Nursing, McMaster University, Hamilton, Ontario, Canada. 4. ICES McMaster, McMaster University, Hamilton, Ontario, Canada. 5. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; ICES McMaster, McMaster University, Hamilton, Ontario, Canada. 6. Department of Medicine, McMaster University, Hamilton, Ontario, Canada. 7. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; School of Nursing, McMaster University, Hamilton, Ontario, Canada. 8. Division of Clinical Public Health, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Bridgepoint Collaboratory for Research and Innovation, Sinai Health System, Toronto, Ontario, Canada.
Abstract
OBJECTIVE: The objective of this study is to describe agreement between administrative and self-report data on the number and type of chronic conditions (CCs) and determine whether associations between CC count and health service use differ by data source. STUDY DESIGN AND SETTING: We linked Canadian Community Health Survey and administrative data for a cohort of adults aged 45+ years in Ontario and identified 12 CCs from both data sources. Agreement was described by count and constituent CCs. We estimated associations between CC count (self-report and administrative data) and health service use (administrative data only) over 1 year. RESULTS: Among 71,317 adults, 26.9% showed agreement on both count and constituent CCs but agreement declined with increasing CCs. Health service use increased with CC count but the association was stronger when CCs were measured with administrative data. For example, when measured with administrative data, the odds of a general practitioner visit for 5+ CCs vs. none was 20.3 (95% CI 20.0-20.5) but when using self-report data, the estimate was 8.0 (95% CI 7.8-8.2). CONCLUSION: Agreement on the number of CCs was low and resulted in different estimates on the association with health service use, illustrating the challenges in CC measurement and the ability to interpret the effects on outcomes.
OBJECTIVE: The objective of this study is to describe agreement between administrative and self-report data on the number and type of chronic conditions (CCs) and determine whether associations between CC count and health service use differ by data source. STUDY DESIGN AND SETTING: We linked Canadian Community Health Survey and administrative data for a cohort of adults aged 45+ years in Ontario and identified 12 CCs from both data sources. Agreement was described by count and constituent CCs. We estimated associations between CC count (self-report and administrative data) and health service use (administrative data only) over 1 year. RESULTS: Among 71,317 adults, 26.9% showed agreement on both count and constituent CCs but agreement declined with increasing CCs. Health service use increased with CC count but the association was stronger when CCs were measured with administrative data. For example, when measured with administrative data, the odds of a general practitioner visit for 5+ CCs vs. none was 20.3 (95% CI 20.0-20.5) but when using self-report data, the estimate was 8.0 (95% CI 7.8-8.2). CONCLUSION: Agreement on the number of CCs was low and resulted in different estimates on the association with health service use, illustrating the challenges in CC measurement and the ability to interpret the effects on outcomes.
Keywords:
Canadian Community Health Survey; Health administrative data; Hospitalization; Multimorbidity; Multiple chronic conditions; Physician visits; Self-report data
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