ArticleInternational journal of population data science2020
Development of comparable algorithms to measure primary care indicators using administrative health data across three Canadian provinces.
Article in International journal of population data science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of international performance indicators and metrics relevant to UK general practice.BMJ open quality · 2025Pooled it
- Association Between Team-Based Continuity of Care Measures and End-of-Life Health Care Outcomes: A Retrospective Cohort Study in Ontario, Canada.Medical care · 2026Article
- Exploring unregulated substance use health data in Ontario, Canada: Identifying gaps, addressing challenges, and uncovering opportunities.Frontiers in public health · 2025Article
- Primary care usage at the end of life: a retrospective cohort study of cancer patients using linked primary and hospital care data.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPerformance measurement has been recognized as key to transforming primary care (PC). Yet, performance reporting in PC lags behind even though high-performing PC is foundational to an effective and efficient health care system.
objectivesWe used administrative data from three Canadian provinces, British Columbia, Ontario and Nova Scotia, to: 1) identify and develop a core set of PC performance indicators using administrative data and 2) examine their ability to capture PC performance.
methodsAdministrative data used included Physician Billings, Discharge Abstract Database, the National Ambulatory Care and Reporting System database, Census and Vital Statistics. Indicators were compiled based on a literature review of PC indicators previously developed with administrative data available in Canada (n=158). We engaged in iterative discussions to assess data conformity, completeness, and plausibility of results in all jurisdictions. Challenges to creating comparable algorithms were examined through content analysis and research team discussions, which included clinicians, analysts, and health services researchers familiar with PC.
resultsOur final list included 21 PC performance indicators pertaining to 1) technical care (n=4), 2) continuity of care (n=6), and 3) health services utilization (n=11). Establishing comparable algorithms across provinces was possible though time intensive. A major challenge was inconsistent data elements. Ease of data access, and a deep understanding of the data and practice context, was essential for selecting the most appropriate data elements.
conclusionsThis project is unique in creating algorithms to measure PC performance across provinces. It was essential to balance internal validity of the indicators within a province and external validity across provinces. The intuitive desire of having the exact same coding across provinces was infeasible due to lack of standardized PC data. Rather, a context-tailored definition was developed for each jurisdiction. This work serves as an example for developing comparable PC performance indicators across different provincial/territorial jurisdictions.
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Registered trials
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