Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities.

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Background Despite increasing popularity among health organizations of pay for performance (P4P) for the provision of comprehensive care for chronic non-communicable diseases, evidence of its effectiveness in improving health system outcomes is weak. An important void in the evidence base is whether there are gendered differences in P4P uptake and in related outcomes amenable to healthcare improvement. This study assesses the gender-specific effects of P4P among family physicians on diabetes healthcare costs in a context of universal health coverage. Methods We use population-based linked longitudinal administrative datasets on chronic disease cases, physician billings, hospital discharge abstracts, and physician and resident registries in the province of New Brunswick, Canada. We estimate the effects of introduction of a P4P scheme on excess public healthcare costs among cohorts of adult diabetes patients using propensity score-adjusted difference-in-differences regressions stratified by physician’s gender. Results We observed greater male physician uptake of incentive payments, seemingly exacerbating gender gaps in professional remuneration. Regression results indicated P4P did not lead to improved outcomes in terms of preventing hospitalization costs among patients, only measurable increases in compensation for both the male and female physician workforce. Conclusions While P4P was not attributed in this study to reduced hospital burden and enhanced sustainability of healthcare financing, incentive payments were found to be related to earning gaps by physician’s gender. Decision-makers should consider that benefits of P4P be monitored not only for patient metrics but also for provider metrics in terms of gender equality especially given feminization of primary care medical workforces.

A collaborative between the Government of New Brunswick (GNB) and the University of New Brunswick to establish a center of public sector administrative data and policy research was envisioned in 2012. Subsequent work between the parties led to the establishment of the New Brunswick Institute for Research, Data and Training (NB-IRDT) in 2014. Academia-government partnerships are not unique in Canada, however what sets this apart is: 1) the legislative approach used to support research, 2) scope of administrative data made available, 3) value placed on anonymized linked data, 4) governance overseeing the partnership, and 5) measures taken to ensure the protection of citizens’ data. In 2017, the New Brunswick Act Respecting Research received proclamation. This Act serves to provide clarity and addresses gaps in access and use of personal / health data for research. The Act has opened the doors for NB-IRDT with data owners of public sector organizations. NB-IRDT may now receive pseudonymous personal data from any public sector program collecting personal information. The partnership is governed by several advisory committees each serving a different role in overseeing the growth of NB-IRDT; overall direction setting being led by a panel of Deputy Ministers and the Clerk (the senior ranking civil servant in GNB.) The collaboration is well positioned to support public policy research and fosters the use of evidence-based information in the development of government programs and services. The partnership has also helped to encourage new and innovative thinking within GNB about the value of linkable data to support decision-making.

Introduction Health insurance registries, which capture insurance coverage and demographic information for entire populations, are a critical component of population health surveillance and research when using administrative data. Lack of standardization of registry information across Canada’s provinces and territories could affect the comparability of surveillance measures. We assessed the contents of health insurance registries across Canada to describe the populations covered and document registry similarities and differences. Methods A survey about the data and population identifiers in health insurance registries was developed by the study team and representatives from the Public Health Agency of Canada. The survey was completed by key informants from most provinces and territories and then descriptively analyzed. Results Responses were received from all provinces; partial responses were received from the Northwest Territories. Demographic information in health insurance registries, such as primary address, date of birth and sex, were captured in all jurisdictions. Data captured on familial relationships, ethnicity and socioeconomic status varied among jurisdictions, as did start and end dates of coverage and frequency of registry updates. Identifiers for specific populations, such as First Nations individuals, were captured in some, but not all jurisdictions. Conclusion Health insurance registries are a rich source of information about the insured populations of the provinces and territories. However, data heterogeneity may affect who is included and excluded in population surveillance estimates produced using administrative health data. Development of a harmonized data framework could support timely and comparable population health research and surveillance results from multi-jurisdiction studies.