Suchergebnisse

OBJECTIVE: To determine physicians' reasons for and against participating in a primary care reform (PCR) pilot project, to identify demographic and practice characteristics associated with participation, to gauge physicians' satisfaction with implementation of the project, and to seek suggestions for change. DESIGN: Cross-sectional mailed survey using a self-administered questionnaire. SETTING: Family practices in Hamilton-Wentworth, Ont. PARTICIPANTS: Eighty-two of 107 (76.6%) physicians who participated in the pilot project and 101 of 150 (67.3% of a 60% random sample of the area's remaining generalist physicians) who chose not to participate. MAIN OUTCOME MEASURES: Physicians' primary and secondary motives for participating or not; comments on the pilot project; and subjects' demographic, professional, and practice characteristics. RESULTS: Despite their experience with capitation practice, after controlling for other factors, physicians from health service organizations were no more likely than their fee-for-service colleagues to join the pilot project. Those in large group practices were more likely to participate. Both participants and non-participants were concerned about disrupting call groups, burdening office staff, not having enough time, and whether the project's objectives were achievable. Other key findings were how few patients declined enrolment and how many physicians had unrealistic ideas about the demands of participation and the capabilities of currently available information technology. CONCLUSION: While many Hamilton-area physicians were eligible and willing to participate in a PCR pilot project, many were not. Our findings suggest that physicians and government should clarify their expectations for PCR and that we need to look for better ways to register patients and select information technology for PCR.

BACKGROUND: Older Canadians frequently migrate to warmer destinations for the winter season (snowbirds). Our aim was to examine the prevalence of migration to warmer destinations among Ontarians, and to compare the characteristics and use of health care services of snowbirds to those of older Ontarians who did not migrate for the winter. METHODS: We conducted a population-based analysis using health administrative databases from Ontario. We compiled 10 seasonal cohorts (2009/10 to 2018/19) of adults aged 65 or more who filled a travel supply of medications under the Ontario Drug Benefits program (snowbirds) between September and January (snowbird season). We calculated the seasonal prevalence of snowbirds per 100 Ontarians aged 65 or more. We matched each snowbird in the 2018/19 season to 2 nonsnowbirds on age and sex, and compared their characteristics and patterns of use of government-funded health care services. RESULTS: Over the 10-year period, 53 431 to 70 863 Ontarians aged 65 or more were identified as snowbirds (seasonal prevalence 2.6%–3.3%). Compared to nonsnowbirds, snowbirds were more likely to be recent migrants, live in higher-income neighbourhoods, have fewer comorbidities and make more visits to primary care physicians. From January to March 2019, snowbirds accessed government-funded health care services for a median of 0 days (interquartile range [IQR] 0–1 d), compared to 4 days (IQR 2–8 d) among nonsnowbirds. INTERPRETATION: About 3% of older Ontarians migrate to warmer destinations for the winter each season. Since few access health care services in Ontario from January to March, researchers are encouraged to consider the snowbird population and the impact of their absence on evaluations that assume continuous observation.

ObjectiveStewards of population-level data have an obligation to serve the public interest. As one such publicly funded data steward, our Public Advisory Council (PAC) co-led and determined the focus of an analysis project using population-level administrative health data. We describe our engagement strategies herein.
ApproachThe 20-member PAC was involved in each stage of the project, from research question formulation to knowledge translation planning over 18 months, consisting of 12 meetings with both large and smaller groups. Our approach to engagement applied the International Association for Public Participation's Framework as the foundation for an 'empowerment' level of engagement and adapted approaches from the James Lind Alliance and the 'Plan-Do-Study-Act' cycle.
ResultsThe PAC chose to focus their analysis project on factors related to mental health and addiction service use. Four strategies were used and co-designed by members to foster engagement throughout: providing education and guidance, shared and guided brainstorming, building consensus, and responsiveness to feedback and evaluation. PAC members directed how and when these strategies were used, with challenges and lessons learned currently being co-developed into a publicly accessible report.
ConclusionsOur work demonstrates the importance and value of public-driven research outputs and the feasibility of integrating public members in the work of data stewards.
ImplicationsThe insights and practical strategies generated from this project will be used to guide effective engagement of the public for future analysis projects and to improve trust and social license for other initiatives using population-level data.

ObjectiveThere is growing recognition of the importance of community data governance to build accountability of research institutions to communities. Our organization, a steward of health and administrative population-level data, has previously implemented community governance structures for Indigenous data. This scoping initiative explores development and implementation of an additional community governance structure for race-related data.
ApproachWe conducted a scoping review of peer-reviewed and grey literature to identify existing practices of community data governance. We also conducted key informant interviews with thirteen racialized community stakeholders, who addressed open-ended questions on potential co-design processes as well as governance mandates, scopes, barriers, and facilitators.
ResultsThe scoping review identified eight community data governance examples. Two of these pertained to race-related data, while the remaining six pertained to other data that identified "community" geographically, by disease condition, life stage, and/or economic circumstance. Governance structures were diverse, ranging from one-time crowd-design of a data-sharing agreement to quarterly meetings of a governing board to review project-level data requests. Key informant interviews provided four themes to guide implementation in the context of our organization: exploring organizational readiness, considering who should be involved, defining the scope and mandate, and drafting an approach and process.
ConclusionWe are committed to implementing a community governance structure for race-related, population-level data. However, there are limited examples of similar structures in the existing literature.
ImplicationsThe identified examples and the advice of community stakeholders will guide co-design of a preliminary structure, scope, and mandate for community governance of race-related, population-level data.

ObjectiveTo provide an update on the key characteristics, refinements to project flow, and future opportunities for a program providing customized research evidence to health system policymakers and providers.
ApproachWith a goal to inform health system decision making, the program answers research questions posed by health system requestors that can be answered with linked, population-based administrative data. Now in its 10th year of operation, the program has been refined over time to improve efficiency, usefulness of research products, and requestor satisfaction. Satisfaction surveys and individual-level engagements with requestors are used to collect feedback on the needs of an increasingly diverse group of requests.
ResultsWith 508 requests, 82 Data Sharing Agreements, and 257 unique requestors since its inception, the program informs governmental decision making, evaluates intervention effectiveness, and aids grassroots organizations' planning for services. Notable updates to the program include, inserting multiple opportunities for connection between the program and requestors through the project life cycle to understand goals and needs; assigning staff scientists to shepherd projects and promote efficiency; training coordinators to review privacy impact assessments; and (soon) accepting a broader range of projects to include data beyond the health sector e.g. education.
ConclusionThis program continues to improve and is an exemplar of sustainable approaches to supporting health system requestors with evidence from administrative data in program evaluation, planning and policy change.
ImplicationsBeing responsive to requestor needs has allowed the program to attract an increasingly diverse range of requesters who can obtain impactful and timely research evidence.

IntroductionHealth care systems have faced unprecedented challenges due to the COVID-19 pandemic. Access to timely population-based data has been vital to informing public health policy and practice.
MethodsWe describe how ICES, an independent not-for-profit research and analytic institute in Ontario, Canada, pivoted existing research infrastructure and engaged health system stakeholders to provide near real-time population-based data and analytics to support Ontario's COVID-19 pandemic response.
ResultsSince April 2020, ICES provided the Ontario COVID-19 Provincial Command Table and public health partners with regular and ad hoc reports on SARS-CoV-2 testing and COVID-19 vaccine coverage. These reports: 1) helped identify congregate care/shared living settings that needed testing and prevention efforts early in the pandemic; 2) provided early indications of inequities in testing and infection in marginalized neighbourhoods, including areas with higher proportions of immigrants and visible minorities; 3) identified areas with high test positivity, which helped Public Health Units target and evaluate prevention efforts; and 4) contributed to altering the province's COVID-19 vaccine roll-out strategy to target high-risk neighbourhoods and helping Public Health Units and community organizations plan local vaccination programs. In addition, ICES is a key component of the Ontario Health Data Platform, which provides scientists with data access to conduct COVID-19 research and analyses.
Discussion and ConclusionICES was well-positioned to provide rapid analyses for decision-makers to respond to the evolving public health emergency, and continues to contribute to Ontario's pandemic response by providing timely, relevant reports to health system stakeholders and facilitating data access for externally-funded COVID-19 research.

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.