Suchergebnisse

ObjectivesThis feasibility study was conducted to inform the design and power evaluation of CODE-MI, a pan-Canadian trial evaluating the impact of using the female-specific 99th-percentile threshold for high-sensitivity cardiac troponin (hs-cTn) on the diagnosis, treatment and outcomes of women presenting to the emergency department with symptoms suggestive for myocardial ischemia.
ApproachCODE-MI is a multi-center, stepped-wedge cluster randomized trial. The cohort and outcomes will be obtained from routinely collected administrative data. Using linked administrative data from 11 hospitals in Ontario from 2014/10 to 2017/09, this feasibility study obtained the following estimates: number of eligible patients, i.e., women presenting to the emergency department with symptoms suggestive of myocardial ischemia and a 24-hour peak hs-cTn value within the female-specific and overall thresholds (i.e. primary cohort); the rate of the 1-year composite outcome of all-cause mortality, re-admission for non-fatal myocardial infarction, incident heart failure, or emergent/urgent coronary revascularization. Study power was evaluated via simulations.
ResultsOverall, 2,073,849 emergency department visits were assessed. Among women, chest pain (with or without cardiac features) and shortness of breath were the most common complaints associated with a diagnosis of acute coronary syndrome. An estimated 7.7% of women with these complaints are eligible for inclusion in the primary cohort. The rate of the 1-year outcome in the primary cohort varied significantly across hospitals with a median rate of 12.2% (95%CI: 7.9%-17.7%). With 30 hospitals, randomized at 5-month intervals in 5 steps, approximately 19,600 women are expected to be included in CODE-MI, resulting in >82% power to detect a 20% decrease in the odds of the primary outcome at a 0.05 significance level.
ConclusionRoutinely collected administrative health data serve as a rich and essential resource for conducting pragmatic trials assessing process change, such as CODE-MI. We demonstrated the strength of using linked administrative health data to guide the design of pragmatic clinical trials and accurately evaluate the study power.

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.