Identifying and Overcoming Policy‐Level Barriers to the Implementation of Digital Health Innovation in Ontario: Qualitative Study
Bibliographic record
Abstract
Research Objective Digital health innovation is the cornerstone of health care modernization internationally, yet innovations often fail to become part of routine practice. Translating evidence into practice remains a challenge despite the accumulating body of evidence regarding factors underlying success and failure. Innovations that establish proof of concept often lack a strategic plan for diffusion, which complicates adoption; however, high‐level policy barriers impede widespread adoption more broadly for even the most well‐positioned innovations. The aim of this study was to explore the challenges and opportunities in the implementation of digital health innovation to identify policy‐level actions to support uptake at scale. Study Design A qualitative study was conducted using a constructivist paradigm. Semi‐structured interviews were conducted with senior leadership members from organizations engaged in digital health planning and/or implementation activities in Ontario, Canada. Interviews were transcribed and analyzed inductively to the point of thematic saturation (point at which no new themes emerged). Findings are presented in terms of the key aspects of policy that require attention to best promote the adoption of digital health innovations at a system level. Population Studied The research team generated a list of key organizations involved in digital health activities in Ontario, Canada, which was circulated to a broader advisory group for further recommendations. Participants were required to hold a senior position within their respective organizations to ensure they could speak to system‐level barriers. Principal Findings Ten participants participated across nine interviews. Participants were from the Ontario Ministry of Health, Ontario Telemedicine Network, Canada Health Infoway, Ontario MD, and the MaRS Excellence in Clinical Innovation program and represented key organizations engaged in the governance, implementation, and adoption of digital health activities. The importance of strong leadership at an organizational and system level was viewed as critical to the successful implementation of digital health innovation, with an emphasis on establishing a culture of innovation. Participants described six key priorities requiring action at the policy level to catalyze digital health innovation, including: 1) a system‐level definition of innovation; 2) a clear overarching mission for digital health innovation; and 3) clearly defined organizational roles. Operationally, there is a need to 4) provide guidance on standardized processes; 5) shift the emphasis to change management; and 6) align funding structures. Conclusions Governments and decision makers play a central role in charting the digital course by developing a vision and creating the foundation upon which (currently fragmented) innovation activities will be modeled. Health care systems around the world and their stakeholders can reflect on these findings and recommendations to consider their utility in advancing local health innovation agendas. Implications for Policy or Practice These findings emphasize the critical role of the government in developing a shared vision and creating a foundation upon which digital health innovation activities can be implemented and adopted in health care systems. Achieving change may rely more on the thoughtful and efficient reconfiguration of existing practices as opposed to the addition of new resources. Primary Funding Source Ontario Ministry of Health Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".