Ontario primary care reform and quality improvement activities: an environmental scan
Bibliographic record
Abstract
BACKGROUND: Quality improvement is attracting the attention of the primary health care system as a means by which to achieve higher quality patient care. Ontario, Canada has demonstrated leadership in terms of its improvement in healthcare, but the province lacks a structured framework by which it can consistently evaluate its quality improvement initiatives specific to the primary healthcare system. The intent of this research was to complete an environmental scan and capacity map of quality improvement activities being built in and by the primary healthcare sector (QI-PHC) in Ontario as a first step to developing a coordinated and sustainable framework of primary healthcare for the province. METHODS: Data were collected between January and July 2011 in collaboration with an advisory group of stakeholder representatives and quality improvement leaders in primary health care. Twenty participants were interviewed by telephone, followed by review of relevant websites and documents identified in the interviews. Data were systematically examined using Framework Analysis augmented by Prior's approach to document analysis in an iterative process. RESULTS: The environmental scan identified many activities (n=43) designed to strategically build QI-PHC capacity, identify promising QI-PHC practices and outcomes, scale up quality improvement-informed primary healthcare practice changes, and make quality improvement a core organizational strategy in health care delivery, which were grouped into clusters. Cluster 1 was composed of initiatives in the form of on-going programs that deliberately incorporated long-term quality improvement capacity building through province-wide reach. Cluster 2 represented activities that were time-limited (research, pilot, or demonstration projects) with the primary aim of research production. The activities of most primary health care practitioners, managers, stakeholder organizations and researchers involved in this scan demonstrated a shared vision of QI-PHC in Ontario. However, this vision was not necessarily collaboratively developed nor were activities necessarily strategically linked. CONCLUSIONS: Within the scope of this research, the scan affirmed that there is currently no province-wide, integrated, and measured quality improvement program for the primary healthcare sector in Ontario. This could be improved by the development of a coordinated plan, an accompanying accountability framework, and an appropriate sustainable funding envelope for QI-PHC at the provincial level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.023 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".