Primary Care Physician Engagement in Integrated Health System Transformation: A Case Study 
Bibliographic record
Abstract
Background: Primary care physician (PCP) engagement is essential in enhancing health system performance, efficacy and collaboration, however; limited research exists in terms of how PCPs are engaged in health system reform. Aims & Methods: Ontario is undergoing a healthcare transformation with the introduction of Ontario Health Teams (OHTs). OHTs provide a new way of organizing and delivering care that is more connected to patients in their local communities. In response to the need for a coordinated sector approach, a group of PCPs in Southwestern Ontario formed a primary care organization: London-Middlesex Primary Care Alliance (LMPCA). This grassroots organization aims to support unified PCP engagement within the health system reform. The aim of our study is to explore the development of the grassroots LMPCA organization and understand how physicians are engaged within the regional health system. The first phase of our study consisted of a literature review which identified that PCP engagement is critical to the success of OHTs. Using an integrated knowledge translation approach (i.e.: in collaboration with members of the LMPCA and Middlesex-London OHT), the second phase of our study involves a case study to explore the development of a regional primary care organization and physician engagement. We will use key informant interviews with physicians, nurse practitioners (NPs) and health care administrators to explore the LMPCA development and understand PCP engagement. The objectives of the overall study are to 1) plot key junctures in the development of the regional organization, 2) explore PCP engagement at local and regional levels and 3) discuss the barriers and facilitators to PCP engagement. Results: Despite PCP engagement being recognized as an important aspect of health systems integration, several barriers exist: ineffective communication within organizations, administrative and legal hurdles, remuneration and reimbursement and other local contextual factors. Results from our literature review indicate that greater levels of PCP engagement can lead to improved primary care performance and efficacy. Engagement in primary care settings has been facilitated both top-down and bottom-up; however, empirical evidence on bottom-up approaches is limited. Three over-arching themes were evident: lack of physician voice, insufficient renumeration, and unsuitable strategies. We anticipate that results of our interviews can provide recommendations to increase physician voice, compensate appropriately, suggest alternative strategies for PCP engagement and gain physician buy-in. Moreover, we expect our results to help shape the LMPCA and the Middlesex-London OHT with their physician engagement efforts within the region. Implications: Findings of our study will benefit researchers, PCPs, NPs, and health care administrators by highlighting barriers and recommendations to support and improve physician engagement efforts. The findings may encourage the international audience to use similar PCP engagement strategies within their organization. Next Steps: We will provide a rich narrative of the development of a grassroots primary care organization as well as an empirical example of PCP engagement in health system reform. We anticipate our results will describe effective strategies for engaging physicians and by extension, provide recommendations to improve organizational efficacy and patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".