Engaging primary care physicians in care coordination for patients with complex medical conditions.
Bibliographic record
Abstract
OBJECTIVE: To explore the dynamics of primary care physicians' (PCPs') engagement with the Seamless Care Optimizing the Patient Experience (SCOPE) project. DESIGN: Qualitative study using semistructured interviews. SETTING: Solo and small group primary care practices in urban Toronto, Ont. PARTICIPANTS: A total of 22 of the 29 SCOPE PCPs (75.8%) were interviewed 14 to 19 months after the initiation of SCOPE. METHODS: Qualitative semistructured interviews were conducted to examine influencing factors associated with PCPs' engagement in SCOPE. Transcripts were analyzed using a grounded theory-informed approach and key themes were identified. MAIN FINDINGS: The SCOPE project provided practical mechanisms through which PCPs could access information and connect with resources. Contextual and historical factors including strained relationships between hospital specialists and community PCPs and PCPs' feelings of responsibility, isolation, disconnection, and burnout influenced readiness to engage. Provision of clinically useful supports in a trusting, collaborative manner encouraged PCPs' engagement in newer, more collaborative ways of working. CONCLUSION: The SCOPE project provided an opportunity for PCPs to build meaningful relationships, reconnect to the broader health care system, and redefine their roles. For many PCPs, reestablishing connections reaffirmed their role in the system and enabled a more collaborative care model. Strategies for connecting community-based PCPs to the broader system need to consider contextual factors and the effects of new linkages and coordination on the identities and relationships of PCPs.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".