Doing primary care integration: a qualitative study of meso-level collaborative practices
Bibliographic record
Abstract
BACKGROUND: The integration of Primary Care (PC) into broader health systems has been a goal in jurisdictions around the world. Efforts to achieve integration at the meso-level have drawn particular attention, but there are few actionable recommendations for how to enact a 'pro-integration culture' amongst government and PC governance bodies. This paper describes pragmatic integration activity undertaken by meso-level participants in Alberta, Canada, and suggests ways this activity may be generalizable to other health systems. METHODS: 11 semi-structured interviews with nine key informants from meso-level organizations were selected from a larger qualitative study examining healthcare policy development and implementation during the COVID-19 pandemic. Selected interviews focused on participants' experiences and efforts to 'do' integration as they responded to Alberta's first wave of the Omicron variant in September 2021. An interpretive descriptive approach was used to identify repeating cycles in the integration context, and pragmatic integration activities. RESULTS: As Omicron arrived in Alberta, integration and relations between meso-level PC and central health system participants were tense, but efforts to improve the situation were successfully made. In this context of cycling relationships, staffing changes made in reaction to exogenous shocks and political pressures were clear influences on integration. However, participants also engaged in specific behaviours that advanced a pro-integration culture. They did so by: signaling value through staffing and resource choices; speaking and enacting personal and group commitments to collaboration; persevering; and practicing bi-directional communication through formal and informal channels. CONCLUSIONS: Achieving PC integration involves not just the reactive work of responding to exogenous factors, but also the proactive work of enacting cultural, relationship, and communication behaviors. These behaviors may support integration regardless of the shocks, staff turnover, and relational freeze-thaw cycles experienced by any health system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".