A cognitive perspective on health systems integration: results of a Canadian Delphi study
Bibliographic record
Abstract
BACKGROUND: Ongoing challenges to healthcare integration point toward the need to move beyond structural and process issues. While we know what needs to be done to achieve integrated care, there is little that informs us as to how. We need to understand how diverse organizations and professionals develop shared knowledge and beliefs - that is, we need to generate knowledge about normative integration. We present a cognitive perspective on integration, based on shared mental model theory, that may enhance our understanding and ability to measure and influence normative integration. The aim of this paper is to validate and improve the Mental Models of Integrated Care (MMIC) Framework, which outlines important knowledge and beliefs whose convergence or divergence across stakeholder groups may influence inter-professional and inter-organizational relations. METHODS: We used a two-stage web-based modified Delphi process to test the MMIC Framework against expert opinion using a random sample of participants from Canada's National Symposium on Integrated Care. Respondents were asked to rate the framework's clarity, comprehensiveness, usefulness, and importance using seven-point ordinal scales. Spaces for open comments were provided. Descriptive statistics were used to describe the structured responses, while open comments were coded and categorized using thematic analysis. The Kruskall-Wallis test was used to examine cross-group agreement by level of integration experience, current workplace, and current role. RESULTS: In the first round, 90 individuals responded (52% response rate), representing a wide range of professional roles and organization types from across the continuum of care. In the second round, 68 individuals responded (75.6% response rate). The quantitative and qualitative feedback from experts was used to revise the framework. The re-named "Integration Mindsets Framework" consists of a Strategy Mental Model and a Relationships Mental Model, comprising a total of nineteen content areas. CONCLUSIONS: The Integration Mindsets Framework draws the attention of researchers and practitioners to how various stakeholders think about and conceptualize integration. A cognitive approach to understanding and measuring normative integration complements dominant cultural approaches and allows for more fine-grained analyses. The framework can be used by managers and leaders to facilitate the interpretation, planning, implementation, management and evaluation of integration initiatives.
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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 | 0.036 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".