A conceptual model for physician-system integration: A scoping review
Bibliographic record
Abstract
Despite the widespread pursuit of physician-health system integration, the evidence for factors affecting successful integration is uncertain and inconclusive. We sought to identify and categorize the organizational factors in the current landscape of physician-health system integration. We conducted a scoping review of the empirical literature on this topic, first surveying the theoretical perspectives that have been used in past studies in order to determine how theory has been used to explain and predict changing integration strategies over time. Second, we extracted factors that have been used to define the environment, physician group, hospital, care coordination, and health system success. From the 29 eligible articles, bargaining-market power theory and transaction cost theory were the predominant theories applied. We identified 48 organizational factors that comprise the landscape of physician-system integration. Our findings cumulated in a conceptual model that may help health care executives, policymakers, and researchers more effectively address the complexities of integration.
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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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.030 | 0.031 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".