The institutional logic of integrated care: an ethnography of patient transitions
Bibliographic record
Abstract
Purpose The purpose of this paper is to use theories of institutional logics and institutional entrepreneurship to examine how and why macro-, meso-, and micro-level influences inter-relate in the implementation of integrated transitional care out of hospital in the English National Health Service. Design/methodology/approach The authors conducted an ethnographic case study of a hospital and surrounding services within a large urban centre in England. Specific methods included qualitative interviews with patients/caregivers, health/social care providers, and organizational leaders; observations of hospital transition planning meetings, community "hub" meetings, and other instances of transition planning; reviews of patient records; and analysis of key policy documents. Analysis was iterative and informed by theory on institutional logics and institutional entrepreneurship. Findings Organizational leaders at the meso-level of health and social care promoted a partnership logic of integrated care in response to conflicting institutional ideas found within a key macro-level policy enacted in 2003 (The Community Care (Delayed Discharges) Act). Through institutional entrepreneurship at the micro-level, the partnership logic became manifest in the form of relationship work among health and social care providers; they sought to build strong interpersonal relationships to enact more integrated transitional care. Originality/value This study has three key implications. First, efforts to promote integrated care should strategically include institutional entrepreneurs at the organizational and clinical levels. Second, integrated care initiatives should emphasize relationship-building among health and social care providers. Finally, theoretical development on institutional logics should further examine the role of interpersonal relationships in facilitating the "spread" of logics between macro-, meso-, and micro-level influences on inter-organizational change.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".