Primary care physician involvement during hospitalisation: a qualitative analysis of perspectives from frequently hospitalised patients
Bibliographic record
Abstract
OBJECTIVE: To explore frequently hospitalised patients' experiences and preferences related to primary care physician (PCP) involvement during hospitalisation across two care models. DESIGN: Qualitative study embedded within a randomised controlled trial. Semistructured interviews were conducted with patients. Transcripts were analysed using qualitative template analysis. SETTING: In the Comprehensive Care Programme (CCP) Study, in Illinois, USA, Medicare patients at increased risk of hospitalisation are randomly assigned to: (1) care by a CCP physician who serves as a PCP across both inpatient and outpatient settings or (2) care by a PCP as outpatient and by hospitalists as inpatients (standard care). PARTICIPANTS: Twelve standard care and 12 CCP patients were interviewed. RESULTS: Themes included: (1) Positive attitude towards PCP; (2) Longitudinal continuity with PCP valued; (3) Patient preference for PCP involvement in hospital care; (4) Potential for in-depth involvement of PCP during hospitalisation often unrealised (involvement rare in standard care; in CCP, frequent interaction with PCP fostered patient involvement in decision making); and (5) PCP collaboration with hospital-based providers frequently absent (no interaction for standard care patients; CCP patients emphasising PCP's role in interdisciplinary coordination). CONCLUSION: Frequently hospitalised patients value PCP involvement in the hospital setting. CCP patients highlighted how an established relationship with their PCP improved interdisciplinary coordination and engagement with decision making. Inpatient-outpatient relational continuity may be an important component of programmes for frequently hospitalised patients. Opportunities for enhancing PCP involvement during hospitalisation should be considered.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".