Primary care provider perceptions of intake transition records and shared care with outpatient cardiac rehabilitation programs
Bibliographic record
Abstract
BACKGROUND: While it is recommended that records are kept between primary care providers (PCPs) and specialists during patient transitions from hospital to community care, this communication is not currently standardized. We aimed to assess the transmission of cardiac rehabilitation (CR) program intake transition records to PCPs and to explore PCPs' needs in communication with CR programs and for intake transition record content. METHOD: 144 PCPs of consenting enrollees from 8 regional and urban Ontario CR programs participated in this cross-sectional study. Intake transition records were tracked from the CR program to the PCP's office. Sixty-six PCPs participated in structured telephone interviews. RESULTS: Sixty-eight (47.6%) PCPs received a CR intake transition record. Fifty-eight (87.9%) PCPs desired intake transition records, with most wanting it transmitted via fax (n = 52, 78.8%). On a 5-point Likert scale, PCPs strongly agreed that the CR transition record met their needs for providing patient care (4.32 ± 0.61), with 48 (76.2%) reporting that it improved their management of patients' cardiac risk. PCPs rated the following elements as most important to include in an intake transition record: clinical status (4.67 ± 0.64), exercise test results (4.61 ± 0.52), and the proposed patient care plan (4.59 ± 0.71). CONCLUSIONS: Less than half of intake transition records are reaching PCPs, revealing a large gap in continuity of patient care. PCP responses should be used to develop an evidence-based intake transition record, and procedures should be implemented to ensure high-quality transitional care.
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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 | 0.007 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".