Four-Year Educational and Patient Care Outcomes of a Team-Based Primary Care Longitudinal Clerkship
Bibliographic record
Abstract
BACKGROUND: Longitudinal clerkships show promise in improving undergraduate primary care education. This study examines the Education-Centered Medical Home (ECMH), a longitudinal clerkship embedding teams of students across all four years into primary care clinics to provide patient care and serve as health coaches for high-risk patients. METHOD: All students graduating in 2015 were surveyed to assess attitudes, experiences, and preferences regarding primary care education. ECMH students were compared with students receiving their primary care training in a traditional curriculum (TC) using paired measures of comparison. To assess the impact of the ECMH on patient care quality, authors performed a detailed chart review at one site. RESULTS: Seventy-six percent of eligible students participated in the study. ECMH students (n = 69) and TC students (n = 68) had similar baseline academic performance and career interests. ECMH students reported more continuity-of-care experiences, higher satisfaction with their primary care learning climate (86% versus 61% in the EMCH and TC cohorts, respectively), more confidence in their quality improvement skills, and scored higher on measures of perceived patient centeredness. Students from both groups recommended the ECMH (91% and 57%, respectively). Student involvement at one ECMH site was correlated with increased patient contacts and improved delivery of recommended preventive care. CONCLUSIONS: Incorporating students longitudinally into primary care clinics is highly rated by students. The ECMH model led to improved continuity, improved perceptions of the learning climate, and higher patient centeredness. Preliminary data suggest that students add value and improve patient outcomes during longitudinal clinical experiences.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".