Implementation of a Biopsychosocial History and Physical Exam Template in the Electronic Health Record: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Patients' perspectives and social contexts are critical for prevention of hospital readmissions; however, neither is routinely assessed using the traditional history and physical (H&P) examination nor commonly documented in the electronic health record (EHR). The H&P 360 is a revised H&P template that integrates routine assessment of patient perspectives and goals, mental health, and an expanded social history (behavioral health, social support, living environment and resources, function). Although the H&P 360 has shown promise in increasing psychosocial documentation in focused teaching contexts, its uptake and impact in routine clinical settings are unknown. OBJECTIVE: The aim of this study was to assess the feasibility, acceptability, and impact on care planning of implementing an inpatient H&P 360 template in the EHR for use by fourth-year medical students. METHODS: A mixed methods study design was used. Fourth-year medical students on internal medicine subinternship (subI) services were given a brief training on the H&P 360 and access to EHR-based H&P 360 templates. Students not working in the intensive care unit (ICU) were asked to use the templates at least once per call cycle, whereas use by ICU students was elective. An EHR query was used to identify all H&P 360 and traditional H&P admission notes authored by non-ICU students at University of Chicago (UC) Medicine. Of these notes, all H&P 360 notes and a sample of traditional H&P notes were reviewed by two researchers for the presence of H&P 360 domains and impact on patient care. A postcourse survey was administered to query all students for their perspectives on the H&P 360. RESULTS: Of the 13 non-ICU subIs at UC Medicine, 6 (46%) used the H&P 360 templates at least once, which accounted for 14%-92% of their authored admission notes (median 56%). Content analysis was performed with 45 H&P 360 notes and 54 traditional H&P notes. Psychosocial documentation across all H&P 360 domains (patient perspectives and goals, mental health, expanded social history elements) was more common in H&P 360 compared with traditional notes. Related to impact on patient care, H&P 360 notes more commonly identified needs (20% H&P 360; 9% H&P) and described interdisciplinary coordination (78% H&P 360; 41% H&P). Of the 11 subIs completing surveys, the vast majority (n=10, 91%) felt the H&P 360 helped them understand patient goals and improved the patient-provider relationship. Most students (n=8, 73%) felt the H&P 360 took an appropriate amount of time. CONCLUSIONS: Students who applied the H&P 360 using templated notes in the EHR found it feasible and helpful. These students wrote notes reflecting enhanced assessment of goals and perspectives for patient-engaged care and contextual factors important to preventing rehospitalization. Reasons some students did not use the templated H&P 360 should be examined in future studies. Uptake may be enhanced through earlier and repeated exposure and greater engagement by residents and attendings. Larger-scale implementation studies can help further elucidate the complexities of implementing nonbiomedical information within EHRs.
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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 | 0.040 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".