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Record W4321447234 · doi:10.2196/42364

Implementation of a Biopsychosocial History and Physical Exam Template in the Electronic Health Record: Mixed Methods Study

2023· article· en· W4321447234 on OpenAlexvenueno aff
Erin Rieger, Irsk Anderson, Valerie G. Press, Michael Cui, Vineet M. Arora, Brent C. Williams, Joyce W. Tang

Bibliographic record

VenueJMIR Medical Education · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialBiopsychosocial modelDocumentationMedicineIntensive care unitHealth careElectronic health recordFamily medicinePsychologyMedical educationPsychiatryComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.473
Teacher spread0.441 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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