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Record W4401045533 · doi:10.1101/2024.07.26.24310500

Discussions about Goals of Care in the Emergency Department: a Qualitative Study of Emergency Physicians’ Opinions Using the Normalization Process Theory

2024· preprint· en· W4401045533 on OpenAlexaffabout
Fannie Péloquin, Émile Marmen, Véronique Gélinas, Ariane Plaisance, Maude Linteau, Audrey Nolet, Nathalie Germain, Patrick Archambault

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversité du Québec à RimouskiCentre intégré de santé et de services sociaux de Chaudière-AppalachesUniversité Laval
Fundersnot available
KeywordsEmergency departmentThematic analysisPsychologyPreventive actionQualitative researchMedical educationMedicineNursingComputer scienceSociology

Abstract

fetched live from OpenAlex

Abstract Purpose We explored emergency department (ED) physicians’ opinions about the feasibility of leading goals of care discussions (GCD) in their daily practice. Method This qualitative study was based on the Normalization Process Theory (NPT). We conducted semi-structured interviews between April and May 2018 with a convenience sample of ten emergency physicians from one academic ED (Lévis, Canada) and aimed to reach data saturation. Using a mixed deductive and inductive thematic analysis, two authors codified the interviews under the four NPT constructs: coherence, cognitive participation, collective action, and reflexive monitoring. We calculated a kappa statistic to measure inter-rater agreement. Results We interviewed 10 emergency physicians. No new ideas emerged after the ninth interview and the inter-rater agreement was substantial. Fourteen themes were identified as factors influencing the feasibility of implementing GCD: (1) interpersonal communication, (2) efficiency of care, (3) anxiety generated by the discussion, (4) identification of an acute deterioration leading to the GCD, (5) meeting of the clinician, patient, and family, (6) importance of knowing the patient’s goals of care before medical handover, (7) lack of training, (8) availability of protocols, (9) heterogeneous prioritization for leading GCD, (10) need to take action before patients consult in the ED, (11) need to develop education programs, (12) need for legislation, (13) need to improve the ED environment and human resources, and (14) selective systematization of GCD for patients. Conclusion Goals of care discussions are possible and essential with selected ED patients. Physicians identified outstanding needs to normalize GCD in their practice: education for both themselves and patients on the concept of GCD, legislative action for the systematization of GCD for patients, and proactive documentation of patients’ preferences pre-ED. Patient, clinician and system-level policy-making efforts remain necessary to address these needs and ensure the normalization of GCD in emergency physicians’ daily practice as suggested by clinical guidelines. Clinician’s capsule What is known about the topic? Goals of care discussions are important to provide care aligned with patients’ values and medical preferences. What did this study ask ? According to emergency physicians, are goals of care discussions feasible in the emergency department? What did this study find? Goals of care discussions are essential and possible if patient, clinician and system-level policymaking structured efforts are deployed. Why does this study matter to clinicians ? This study identified action items to improve the implementation and quality of goals of care discussions in the emergency department.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.049
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.016
Scholarly communication0.0050.007
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.136
GPT teacher head0.498
Teacher spread0.363 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2024
Admission routes2
Has abstractyes

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