Evaluation of a Novel Goals-of-Care Discussion Priming Tool (MyCare) in Inpatient General Internal Medicine Ward Settings: Feasibility, Acceptability, and Usability Study
Notice bibliographique
Résumé
BACKGROUND: For patients who are seriously ill, conversations about prognosis, values, and goals can improve person-centered care; however, these conversations do not occur consistently. OBJECTIVE: We aimed to develop an online, interactive goals-of-care discussion priming tool called MyCare to facilitate conversations about patient goals among physicians, patients, and family members. Our objective was to determine the feasibility, acceptability, and usability of MyCare for patients who are seriously ill in hospitals. METHODS: We conducted a mixed methods study on internal medicine wards with patients who were seriously ill at 2 hospitals. Participants completed MyCare with a research assistant in their hospital room, and their responses were sent to their attending physician team. Patients, family members, and physicians participated in semistructured interviews to assess advance care planning engagement, usability, and acceptability. Patients also completed the System Usability Scale, the eHealth literacy scale, and survey questions about acceptability. RESULTS: Patients took a median time of 32 (IQR 21-43) minutes to complete MyCare, with a range of 12 to 101 minutes. The mean eHealth literacy score was 56 out of 100. In total, 19 (76%) out of 25 patients indicated that MyCare helped them think about and understand what was most important to them, and 16 (64%) stated that MyCare helped them think about the type of care they would want if their illness progressed. The mean advance care planning engagement scores on a 5-point scale before and after MyCare were 4.11 (SD 0.77) and 4.20 (SD 0.74), respectively (mean difference 0.09, 95% CI -0.08 to 0.34; P=.22). After completing MyCare, 16% (4/25) of the patients reported feeling more prepared to talk to their medical decision-maker about the type of care they would want if they were very sick or near the end of life, and none felt less prepared. The most useful elements for patients were (1) clarifying goals and wishes for care, (2) identifying people who supported them, and (3) having a resource to facilitate conversations with their families. The most useful elements for physicians were patients' prioritized values and goals. CONCLUSIONS: MyCare and similar tools will be more usable and acceptable if they are short and simple, focus on shared physician-patient priorities, and empower patients to advocate for their own goals.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».