Acceptability and Reliability of a Novel Palliative Care Screening Tool Among Emergency Department Providers
Notice bibliographique
Résumé
BACKGROUND: The Palliative Care and Rapid Emergency Screening (P-CaRES) Project is an initiative intended to improve access to palliative care (PC) among emergency department (ED) patients with life-limiting illness by facilitating early referral for inpatient PC consultations. In the previous two phases of this project, we derived and validated a novel PC screening tool. This paper reports on the third and final preimplementation phase. OBJECTIVES: Examine the acceptability of the P-CaRES tool among PC and ED providers as well as test its reliability on case vignettes. Compare variations in reliability and acceptability of the tool based on ED providers' roles (attendings, residents, and nurses) and lengths of experience. METHODS: A two-part electronic survey was distributed to ED providers at multiple sites across the United States. We tested the reliability of the tool in the first part of the survey, through a series of case vignettes. A criterion standard of correct responses was first defined by consensus input from expert PC physicians' interpretations of the vignettes. The experts' input was validated using the Gwet's AC1 coefficient for inter-rater reliability. ED providers were then presented with the case vignettes and asked to use the P-CaRES tool to correctly identify which patients had unmet PC needs. ED provider responses were compared both against the criterion standard and against different subsets of respondents (divided both by role and by level of experience). The second part of the survey assessed acceptability of the P-CaRES tool among ED providers using responses to questions from a modified Ottawa Acceptability of Decision Rules Instrument, based on a 1-5 Likert rating scale. Descriptive statistics were used to report all outcomes. RESULTS: In total, 213 ED providers employed in three different regions across the country responded to the survey (39.4%) and 185 (86.9%) of those completed it. The majority of providers felt that the tool would be useful in their practice (80.5%), agreed that the tool was clear and unambiguous (87.1%), thought that use of the tool would likely benefit patients (87.5%), and thought that it would result in improved use of resources to help severely ill patients (83.6%). Over three-quarters of ED providers (78.5%) also self-reported that they refer patients with unmet PC needs less than 10% of the time, and only 10.8% of respondents believed that they are already utilizing an effective strategy to screen or refer patients to PC. Applying our P-CaRES tool to case vignettes, ED providers generated PC referrals in concordance with PC experts over 88.7% of the time (95% confidence interval = 86.4% to 90.6%), with an overall sensitivity of more than 90%. These results varied minimally regardless of the respondent's role in the ED or their level of experience. CONCLUSION: Screening by emergency medicine providers for unmet PC needs using a brief, novel, content-validated screening tool is acceptable and is also reliable when applied to case vignettes-regardless of provider role or experience. Clinical trial and further study are warranted and are currently under way.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,046 | 0,124 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».