MétaCan
Menu
Retour à la cohorte
Enregistrement W4224237487 · doi:10.1111/acem.14510

Hot off the press: We care a lot: The <scp>EmPATH</scp> study

2022· article· en· W4224237487 sur OpenAlexaff
Kirsty Challen, Lauren M. Westafer, William K. Milne

Notice bibliographique

RevueAcademic Emergency Medicine · 2022
Typearticle
Langueen
DomainePsychology
ThématiqueHealthcare Decision-Making and Restraints
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésMedicineEmergency departmentReferralPsychological interventionMental healthUnit (ring theory)PsychiatryEmergency medicineMedical emergencyFamily medicine

Résumé

récupéré en direct d'OpenAlex

Over 8 million emergency department (ED) visits with psychiatric or substance use–related diagnoses occurred in the United States between 2007 and 2016.1 This may reflect difficulties in accessing urgent psychiatric care2 and is often associated with prolonged delays in transfer to inpatient psychiatric facilities.3 Various models of provision of psychiatric emergency care, including a centralized psychiatric assessment facility,4 a dedicated psychiatric ED,5 and community crisis interventions,6 have been shown to reduce inpatient psychiatric admissions and reduce ED boarding times. The EmPATH unit was established at the Department of Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, in October 2018. It provides stabilization and treatment for up to 12 patients from a team of psychiatrists, nurses, and social workers for 1 day to several days to include medication, referral for substance use disorders, and support with financial and housing problems. This article is a before (November 2017–May 2018) and after (November 2018–May 2019) assessment of the effect of establishing an EmPATH unit that provided care for up to 12 mental health patients at a single tertiary referral site in rural Iowa. The unit was staffed with psychiatrists, social workers, and nurses and patients had access to recliners, restrooms, laundry facilities, and a calming room. The authors assessed whether the establishment of the EmPATH unit was associated with a reduction in the proportion of patients admitted to inpatient psychiatric facilities (primary outcome) and altered ED boarding time, restraint use in ED, and 30-day ED returns (secondary outcomes). As a before-and-after design, this study has inherent limitations in that other factors that may influence outcomes such as changes in case mix, referral patterns, or other parts of the care system cannot be isolated from the effect of the studied intervention.7 However, the authors compared many important patient demographics (age, gender, race, homelessness, and insurance coverage) between the two groups and found no difference. They did not, however, compare rates of substance misuse or previous psychiatric diagnosis, which could potentially have changed the patient journey through care. The single-center setting of the study limits generalizability of the findings; as a tertiary referral unit with an annual census of 60,000 of predominantly White patients the University of Iowa Carver College may not be representative of other populations. As the senior author Dr. Lee said in discussion on the SGEM podcast, the establishment of the EmPATH unit required significant financial investment and buy-in from the psychiatric team and this would need to be considered by any clinicians expecting to replicate the unit. The authors included 435 patients in the pre-EmPATH stage and 527 in the post-EmPATH stage with a median age of 32 years and a near-even gender split. For the primary outcome of psychiatric admission, rates decreased from 248 (57%) to 144 (27%), resulting in a relative risk of 0.48 (95% confidence interval [CI] 0.40 to 0.56). Mean ED boarding time reduced from 16.2 to 4.9 h (95% CI −1.23 to −0.99), restraint use in ED was unchanged at 2.8% versus 3.8%, and 30-day ED returns reduced from 20% to 15% (relative risk 0.75, 95% CI 0.57 to 0.99). Joshua (@reverendofdoubt): We have one and it's amazing. Couldn't imagine not having one! Abhi “Searching for the Truth in the Universe” (@EMIMMD): We have created a virtual model of this and have recognized real outcomes in numerous outcomes. Suneel Uphadye (@SuneelUphadye): I have been fortunate to work in ER systems that have embedded emergency psych services for acute mental health crises… Vital and priceless service!! Establishment of the EmPATH unit was associated with fewer psychiatric admissions and a reduced ED boarding time in this unit in Iowa. Clinicians or administrators hoping to replicate this should consider how comparable their practice setting is to the site described here.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,033

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,010
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0020,005
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,101
Tête enseignante GPT0,430
Écart entre enseignants0,329 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueAcademic Emergency MedicineMême sujetHealthcare Decision-Making and RestraintsTravaux en français237 207