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Enregistrement W4296185270 · doi:10.1002/emp2.12805

Invited Editorial: Patient perspectives of the climate of diversity, equity, and inclusion in the emergency department

2022· editorial· en· W4296185270 sur OpenAlexaff
Juan A. March, Sing‐Yi Feng, Elizabeth Donnelly

Notice bibliographique

RevueJournal of the American College of Emergency Physicians Open · 2022
Typeeditorial
Langueen
DomaineMedicine
ThématiqueEmergency and Acute Care Studies
Établissements canadiensUniversity of Windsor
Organismes subventionnairesnon disponible
Mots-clésEquity (law)Likert scaleEmergency departmentHealth careDescriptive statisticsCensusInclusion (mineral)PopulationPsychologyFamily medicineMedicineNursingSocial psychologyPolitical scienceStatistics

Résumé

récupéré en direct d'OpenAlex

As the "safety net" for US healthcare, emergency departments (EDs) provide critical healthcare access to a diverse group of patients regardless of insurance coverage or ability to pay.1 Yet, ED clinicians' implicit biases, which are similar to the levels in the general population, can influence their clinical decision making and the patients' perception of care.2 Because perception is reality, a patient's perception of their healthcare professional has a direct effect on medication compliance, willingness to communicate, and treatment adherence.2-6 Unfortunately, there is no published data on patient's perceptions of diversity, equity, and inclusion (DEI) in the ED. For these reasons, the study by Davuluri et al and its results are important. The cross-sectional survey by Davuluri et al describes patients' perspectives of the climate of DEI in the ED.1 The survey was developed by an interdisciplinary group of physicians, nurses, social workers, and so on. The survey consisted of 41 questions, largely organized into matrices and divided into the following 4 sections: care for specific patient populations, patient's care experiences and values, ED compared to other hospital system clinics and departments, and demographics. To minimize acquiesce bias, the authors intentionally combined positive and negative valence questions using a 5-point Likert-type scale. Analyses included descriptive statistics for all variables and continuous data as means with standard deviations and categorical data as counts and percentages. The survey was administered in a single urban ED with an annual census of 100,000 representing >60,000 unique patients. Of 1691 patients screened, 849 respondents were sampled. Demographics of the local population were similar to the survey results with 4.3% Latino/Hispanic, 10.1% White non-Hispanic, and 72.9% Black non-Hispanic. Only 0.82% (n = 7) of the surveys were completed in Spanish. The investigators found that most respondents reported that ED staff treated patients from all races equally and made patients feel accepted. Respondents identified that the ED staff's treatment of patients who are mentally ill (16.8%) or lower income (14.3%) as needing the most improvement. This is noteworthy because patients who were mentally ill were not surveyed, and this observation was made by other patients. A high percentage of patients (16.8%) in the study witnessed discrimination or harassment of ED staff by another patient. Harassment of healthcare professionals and ED staff is not a new finding, but to realize that patients are witnessing and perhaps being impacted by these events at such a high percentage is concerning.7-9 This finding illustrates a dynamic that is underexplored in EDs: how witnessed interactions between others may impact a patients' perception of their own care and may warrant further exploration. This study had numerous limitations, including convenience sampling and a novel survey administered in only 1 urban ED with a high percentage of underrepresented minorities. The authors did not comment on the percentage of ED staff who were also underrepresented minorities, and this may have affected the results. Although the survey was translated into Spanish, the research assistants did not speak Spanish, and this may have excluded a percentage of possible Hispanic respondents. Despite limitations, this study is one of the first to study patients' perception of DEI in the ED. The old saying that perception is reality holds true, and thus patients' perceptions of DEI provide important insights that could help guide strategic initiatives to improving future healthcare for subgroups of ED patients. This study could serve as part of a model for the ongoing assessment in other EDs. As patient populations are fluid, these perceptions may change over time, and as such, an approach to measurement that includes patient perceptions may allow for a broad understanding of the ways in which DEI is perceived and where there may be room for improvement. Another strength in this study is the acknowledgment by the authors that these patient/professional interactions are occurring in the context of systemic pressures, both within the context of the global structural oppression of minorities in Western society and within the structural pressure of an overburdened ED system. Systems that are dealing with pressures such as overcrowding force providers to deliver care in deeply suboptimal ways. Acknowledging the impact of the environment and how it may influence these patient experiences is important as it frames these issues within the context in which they are happening and not solely as dependent on individual interactions. Clearly, future studies are needed to further examine patients' perceptions of DEI in suburban, rural, and other urban EDs and those with different patient demographics. Future research should include an assessment of the consequences of institutional stigma in EDs, including variations in patient outcomes according to various demographic indicators of DEI.

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)0,004
score de la tête « metaresearch » (Gemma)0,023
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,079

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,023
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,003
Communication savante0,0050,003
Science ouverte0,0050,001
Intégrité de la recherche0,0140,011
Charge utile insuffisante (le modèle a refusé de juger)0,0240,009

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 Opus0,020
Tête enseignante GPT0,335
Écart entre enseignants0,315 · 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'étudeSans objet
Domainenon disponible
GenreÉditorial

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

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