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Enregistrement W4388516723 · doi:10.1097/jhm-d-23-00214

Building Community for Greater Well-Being

2023· editorial· en· W4388516723 sur OpenAlexaboutno aff
Eric W. Ford

Notice bibliographique

RevueJournal of Healthcare Management · 2023
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueHealth Policy Implementation Science
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPublishingHealth carePublic relationsPsychologyMedical educationSociologyPolitical scienceMedicine

Résumé

récupéré en direct d'OpenAlex

The self-help movement has grown dramatically over recent decades. Recently, the notion that any individual can care for themself without community support has been thoroughly debunked. Creating community has both serendipitous and purposeful components. To make the point at the Journal of Healthcare Management (JHM), we decided to engage in some purposeful community-building with the Canadian College of Health Leaders and its journal, Healthcare Management Forum (HMF). The final issues for 2023 of both HMF and JHM are dedicated to behavioral health. Both are publishing new original research that looks at the behavioral health of caregivers as well as patients and their communities. Planning for this special collaboration began last year when the journals posted a joint call for papers. The subsequent submissions underwent the same peer-review process that both journals typically rely upon to ensure scientific rigor. In addition, each journal is presenting a free webinar highlighting a research article published in the other journal. JHM readers will be treated to a discussion of the impact of physician leadership development on behavior and work-related changes from the November issue of HMF. Look for a detailed announcement in ACHe-news. Given the large number of submissions received and the great interest in behavioral health issues among readers, JHM will highlight additional research on the topic in 2024. With all that noted, it's on to the issue at hand. ... IN THIS ISSUE Beyond the research articles, JHM's regular healthcare leader interview and feature column also present diverse perspectives on behavioral health. The interview is with Wayne Young, FACHE, CEO of The Harris Center for Mental Health and IDD in Houston, Texas. Young is leading a remarkable organization that is taking on some of the toughest healthcare issues in one of America's most diverse and expansive communities. Battling endemic substance addictions and other behavioral health challenges on this scale is a Herculean task. The success of The Harris Center's innovative healthcare-centered approach to law enforcement calls associated with mental health is remarkable. Guest contributor Melinda L. Estes, MD, president and CEO of Saint Luke's Health System in Kansas City, Missouri, provides the feature column. Dr. Estes addresses the topic of childhood trauma and its pernicious, persistent impact on society. As the leader of Saint Luke's trailblazing Crittenton Children's Center, Dr. Estes outlines steps to stem the crisis and make the U.S. healthcare system more efficacious in those efforts. The first empirical research article comes from Jeffrey Glenn, DrPH, Danica Gibson, and Heather F. Thiesset, PhD. They asked physicians whether the electronic health record (EHR) helps in avoiding opioid misuse and addiction through enhanced decision support. Their results beg some important questions if, as they reveal, the EHR is helping only 34% of physicians prevent opioid misuse and addiction. The next article describes Mayo Clinic's employee assistance program (EAP). Gregory P. Couser, MD, Jody L. Nation, Dennis P. Apker, PhD, Susan M. Connaughty, and Mark A. Hyde, share their organization's experiences with the EAP implementation and its features. The researchers also recommend ways for other health systems to effectively identify and troubleshoot employee relational issues and allow for customized initiatives to improve mental health through an EAP. Hospitalization is one of the most stressful developments a family can experience. As a result, both the distressed patient and their family members can sometimes create an environment that is unacceptable and dangerous for all concerned. The Johns Hopkins research team of Jennifer M. Katzenstein, PhD, ABPP-CN, Sondra L. Boatman, RN, CNL, CPN, Kevin Newman, RN, CPHRM, CPPS, and Kristin Maier, CPXP, CCLS, describes the implementation of a behavior intervention response team. The program dramatically reduced harmful behaviors. The final article comes from my colleagues at The University of Alabama at Birmingham: Laurence M. Boitet, PhD, Katherine A. Meese, PhD, Megan Hays, PhD, C. Allen Gorman, PhD, Katie Sweeney, and David A. Rogers, MD. They explore the impact of COVID-19 on healthcare workers. Many of their study's subjects reported compassion fatigue, moral distress, and burnout leading to posttraumatic stress symptoms. The magnitude of the problem is staggering, if not surprising. The findings presented here support the development of trauma-informed leadership strategies. This issue of JHM also includes two abstracts from ACHE's 2023 Forum on Advances in Healthcare Management Research, which was held during the Congress on Healthcare Leadership. Featured contributors are Emily Bonazelli, DHA, Lihua Dishman, DBA, FACHE, and John Fick, EdD, FACHE, of A.T. Still University (exploring executive leadership competencies and value-based organizational performance), and Stephen B. Williams, MD, Peter McCaffrey, PhD, David Reynoso, MD, Phillip Keiser, MD, Rick Trevino, John Heymann, MD, Gulshan Doulatram, MD, Abe DeAnda, MD, Timothy J. Harlin, PhD, and Gulshan Sharma, MD, of The University of Texas Medical Branch (promoting the implementation and dissemination of a high-value care program). Eric W. Ford, PhD Editor

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,022
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
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 enseignants0,022
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0220,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,005
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,415
Tête enseignante GPT0,654
Écart entre enseignants0,239 · 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 tête enseignante, pas un consensus.

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
Publié2023
Routes d'admission1
Résumé présentoui

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