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Enregistrement W4293792767 · doi:10.1097/acm.0000000000004823

Recognizing Rural Health Resource and Education Needs

2022· article· en· W4293792767 sur OpenAlexaboutno aff
Laura Weiss Roberts

Notice bibliographique

RevueAcademic Medicine · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Workforce Issues
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésResource (disambiguation)Rural healthMEDLINEMedical educationRural areaMedicineComputer sciencePolitical science

Résumé

récupéré en direct d'OpenAlex

When I teach, I love to tell the story of a patient I cared for years ago in Albuquerque, New Mexico. One morning, while serving on the consultation-liaison psychiatry service, I was called to the emergency room (ER) to evaluate a suicidal patient. The consult request read something like “Suicidal male; left ammo, pistols, and shotguns in truck; is he safe to go?” Being hugely pregnant with my second daughter, and feeling a little nervous, I waddled down to the ER. As I entered the room, I encountered a dignified older man holding an exquisite cowboy hat in his hands as he leaned forward to pray. He saw my round form and offered a blessing to my coming child. We sat down. We talked for a long, long time. Three weeks before, he had found a corpse on the ranch where he was caretaker. This grisly discovery triggered terrible memories and intrusive thoughts of his war experiences, long before, in Vietnam. He started drinking to cope with the terror, and he felt weak and broken. He was certain he would lose his job on the ranch and, in so doing, would lose his greatest sense of pride and source of standing in the community. My patient told me that he had spent the night before in a field on his ranch, planning to kill himself. But rather than ending his life, he had struggled each moment to shoot off every bit of ammunition he possessed into the sky. When dawn came, he drove more than 300 miles to our ER. It was clear that my patient wanted to live, and that he needed help with recent and past traumatic experiences. We worked out a plan for his care, and, yes, I could answer the consult question that it was OK for him to leave the hospital. As I was leaving the room, I turned and asked him, “Why did you drive hundreds of miles? There is a clinic down there—not too far from where you live.” He sat up a bit straighter in his chair, and he answered with a slight smile, “Oh, yes. We built that clinic.” But then he leaned back, looked down, and quietly said, “No. I can’t go to the clinic. My sister works there.” There are many lessons in even this one patient encounter, and I discover more with each telling. Perhaps the first point to emphasize is that this story of a struggling person from a rural area is unlikely to be unique, as recent data indicate that 45% of the global population (over 3 billion people) lives in rural areas or remote communities. 1 In the United States and in Canada, roughly 80% of the population is concentrated in urban areas, 1 even though urban areas make up less than 4% of the geography in those countries. 2,3 As was the case for my patient, individuals who reside in rural communities often have important health needs that may not be fully met, even when some local services exist. A second observation is that most health professions education institutions and health care systems are based in urban areas. Health professions students often do not receive training in settings that allow them to understand the distinct, sometimes unique, challenges for patients and clinicians in certain contexts, as reflected in my patient’s story of how the overlap of personal and professional roles can create an invisible barrier to necessary care in small communities. 4 Fortunately, some MD-granting and DO-granting medical schools have been established to help address these needs, and faculty and trainees in some academic programs have identified rural health as a priority. 5–7 Nevertheless, curricula of medical schools are often silent on the topic of culturally attuned care for patients who live in rural and frontier areas. 8 The co-location of health resources and larger population areas contributes to health disparities that are substantial and foreseeable. Rural Americans report traveling farther to access health care and are more likely to say that a lack of good doctors is a serious concern in their communities. 9 Hundreds of rural hospitals have closed in the United States since 2005 due to market factors, changes in payer mix, declining in-patient use, and other pressures. 10,11 In addition, workforce shortages of primary and specialist clinicians are common outside of urban areas. 12 As a result, health outcomes for certain infection-related illnesses, including COVID-19, and chronic conditions such as diabetes and stroke have been found to be worse for rural residents than for their urban counterparts. 13,14 With respect to mental health, across all rural counties in the United States in 2019, there were 590 psychiatrists serving 27 million people—approximately 2 psychiatrists available for every 100,000 people—with as few as 1 per 100,000 in the most underserved rural counties. 15 More mental health and addiction-related disparities inevitably arise as consequences, and rural communities in recent years have experienced heightened rates of suicide and opioid-related deaths. 16 Economic erosion, population instability, illness-related stigma, isolation, limited access to education resources, and cumulative trauma—all important social determinants of health—have hit many rural areas very hard. 17–19 Thus, rural people overall tend to have shorter life spans and innumerable instances of significant health challenges. 14,17 Moreover, individuals in rural areas who are members of racial or ethnic minority groups are especially likely to suffer from poor health. 18–20 Because many who live in rural and especially in frontier areas are older; younger; or ethnically, culturally, or racially distinct, the magnitude of health disparities through an intersectional lens is immense. These factors, taken together, contribute to the widening and worsening gap in rates of disability and premature mortality in rural communities. Clinicians, educators, and leaders in community-based health systems and academic medicine continue to develop innovative responses to address distinct rural health needs, as reflected in many articles that have appeared in our journal. 4–8,12,21–27 We should be inspired by the courage and creativity that exists among rural and frontier people, both in seeking to live their best lives and in working to address the health needs of those around them. Early in my career, I spent more than a decade as a resident, fellow, and faculty member at the one medical school in New Mexico, a remarkably innovative institution in a large and almost entirely rural state. 28–30 I also led a large project funded by the National Institutes of Health investigating health disparities experienced by people living in frontier areas of New Mexico and Alaska. Our project also documented the remarkable, creative efforts that have been undertaken to address the distinct health challenges that exist in rural communities. 31–45 Through this work, I learned about the immense need for more, and more accessible, health services in rural areas as well as for more rural-serving medical and other health professions education institutions. I will always carry with me the story of the patient who, during and after his night of despair, fought for his life. I will not forget the blessing he offered to my daughter. I extend my thanks to him, and to the others who taught me medicine, with gratitude that stretches as far as the eye can see.

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)0,002
score de la tête « metaresearch » (Gemma)0,008
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: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil0,086

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0050,002
Communication savante0,0030,003
Science ouverte0,0010,008
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0260,002

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 Opus0,067
Tête enseignante GPT0,470
Écart entre enseignants0,402 · 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
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

Citations5
Publié2022
Routes d'admission1
Résumé présentoui

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