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Enregistrement W2896377317 · doi:10.1111/1468-0009.12349

How Equity‐Oriented Health Care Affects Health: Key Mechanisms and Implications for Primary Health Care Practice and Policy

2018· article· en· W2896377317 sur OpenAlexafffund
Marilyn Ford‐Gilboe, C. Nadine Wathen, Colleen Varcoe, Carol P. Herbert, Beth Jackson, Josée G. Lavoie, Bernie Pauly, Nancy Perrin, Victoria Smye, Bruce Wallace, Sabrina T. Wong

Notice bibliographique

RevueMilbank Quarterly · 2018
Typearticle
Langueen
DomainePsychology
ThématiqueMigration, Health and Trauma
Établissements canadiensUniversity of VictoriaCarleton UniversityUniversity of British ColumbiaUniversity of ManitobaPublic Health Agency of CanadaWestern University
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésHealth equityHealth carePopulation healthHealth policyPsychological interventionMedicineEquity (law)NursingHealth promotionPublic healthContext (archaeology)Social determinants of healthHealth services researchInternational healthRace and healthPopulationEnvironmental healthPolitical scienceGeography

Résumé

récupéré en direct d'OpenAlex

Policy Points A consensus regarding the need to orient health systems to address inequities is emerging, with much of this discussion targeting population health interventions and indicators. We know less about applying these approaches to primary health care. This study empirically demonstrates that providing more equity-oriented health care (EOHC) in primary health care, including trauma- and violence-informed, culturally safe, and contextually tailored care, predicts improved health outcomes across time for people living in marginalizing conditions. This is achieved by enhancing patients' comfort and confidence in their care and their own confidence in preventing and managing health problems. This promising new evidence suggests that equity-oriented interventions at the point of care can begin to shift inequities in health outcomes for those with the greatest need. CONTEXT: Significant attention has been directed toward addressing health inequities at the population health and systems levels, yet little progress has been made in identifying approaches to reduce health inequities through clinical care, particularly in a primary health care context. Although the provision of equity-oriented health care (EOHC) is widely assumed to lead to improvements in patients' health outcomes, little empirical evidence supports this claim. To remedy this, we tested whether more EOHC predicts more positive patient health outcomes and identified selected mediators of this relationship. METHODS: Our analysis uses longitudinal data from 395 patients recruited from 4 primary health care clinics serving people living in marginalizing conditions. The participants completed 4 structured interviews composed of self-report measures and survey questions over a 2-year period. Using path analysis techniques, we tested a hypothesized model of the process through which patients' perceptions of EOHC led to improvements in self-reported health outcomes (quality of life, chronic pain disability, and posttraumatic stress [PTSD] and depressive symptoms), including particular covariates of health outcomes (age, gender, financial strain, experiences of discrimination). FINDINGS: Over a 24-month period, higher levels of EOHC predicted greater patient comfort and confidence in the health care patients received, leading to increased confidence to prevent and manage their health problems, which, in turn, improved health outcomes (depressive symptoms, PTSD symptoms, chronic pain, and quality of life). In addition, financial strain and experiences of discrimination had significant negative effects on all health outcomes. CONCLUSIONS: This study is among the first to demonstrate empirically that providing more EOHC predicts better patient health outcomes over time. At a policy level, this research supports investments in equity-focused organizational and provider-level processes in primary health care as a means of improving patients' health, particularly for those living in marginalizing conditions. Whether these results are robust in different patient groups and across a broader range of health care contexts requires further study.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,871
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,025
Tête enseignante GPT0,392
Écart entre enseignants0,367 · 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
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

Citations208
Publié2018
Routes d'admission2
Résumé présentoui

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