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Enregistrement W2769151876 · doi:10.1186/s12913-017-2745-7

Urban-rural difference in satisfaction with primary healthcare services in Ghana

2017· article· en· W2769151876 sur OpenAlex

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Notice bibliographique

RevueBMC Health Services Research · 2017
Typearticle
Langueen
DomaineHealth Professions
ThématiquePatient Satisfaction in Healthcare
Établissements canadiensUniversity of OttawaGlobal Affairs Canada
Organismes subventionnairesnon disponible
Mots-clésHealth careHealth administrationMedicineNursing researchMilestoneDeveloping countryHealth informaticsHealth services researchRural areaPopulationSocioeconomic statusEnvironmental healthSocioeconomicsPublic healthNursingEconomic growthGeography

Résumé

récupéré en direct d'OpenAlex

Understanding regional variation in patient satisfaction about healthcare systems (PHCs) on the quality of services provided is instrumental to improving quality and developing a patient-centered healthcare system by making it more responsive especially to the cultural aspects of health demands of a population. Reaching to the innovative National Health Insurance Scheme (NHIS) in Ghana, surpassing several reforms in healthcare financing has been a milestone. However, the focus of NHIS is on the demand side of healthcare delivery. Studies focusing on the supply side of healthcare delivery, particularly the quality of service as perceived by the consumers are required. A growing number of studies have focused on regional differences of patient satisfaction in developed countries, however little research has been conducted concerning patient satisfaction in resource-poor settings like in Ghana. This study was therefore dedicated to examining the variation in satisfaction across rural and urban women in Ghana. Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS 2014). Participants were 3576 women aged between 15 and 49 years living in non-institutional settings in Ghana. Summary statistics in percentages was used to present respondents’ demographic, socioeconomic characteristics. Chi-square test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R 2. Statistical significance was set at p < 0.05. The findings in this study revealed that about 57.1% were satisfied with primary health care services. The urban and rural areas reported 57.6 and 56.6% respectively which showed no statistically significant difference (z = 0.64; p = 0.523; 95%CI: -0.022, 0.043). Bivariate analysis showed that region, highest level of education, wealth index and type of facility were significantly associated with location of residence (urban-rural areas). After adjusting for confounding variables using logistic regression, geographical location became a key factor of satisfaction with primary healthcare services by location of residence. In urban areas, respondents from Greater Accra had 64% increase in the level of satisfaction when compared to those in Western region (OR = 1.64; 95CI: 1.09–2.47), Upper East had 75% increase in satisfaction compared to Western region (OR = 1.75; 95%CI: 1.08–2.84), Northern had an estimated 44% reduction in satisfaction when compared to Western region (OR = 0.56; 95%CI: 0.34–0.92). However, rural areas in Central, Volta, Eastern, Ashanti, Brong Aghafo, Northern and Upper West region had 51, 81, 69, 46, 62, 75 and 61% reduction respectively in the level of satisfaction when compared to Western region. Patient satisfaction is an important indicator of health outcomes. Quality of care and measuring level of patient satisfaction has been found to be the most useful tool to predict utilization and compliance. In fact, satisfied patients are more likely than unsatisfied ones to continue using health care services. Our results suggest that policymakers need to better understand the determinants of satisfaction with the health system and how different socio-demographic groups perceive satisfaction with healthcare services so as to address health inequalities between urban and rural areas within the same country.

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.

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)0,005
score de la tête « metaresearch » (Gemma)0,000
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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,368
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,000
Communication savante0,0000,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,004
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 Opus0,144
Tête enseignante GPT0,497
Écart entre enseignants0,353 · 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