Profiles of Community Care Sites and provider Community Health Workers: A Case study at Gombe Matadi, Kenge and Kisantu Rural Health Zones in the Democratic Republic of Congo
Notice bibliographique
Résumé
BACKGROUND: In sub-Saharan Africa, the DRC is ones of countries with high infant and child mortality. To solve this problem, the Ministry of Public Health has set up a new program: ICCM at the level of Community Care Sites managed by non-health professionals who are provider CHWs to serve Health Areas with difficult access. Since its implementation, there have not yet been many studies that concretely describe the functionality of CCS. To contribute to the extension of CCC in other Rural Health Zones, we conducted a study in 3 RHZ by choosing the Realistic Evaluation Approach to analyze the functionality of CCS in the DRC. METHODS: This is a cross-sectional study which is essentially a case study. Data were collected at the CCS level in these 3 RHZ chosen after multistage random sampling by mixed method (qualitative, quantitative). We used the following techniques: documentary review, direct observation at the CCS level, an in-depth interview with registered nurses and members of the health Zone management team and a survey using quantitative questionnaire with provider CHWs. The conceptual model that we developed is inspired by realist evaluation with an emphasis on Mechanisms. The relationship between the dependent variable (CCS functionality) and the independent variables was proven using Odds Ratio and Multiple Logistic Regression. RESULTS: CCS functionality and provider CHW profile were measured through the standards enacted for CCS implantation. At the significance level (p=0.05) has been in place for 3 years or more increases by 7 times chance that it is functional (OR = 6.7; p = 0.000). Has household been located less than 5 km from CCS increases by 4 times chance that the CCS is functional (OR = 7.04; p = 0.034). Has provider CHW is regularly trained and supervised increases by 10 times chance that the CCS is functional (OR = 10.01; p = 0.031). If provider CHW participate in Community cell animation meetings (OR = 4.34; p = 0.009) and CCS Management is done by CCS Management team increase by 4 times chance that this CCS is functional (OR = 3.6; p = 0.002). Finally, if there is an initiative for funding CCS increases by 8 times CCS functionality (OR = 8.69; p = 0.009). CONCLUSION: CCS are functional in the 3 RHZs. Their organization, establishment and operation are directly linked to the provision of services to populations living mainly in health areas with difficult access, the availability of inputs of three ICCM-C diseases management, namely uncomplicated malaria, diarrhoea and pneumonia as well as building provider community health workers capacity to ensure their management. This study shows an effective contribution of provider CHWs on CCS functionality in health areas with difficult access.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,010 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».