Comprehensive review of the evidence regarding the effectiveness of community–based primary health care in improving maternal, neonatal and child health: 8. summary and recommendations of the Expert Panel
Notice bibliographique
Résumé
BACKGROUND: The contributions that community-based primary health care (CBPHC) and engaging with communities as valued partners can make to the improvement of maternal, neonatal and child health (MNCH) is not widely appreciated. This unfortunate reality is one of the reasons why so few priority countries failed to achieve the health-related Millennium Development Goals by 2015. This article provides a summary of a series of articles about the effectiveness of CBPHC in improving MNCH and offers recommendations from an Expert Panel for strengthening CBPHC that were formulated in 2008 and have been updated on the basis of more recent evidence. METHODS: An Expert Panel convened to guide the review of the effectiveness of community-based primary health care (CBPHC). The Expert Panel met in 2008 in New York City with senior UNICEF staff. In 2016, following the completion of the review, the Panel considered the review's findings and made recommendations. The review consisted of an analysis of 661 unique reports, including 583 peer-reviewed journal articles, 12 books/monographs, 4 book chapters, and 72 reports from the gray literature. The analysis consisted of 700 assessments since 39 were analyzed twice (once for an assessment of improvements in neonatal and/or child health and once for an assessment in maternal health). RESULTS: The Expert Panel recommends that CBPHC should be a priority for strengthening health systems, accelerating progress in achieving universal health coverage, and ending preventable child and maternal deaths. The Panel also recommends that expenditures for CBPHC be monitored against expenditures for primary health care facilities and hospitals and reflect the importance of CBPHC for averting mortality. Governments, government health programs, and NGOs should develop health systems that respect and value communities as full partners and work collaboratively with them in building and strengthening CBPHC programs - through engagement with planning, implementation (including the full use of community-level workers), and evaluation. CBPHC programs need to reach every community and household in order to achieve universal coverage of key evidence-based interventions that can be implemented in the community outside of health facilities and assure that those most in need are reached. CONCLUSIONS: Stronger CBPHC programs that foster community engagement/empowerment with the implementation of evidence-based interventions will be essential for achieving universal coverage of health services by 2030 (as called for by the Sustainable Development Goals recently adopted by the United Nations), ending preventable child and maternal deaths by 2030 (as called for by the World Health Organization, UNICEF, and many countries around the world), and eventually achieving Health for All as envisioned at the International Conference on Primary Health Care in 1978. Stronger CBPHC programs can also create entry points and synergies for expanding the coverage of family planning services as well as for accelerating progress in the detection and treatment of HIV/AIDS, tuberculosis, malaria, hypertension, and other chronic diseases. Continued strengthening of CBPHC programs based on rigorous ongoing operations research and evaluation will be required, and this evidence will be needed to guide national and international policies and programs.
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Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,068 | 0,108 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,008 | 0,010 |
| Bibliométrie | 0,012 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».