Health facilities preparedness to deliver maternal and newborn health care in Kilifi and Kisii Counties, Kenya
Notice bibliographique
Résumé
Abstract Introduction: Health facility preparedness to deliver quality maternal and newborn care reduces maternal and newborn morbidity and mortality by avoiding the three delays (delay in deciding to seek care from a skilled attendant by pregnant woman; delay in reaching the facility with capacity to offer basic emergency obstetric care; and delay in receiving emergency care upon reaching a health facility). Rapid assessment and review of previous health records has shown that 16 health facilities in rural Kenya had poor maternal and newborn indicators. As a result, support was given to these facilities by providing basic emergency obstetric and newborn care (BEmONC) and comprehensive emergency obstetric and newborn care (CEmONC) training to providers, provision of equipment and supplies, and strengthening referral linkages. This study described the preparedness of the facilities to deliver maternal and newborn health care services at the end of the project implementation. Methods: A descriptive cross-sectional study was conducted in targeted rural counties of Kilifi and Kisii counties in December 2019 covering 16 Government of Kenya (GoK) health facilities to describe the preparedness of the facilities to deliver maternal and newborn healthcare services by examining the availability of drugs, commodities, equipment, staffing, general requirements (water and electricity, and guidelines), and the ability to perform. The results of the assessment are described using frequency and percentages, and comparative synthesis. Results: All of the 16 facilities were offering routine ANC and normal vaginal delivery services, however only two were providing CEmONC services. Most of the essential medicines and commodities were available in most of the health facilities as well as the required equipment. BEmONC and CEmONC guidelines were available in Kilifi health facilities and none in Kisii. There was only one staff in each county available 24/7 for Caesarian Section (CS) and only one anesthetist available in Kilifi. Electricity was available in all the facilities, however only half had secondary power supply. All the facilities offering CS were equipped with generators as a secondary power back-up. Conclusion: The health facilities reported availability of most of the drugs, commodities, and equipment than on general requirements as per their level of operation, however staffing and guidelines were limited. Facilities in Kilifi performed better than in Kisii. To deliver quality maternal and newborn health services, more support is required towards general infrastructure and human resources. Continuous monitoring of these services will help in the allocation of resources based on the need of the health facilities.
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 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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».