Effectiveness of Onsite Nurse Mentoring in Improving Quality of Institutional Births in the Primary Health Centres of High Priority Districts of Karnataka, South India: A Cluster Randomized Trial
Notice bibliographique
Résumé
BACKGROUND: In India, although the proportion of institutional births is increasing, there are concerns regarding quality of care. We assessed the effectiveness of a nurse-led onsite mentoring program in improving quality of care of institutional births in 24/7 primary health centres (PHCs that are open 24 hours a day, 7 days a week) of two high priority districts in Karnataka state, South India. Primary outcomes were improved facility readiness and provider preparedness in managing institutional births and associated complications during child birth. METHODS: All functional 24/7 PHCs in the two districts were included in the study. We used a parallel, cluster randomized trial design in which 54 of 108 facilities received six onsite mentoring visits, along with an initial training update and specially designed case sheets for providers; the control arm received just the initial training update and the case sheets. Pre- and post-intervention surveys were administered in April-2012 and August-2013 using facility audits, provider interviews and case sheet audits. The provider interviews were administered to all staff nurses available at the PHCs and audits were done of all the filled case sheets during the month prior to data collection. In addition, a cost analysis of the intervention was undertaken. RESULTS: Between the surveys, we achieved coverage of 100% of facilities and 91.2% of staff nurse interviews. Since the case sheets were newly designed, case-sheet audit data were available only from the end line survey for about 80.2% of all women in the intervention facilities and 57.3% in the control facilities. A higher number of facilities in the intervention arm had all appropriate drugs, equipment and supplies to deal with gestational hypertension (19 vs.3, OR (odds ratio) 9.2, 95% C.I 2.5 to33.6), postpartum haemorrhage (29 vs. 12, OR 3.7, 95% C.I 1.6 to8.3); and obstructed labour (25 vs.9, OR 3.4, 95% CI 1.6 to8.3). The providers in the intervention arm had better knowledge of active management of the third stage of labour (82.4% vs.35.8%, AOR (adjusted odds ratio) 10, 95% C.I 5.5 to 18.2); management of maternal sepsis (73.5% vs. 10.9%, AOR 36.1, 95% C.I 13.6 to 95.9); neonatal resuscitation (48.5% vs.11.7%, AOR 10.7, 95% C.I 4.6 to 25.0) and low birth weight newborn care (58.1% vs. 40.9%, AOR 2.4, 95% C.I 1.2 to 4.7). The case sheet audits revealed that providers in the intervention arm showed greater compliance with the protocols during labour monitoring (77.3% vs. 32.1%, AOR 25.8, 95% C.I 9.6 to 69.4); delivery and immediate post-partum care for mothers (78.6% vs. 31.8%, AOR 22.1, 95% C.I 8.0 to 61.4) and for newborns (73.9% vs. 32.8%, AOR 24.1, 95% C.I 8.1 to 72.0). The cost analysis showed that the intervention cost an additional $5.60 overall per delivery. CONCLUSIONS: The mentoring program successfully improved provider preparedness and facility readiness to deal with institutional births and associated complications. It is feasible to improve the quality of institutional births at a large operational scale, without substantial incremental costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02004912.
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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 | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».