Birth and Death Notifications for Improving Civil Registration and Vital Statistics in Bangladesh: Pilot Exploratory Study
Notice bibliographique
Résumé
BACKGROUND: Effective health policy formulation requires sound information of the numerical data and causes of deaths in a population. Currently, in Bangladesh, neither births nor deaths are fully and promptly registered. Birth registration in Bangladesh is around 54% nationally. Although the legal requirements are to register within 45 days of an event, only 4.5% of births and 35.9% of deaths were reported within the required time frame in 2020. This study adopted an innovative digital notification approach to improve the coverage of registration of these events at the community level. OBJECTIVE: Our primary objective was to assess (1) the proportion of events identified by the new notification systems (success rate) and the contribution of the different notifiers individually and in combination (completeness) and (2) the proportion of events notified within specific time limits (timeliness of notifications) after introducing the innovative approach. METHODS: We conducted a pilot study in 2016 in 2 subdistricts of Bangladesh to understand whether accurate, timely, and complete information on births and deaths can be collected and notified by facility-based service providers; community health workers, including those who routinely visit households; local government authorities; and key informants from the community. We designed a mobile technology-based platform, an app, and a call center through which the notifications were recorded. All notifications were verified through the confirmation of events by family members during visits to the concerned households. We undertook a household survey-based assessment at the end of the notification period. RESULTS: Our innovative system gathered 13,377 notifications for births and deaths from all channels, including duplicate reports from multiple sources. Project workers were able to verify 92% of the births and 93% of the deaths through household visits. The household survey conducted among a subsample of the project population identified 1204 births and 341 deaths. After matching the notifications with the household survey, we found that the system was able to capture over 87% of the births in the survey areas. Health assistants and family welfare assistants were the primary sources of information. Notifications from facilities were very low for both events. CONCLUSIONS: The Global Civil Registration and Vital Statistics: Scaling Up Investment Plan 2015-2024 and the World Health Organization reiterated the importance of building an evidence base for improving civil registration and vital statistics. Our pilot innovation revealed that it is possible to coordinate with the routine health information system to note births and deaths as the first step to ensure registration. Health assistants could capture more than half of the notifications as a stand-alone source.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».