Innovative dashboard for optimising emergency obstetric care geographical accessibility in Nigeria: Qualitative study with technocrats
Notice bibliographique
Résumé
Objective: To explore perspectives of public sector technocrats on the role of and considerations needed for implementing an innovative dashboard that leverages geographic information systems (GIS) in supporting optimisation of emergency obstetric care (EmOC) geographical accessibility in Nigeria. Methods: Twenty-three semi-structured interviews were conducted in person or virtually with six policymakers and 17 senior civil servants in Nigeria. Braun and Clarke's six-step approach to thematic analysis, which involved data familiarisation, initial code generation, searching for themes, reviewing themes, defining themes, and producing the report, was applied. Results: Despite recognising the ideal of data-driven needs assessment, in reality, factors such as political pressure, persistent community advocacy, and donor funding drive decisions on siting EmOC facilities. Irregular short-term political cycles and exigencies in health systems prevent new facilities from being established or motivate a focus on facility quality over quantity. There was a strong appetite for using GIS-enabled dashboards to support planning, with enthusiasm for such technology more apparent where innovation was already part of government's philosophy. A digital dashboard that is dynamic, reflective of reality, inclusive of public and private providers, incorporates facility characteristics, and can test accessibility scenarios, was deemed particularly valuable. Its value proposition extended beyond EmOC and provider type. However, its success as a policy tool will depend on the veracity and currency of the data informing it. Conclusions: Technocrats welcome dynamic GIS-enabled dashboards as it offers a significant step-change compared to the current practice for EmOC service planning. Value-for-money of such innovations must be considered if implemented. Public Interest Summary: Planning and siting of emergency services used by pregnant women (EmOC) in many low-resource countries are mostly haphazard. However, there is increasing recognition that technology can refine this process. In this study, we explored perspectives of public sector technocrats in Nigeria on the role of and considerations needed for implementing an innovative digital dashboard that leverages geographic information systems in optimising EmOC geographical accessibility. We found that current planning is mainly driven by political pressure, community advocacy, and donor funding. However, there is a strong appetite in government for using GIS-enabled dashboards to inform service planning, with enthusiasm for such technology appearing to be more grounded in states where innovation was already part of the government's philosophy. Yet, concerns about data accuracy were expressed. Broadly, dashboards that are dynamic, reflective of reality, inclusive of public and private providers, incorporate facility characteristics, and can test access scenarios, were deemed particularly valuable.
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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 | 0,011 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,006 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».