Optimizing data visualization for reproductive, maternal, newborn, child health, and nutrition (RMNCH&N) policymaking: data visualization preferences and interpretation capacity among decision-makers in Tanzania.

Aung, Tricia; Niyeha, Debora; Shagihilu, Shagihilu; Mpembeni, Rose; Kaganda, Joyceline; Sheffel, Ashley; Heidkamp, Rebecca

Aung, Tricia; Niyeha, Debora; Shagihilu, Shagihilu; Mpembeni, Rose; Kaganda, Joyceline; Sheffel, Ashley; Heidkamp, Rebecca.

Afiliación

Aung T; 1Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
Niyeha D; 1Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
Shagihilu S; National Bureau of Statistics, Dar es Salaam, Tanzania.
Mpembeni R; 3School of Public Health and Social Sciences, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.
Kaganda J; 4Tanzania Food and Nutrition Centre, Dar es Salaam, Tanzania.
Sheffel A; 1Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
Heidkamp R; 1Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.

Glob Health Res Policy ; 4: 4, 2019.

Article en En | MEDLINE | ID: mdl-30783631

Palabras clave

Child health; Data visualization; Maternal; Newborn; Nutrition; Policy; Reproductive; Tanzania

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Aspecto: Patient_preference Idioma: En Revista: Glob Health Res Policy Año: 2019 Tipo del documento: Article Pais de publicación: Reino Unido

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