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Understanding evidence ecosystems: What influences the production, translation, and use of modeled evidence in Burkina Faso, Nigeria, India, and Kenya?
Sié, Ali; Fofana, Habibou; Kagoné, Moubassira; Ouédraogo, Moussa; Onwujekwe, Obinna E; Mbachu, Chinyere O; Chokshi, Maulik; Chilgod, Latha; Mokashi, Tushar; Nair, Arun B; Muriuki, Peter; Taddese, Abeba; Ewald, Leah; Handigol, Apoorva.
Afiliação
  • Sié A; Centre de recherche en santé de Nouna, Ouagadougou, Burkina Faso.
  • Fofana H; Centre de recherche en santé de Nouna, Ouagadougou, Burkina Faso.
  • Kagoné M; Centre de recherche en santé de Nouna, Ouagadougou, Burkina Faso.
  • Ouédraogo M; Centre de recherche en santé de Nouna, Ouagadougou, Burkina Faso.
  • Onwujekwe OE; Health Policy Research Group, University of Nigeria, Enugu, Nigeria.
  • Mbachu CO; Health Policy Research Group, University of Nigeria, Enugu, Nigeria.
  • Chokshi M; ACCESS Health International, New Delhi, India.
  • Chilgod L; ACCESS Health International, New Delhi, India.
  • Mokashi T; ACCESS Health International, New Delhi, India.
  • Nair AB; ACCESS Health International, New Delhi, India.
  • Muriuki P; Independent, Nairobi, Kenya.
  • Taddese A; Results for Development Institute, Washington, District of Columbia, USA.
  • Ewald L; Results for Development Institute, Washington, District of Columbia, USA.
  • Handigol A; Results for Development Institute, Washington, District of Columbia, USA.
Gates Open Res ; 7: 135, 2023.
Article em En | MEDLINE | ID: mdl-39165698
ABSTRACT

Background:

This study sought to document and understand facilitators and barriers to producing, translating, and using modeled evidence in decision-making in Burkina Faso, Nigeria, India, and Kenya. We explored researcher-decision-maker engagement mechanisms as key facilitators of evidence use, with a focus on knowledge brokers and boundary organizations.

Methods:

The study used sequential mixed methods drawing on data collected from surveys and key informant interviews, complemented by a rapid desk review to map modeling activities and actors. The survey was conducted online while the qualitative research entailed in-depth interviews with modelers, knowledge brokers, and decision-makers working in a representative variety of health fields, organizations, and levels of government. This study was approved by Health Media Lab IRB (Institutional Review Board) in the United States and a local IRB in each study country and conducted between September 2021 and June 2022.

Results:

Informants interviewed for this study described a range of factors that facilitate and inhibit the use of modeled evidence in public health decision-making at the individual, organizational, and environmental levels. Key themes included the capacity to produce, translate, and use modeled evidence; the timing and relevance of modeling outputs; the existence of communications channels between modelers and decision-makers; the strength of underlying data systems; the role of sustained funding; and the impact of global crises.

Conclusion:

This study highlights the importance of taking an ecosystem approach to supporting modeling activities, considering individual, organizational, and environmental factors and how different actors and interact to inform the production, translation, and use of modeled evidence. Structured interaction that promotes dialogue, debate, and joint sense making between the producers and users of evidence is critical to informing and influencing the use of evidence in decision-making.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tomada de Decisões Limite: Humans País/Região como assunto: Africa / Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tomada de Decisões Limite: Humans País/Região como assunto: Africa / Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article