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Bringing a health systems modelling approach to complex evaluations: multicountry applications in HIV, TB and malaria.
Phillips, David E; Ambrosio, Guillermo; Batzel, Audrey; Cerezo, Carmen; Duber, Herbert; Faye, Adama; Gaye, Ibrahima; Hernández Prado, Bernardo; Huntley, Bethany; Kestler, Edgar; Kingongo, Constant; Lim, Stephen S; Linebarger, Emily; Matute, Jorge; Mpanya, Godefroid; Mulongo, Salva; O'Brien-Carelli, Caitlin; Palmisano, Erin; Rios Casas, Francisco; Shelley, Katharine; Tine, Roger; Whitaker, Daniel; Ross, Jennifer M.
Afiliação
  • Phillips DE; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA davidemphillips.passthrough@gmail.com.
  • Ambrosio G; Centro de Investigación Epidemiológica en Salud Sexual y Reproductiva (CIESAR), Guatemala City, Guatemala.
  • Batzel A; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Cerezo C; Centro de Investigación Epidemiológica en Salud Sexual y Reproductiva (CIESAR), Guatemala City, Guatemala.
  • Duber H; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Faye A; Faculty of Medicine, Universite Cheikh Anta Diop, Dakar, Senegal.
  • Gaye I; Faculty of Medicine, Universite Cheikh Anta Diop, Dakar, Senegal.
  • Hernández Prado B; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Huntley B; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Kestler E; Centro de Investigación Epidemiológica en Salud Sexual y Reproductiva (CIESAR), Guatemala City, Guatemala.
  • Kingongo C; PATH, Kinshasa, Democratic Republic of Congo.
  • Lim SS; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Linebarger E; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Matute J; Centro de Investigación Epidemiológica en Salud Sexual y Reproductiva (CIESAR), Guatemala City, Guatemala.
  • Mpanya G; PATH, Kinshasa, Democratic Republic of Congo.
  • Mulongo S; PATH, Kinshasa, Democratic Republic of Congo.
  • O'Brien-Carelli C; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Palmisano E; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Rios Casas F; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
  • Shelley K; PATH, Seattle, Washington, USA.
  • Tine R; Faculty of Medicine, Universite Cheikh Anta Diop, Dakar, Senegal.
  • Whitaker D; Technical Evaluation Reference Group, The Global Fund to Fight AIDS Tuberculosis and Malaria, Genève, Switzerland.
  • Ross JM; Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.
BMJ Glob Health ; 5(11)2020 11.
Article em En | MEDLINE | ID: mdl-33148539
INTRODUCTION: Understanding how to deliver interventions more effectively is a growing emphasis in Global Health. Simultaneously, health system strengthening is a key component to improving delivery. As a result, it is challenging to evaluate programme implementation while reflecting real-world complexity. We present our experience in using a health systems modelling approach as part of a mixed-methods evaluation and describe applications of these models. METHODS: We developed a framework for how health systems translate financial inputs into health outcomes, with in-country and international experts. We collated available data to measure framework indicators and developed models for malaria in Democratic Republic of the Congo (DRC), and tuberculosis in Guatemala and Senegal using Bayesian structural equation modelling. We conducted several postmodelling analyses: measuring efficiency, assessing bottlenecks, understanding mediation, analysing the cascade of care and measuring subnational effectiveness. RESULTS: The DRC model indicated a strong relationship between shipment of commodities and utilisation thereof. In Guatemala, the strongest model coefficients were more evenly distributed. Results in Senegal varied most, but pathways related to community care had the strongest relationships. In DRC, we used model results to estimate the end-to-end cost of delivering commodities. In Guatemala, we used model results to identify potential bottlenecks and understand mediation. In Senegal, we used model results to identify potential weak links in the cascade of care, and explore subnationally. CONCLUSION: This study demonstrates a complementary modelling approach to traditional evaluation methods. Although these models have limitations, they can be applied in a variety of ways to gain greater insight into implementation and functioning of health service delivery.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Infecções por HIV / Malária Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans País/Região como assunto: Africa Idioma: En Revista: BMJ Glob Health Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Infecções por HIV / Malária Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans País/Região como assunto: Africa Idioma: En Revista: BMJ Glob Health Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos