PT  - JOURNAL ARTICLE
AU  - David E Phillips
AU  - Guillermo Ambrosio
AU  - Audrey Batzel
AU  - Carmen Cerezo
AU  - Herbert Duber
AU  - Adama Faye
AU  - Ibrahima Gaye
AU  - Bernardo Hernández Prado
AU  - Bethany Huntley
AU  - Edgar Kestler
AU  - Constant Kingongo
AU  - Stephen S Lim
AU  - Emily Linebarger
AU  - Jorge Matute
AU  - Godefroid Mpanya
AU  - Salva Mulongo
AU  - Caitlin O'Brien-Carelli
AU  - Erin Palmisano
AU  - Francisco Rios Casas
AU  - Katharine Shelley
AU  - Roger Tine
AU  - Daniel Whitaker
AU  - Jennifer M Ross
TI  - Bringing a health systems modelling approach to complex evaluations: multicountry applications in HIV, TB and malaria
AID  - 10.1136/bmjgh-2020-002441
DP  - 2020 Nov 01
TA  - BMJ Global Health
PG  - e002441
VI  - 5
IP  - 11
4099  - http://gh.bmj.com/content/5/11/e002441.short
4100  - http://gh.bmj.com/content/5/11/e002441.full
SO  - BMJ Global Health2020 Nov 01; 5
AB  - 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.