A Systems Dynamics Approach to Understanding the Determinants of Antenatal Care Utilization in Low-and Middle-Income Countries

Abstract

There has been low adherence of antenatal care utilization (ANC) in low and middle-income countries (LMIC) despite its associated negative outcome on women and their unborn babies. Although several studies have examined ANC, the majority focus on isolated aspects and do not explore the holistic approach to understand its dynamics. The system dynamics approach provides a deeper understanding of the phenomenon by examining the underlying factors, causes, effects, feedback, and delays. This study aimed at understanding factors that influence ANC utilization using the system's dynamics approach. An interpretive systematic review to establish multifaceted and context-specific processes was done between May and November 2019. Data from 24 articles were synthesized and used to build causal loop diagrams, which were validated through focus group discussions and interviews with stakeholders. Results revealed human resource numbers and welfare, awareness campaigns, peer support groups, and community-based engagement as key leverage points towards ANC improvement.

Utilization of Antenatal Care Services Within the Context of COVID-19, Security Challenges, and an Unstable Healthcare System at Primary Health Care Centers

“…The outcomes of this study are in line with established literature, underscoring the diverse factors that impact ANC utilization. 22–24 These parallels underscore the global nature of these challenges and the need for context-specific intervention. We must address the complexity of the factors influencing ANC utilization, encompassing sociodemographic and external challenges.…”

How to do (or not to do)…using causal loop diagrams for health system research in low and middle-income settings

“…They can be used in conjunction with existing health system frameworks, for example by identifying interconnections and/or dynamic behaviour between the WHO health system building blocks (Sharma et al, 2020). Finally, CLDs can also support the synthesis of evidence regarding a health systems intervention, used to present the results of realist and systematic reviews (Namatovu and Semwanga, 2020;Singh et al, 2021).…”

“…Other secondary data such as published or grey literature (Yu et al, 2018;Kurnianingtyas et al, 2020), health surveys or reports (Li et al, 2019) and policy documents (Nigenda et al, 2015) can also be used to develop CLDs. Data extracted through a systematic or realist review can be cleaned, integrated and categorized to generate cause and effect relationships that can be represented in a CLD (Namatovu and Semwanga, 2020;Singh et al, 2021).…”