Understanding the maternal and child health system response to payment for performance in Tanzania using a causal loop diagram approach

Understanding the role of the Tanzania national health insurance fund in improving service coverage and quality of care

Health insurance is one of the main financing mechanisms currently being used in low and middle-income countries to improve access to quality services. Tanzania has been running its National Health Insurance Fund (NHIF) since 2001 and has recently undergone significant reforms. However, there is limited attention to the causal mechanisms through which NHIF improves service coverage and quality of care. This paper aims to use a system dynamics (qualitative) approach to understand NHIF causal pathways and feedback loops for improving service coverage and quality of care at the primary healthcare level in Tanzania. We used qualitative interviews with 32 stakeholders from national, regional, district, and health facility levels conducted between May to July 2021. Based on the main findings and themes generated from the interviews, causal mechanisms, and feedback loops were created. The majority of feedback loops in the CLDs were reinforcing cycles for improving service coverage among beneficiaries and the quality of care by providers, with different external factors affecting these two actions. Our main feedback loop shows that the NHIF plays a crucial role in providing additional financial resources to facilities to purchase essential medical commodities to deliver care. However, this cycle is often interrupted by reimbursement delays. Additionally, beneficiaries' perception that lower-level facilities have poorer quality of care has reinforced care seeking at higher-levels. This has decreased lower level facilities' ability to benefit from the insurance and improve their capacity to deliver quality care. Another key finding was that the NHIF funding has resulted in better services for insured populations compared to the uninsured. To increase quality of care, the NHIF may benefit from improving its reimbursement administrative processes, increasing the capacity of lower levels of care to benefit from the insurance and appropriately incentivizing providers for continuity of care.

Viewing the global health system as a complex adaptive system - implications for research and practice

The global health system (GHS) is ill-equipped to deal with the increasing number of transnational challenges. The GHS needs reform to enhance global resilience to future risks to health. In this article we argue that the starting point for any reform must be conceptualizing and studying the GHS as a complex adaptive system (CAS) with a large and escalating number of interconnected global health actors that learn and adapt their behaviours in response to each other and changes in their environment. The GHS can be viewed as a multi-scalar, nested health system comprising all national health systems together with the global health architecture, in which behaviours are influenced by cross-scale interactions. However, current methods cannot adequately capture the dynamism or complexity of the GHS or quantify the effects of challenges or potential reform options. We provide an overview of a selection of systems thinking and complexity science methods available to researchers and highlight the numerous policy insights their application could yield.   We also discuss the challenges for researchers of applying these methods and for policy makers of digesting and acting upon them. We encourage application of a CAS approach to GHS research and policy making to help bolster resilience to future risks that transcend national boundaries and system scales.

How to do (or not to do)…Using Causal Loop Diagrams for Health System Research in Low- and Middle-Income Settings

Causal loop diagrams (CLDs) are a systems thinking method that can be used to visualize and unpack complex health system behaviour. They can be employed prospectively or retrospectively to identify the mechanisms and consequences of policies or interventions designed to strengthen health systems and inform discussion with policymakers and stakeholders on actions that may alleviate sub-optimal outcomes. Whilst the use of CLDs in health systems research has generally increased, there is still limited use in low- and middle-income settings. In addition to their suitability for evaluating complex systems, CLDs can be developed where opportunities for primary data collection may be limited (such as in humanitarian or conflict settings) and instead be formulated using secondary data, published or grey literature, health surveys/reports and policy documents. The purpose of this paper is to provide a step-by-step guide for designing a health system research study that uses CLDs as their chosen research method, with particular attention to issues of relevance to research in low- and middle-income countries (LMICs). The guidance draws on examples from the LMIC literature and authors’ own experience of using CLDs in this research area. This paper guides researchers in addressing the following four questions in the study design process; (1) What is the scope of this research? (2) What data do I need to collect or source? (3) What is my chosen method for CLD development? (4) How will I validate the CLD? In providing supporting information to readers on avenues for addressing these key design questions, authors hope to promote CLDs for wider use by health system researchers working in LMICs.