Applying a system dynamics modelling approach to explore policy options for improving neonatal health in Uganda

Description of variables. (DOCX 31 kb

Advancing the application of systems thinking in health : understanding the dynamics of neonatal mortality in Uganda

Systems thinking in health encompasses linkages, interactions, feedbacks, and processes between elements that comprise a whole system, including the complexity of a disease or condition itself (such as neonatal mortality) and the systems within which they are interacting and evolving, in this case the health system. Data analysis and brainstorming sessions were used to develop causal loop diagrams (CLDs) depicting the causes of neonatal mortality. The study explores how systems thinking tools, more specifically CLDs and system dynamics modelling can help better understand the complexity underlying factors behind stagnant neonatal mortality rates in Uganda

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

Payment for performance (P4P) has been employed in low and middle-income (LMIC) countries to improve quality and coverage of maternal and child health (MCH) services. However, there is a lack of consensus on how P4P affects health systems. There is a need to evaluate P4P effects on health systems using methods suitable for evaluating complex systems. We developed a causal loop diagram (CLD) to further understand the pathways to impact of P4P on delivery and uptake of MCH services in Tanzania. The CLD was developed and validated using qualitative data from a process evaluation of a P4P scheme in Tanzania, with additional stakeholder dialogue sought to strengthen confidence in the diagram. The CLD maps the interacting mechanisms involved in provider achievement of targets, reporting of health information, and population care seeking, and identifies those mechanisms affected by P4P. For example, the availability of drugs and medical commodities impacts not only provider achievement of P4P targets but also demand of services and is impacted by P4P through the availability of additional facility resources and the incentivisation of district managers to reduce drug stock outs. The CLD also identifies mechanisms key to facility achievement of targets but are not within the scope of the programme; the activities of health facility governing committees and community health workers, for example, are key to demand stimulation and effective resource use at the facility level but both groups were omitted from the incentive system. P4P design considerations generated from this work include appropriately incentivising the availability of drugs and staffing in facilities and those responsible for demand creation in communities. Further research using CLDs to study heath systems in LMIC is urgently needed to further our understanding of how systems respond to interventions and how to strengthen systems to deliver better coverage and quality of care

Factors influencing customer behaviour in different market segments: an agent-based approach in mobile telecommunication in Uganda

This research investigated the factors that influence customer behaviour in the different market segments using Agent-Based simulation modeling in the mobile telecommunication in Uganda. The study was based on a computer simulated model designed using data collected. Results were analyzed to understand the behaviour of different segments of customers. Findings revealed that using AB model specific factors like strong desire to search new ideas influence the youth, self-esteem the professionals, a sense of belongingness the business people and low-income earners are influenced by risk aversion. Hence other than bringing out specifics for generalities the integration with system dynamics is necessary.Keywords: Simulation, Agent-Based, Market, segments, Any-Logic, Modellin

Critical risk and success factors for sustainability of an electronic health data capture, processing and dissemination platform for Uganda.

Peer reviewed: TrueSeveral studies have investigated challenges that have marred success or even caused the failure of eHealth implementations in Uganda; however, none has focused on the risks and success factors of their sustainability. This study explored critical risk and success factors for the sustainability of an electronic health data capture, processing and dissemination platform for Uganda. A mixed-method research design was followed involving collecting empirical data from all four regions of Uganda. A purposive sampling strategy was used to select the study districts per region, health facilities per district, and respondents/participants per facility or district. Findings revealed several risks and success factors for sustainability, including; bad leadership, corruption, lack of sustainable maintenance programs, lack of suitable sustainability plans, lack of ICT infrastructure investment, poor management systems, funds, stakeholder buy-ins, data sharing and access rights. The success factors included reinvestments as a partial sustainability plan for ICT infrastructure. These factors can be leveraged to ensure the continued operation of eHealth implementations in Uganda. Every electronic health project aiming at success should always make due consideration/sustainability plan at the onset of project conceptualisation; as lack of such a plan has often resulted in failed projects after the initial funds have been withdrawn

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 visualise 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