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

Description of variables. (DOCX 31 kb

An application of system dynamics modeling to immunisation policy analysis

A thesis submitted in partial fulfillment of the requirements for the award of the Doctor of Philosophy Degree in Computer Science of Makerere University.Simulation modeling is increasingly being used for strategy implementation, policy analysis and design in many application areas including health care management. Preventable childhood diseases and premature deaths still occur particularly in the developing countries due to low immunisation coverage. Although, various approaches have been applied to understand immunisation coverage problems, there are still acknowledged deficiencies in these approaches. While the immunisation system like other healthcare systems is very complex and difficult to manage, the System Dynamics modeling approach is applied to improve the understanding of acknowledged problems and to support improved decision making. To determine the full range of activities, inputs and challenges associated with immunisation coverage, field studies were carried out. Problems influencing immunisation coverage included inadequate provision of healthcare service, low levels of immunisation awareness, economic factors and poor vaccine management. The research presents the overall architecture of the immunisation system which constitutes agents, key processes, activities and information flow. Causal loop diagrams and a simulation model (stock and flow) were used to capture the complex and dynamic nature of the immunisation process while a case study on the Ugandan healthcare system was used to test its effectiveness. National immunisation service providers validated the model and rated it as a useful communication and decision making tool. The above provide a deeper understanding of the immunisation system thus facilitating the development of health information systems that are appropriate. Results of the study show that, the population, healthcare and vaccine management policies have overwhelming influence on immunisation coverage and form the foundations on which the success of immunisation policy is based. The study reaffirms the need to determine the current capacity of the health system and strengthen it to cater for the growing population. The designed application demonstrates the dynamics arising from complexity, delays and non‐linearity which characterise the immunisation system and tests different policies towards the improvement of immunisation coverage. Based on the results of simulation experiments, suggested intervention strategies that could provide substantial effect on immunisation coverage include: strengthening of the healthcare system, design of relevant health information systems, adoption of ICTs innovations to improve operational efficiency, improvement of the livelihood of the population and increasing literacy levels. The developed model and causal loop diagrams constitute significant knowledge in terms of structure and the understanding of immunisation coverage. The model captures requisite information requirements, key processes of the immunisation system which provide support for process improvement, operational management and training. The model provides tools that test different policies thus making it useful for strategic planning and policy debate

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

Identifying the active ingredients in payment for performance programmes using system dynamics modelling

Payment for performance (P4P) is not a uniform intervention, with programme effect dependent on several interconnected factors. In this study, a system dynamics model was developed to explore the pathways to improved outcomes and how changes in the design, implementation and context of a P4P programme affected maternal and child health (MCH) service delivery outcomes in Tanzania. A previously developed causal loop diagram of the programme effects was used to inform model development, with further data sources (including an impact evaluation of programme, health surveys, stakeholder feedback and relevant literature) used to build the model. A number of pathways were identified to improved services under P4P, with increased availability of drugs underpinning the content of care outcome (intermittent preventative treatment during ANC), which together with increased supervision, enhanced health worker motivation. This in turn increased perceived quality of care at the facility which improved the coverage of services outcome (facility-based deliveries), and with increased outreach, increased awareness of services also boosted demand. Minor delays in payment reduced provider purchasing power for medicines, with severe delays driving erosion of provider trust and motivation for programme participation. Allocating a larger share of funds for facility operations can enhance performance effects, particularly for those services that rely on efficient drug administration. Contextual factors including limited baseline provision of essential medications, lower community awareness of facility services and dispersed/distant populations reduced programme effect. This paper demonstrates the feasibility and the potential of such models to inform the design of effective health system interventions

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

Modeling the Complexity of Road Accidents Prevention

Simplistic representations of traffic safety disregard the dynamic interactions between the components of the road transport system (RTS). The resultant road accident (RA) preventive measures are consequently focused almost solely on individual/team failures at the sharp end of the RTS (mainly the road users). The RTS is complex and therefore cannot be easily understood by studying the system parts in isolation. The study modeled the occurrence of road accidents in Uganda using the dynamic synthesis methodology (DSM). This article presents the work done in the first three stages of the DSM. Data was collected from various stakeholders including road users, traffic police officers, road users, and road constructors. The study focused on RA prevention by considering the linear and non-linear interactions of the variables during the pre-crash phase. Qualitative models were developed and from these, key leverage points that could possibly lower the road accident incidences demonstrating the need for a shared system wide responsibility for road safety at all levels are suggested.</jats:p

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

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.</jats:p

Assessing the Quality of E-Government Websites in Uganda

Governments are increasingly using web-based portals to provide information and cost-effective service delivery. While some e-government websites have delivered the intended goal, others are still struggling. This study assessed the quality of the e-government websites using a three-step investigation methodology. Firstly, the quality attributes were generated from literature, then a conceptual framework for e-government websites with four quality dimensions was developed, and lastly, an observation instrument was used to measure the quality attributes of 78 Uganda e-government websites. Most of the websites scored highly on the level of authority, relevance, quality of text, organization of the website, and time to download. The level of attractiveness, content accuracy, objectivity, currency of information, use of multimedia, and multi-language required significant improvements while the use of social media and evidence of security and privacy of the information was hardly visible. A framework is proposed to improve the quality of e-government websites.</p

System dynamics modeling in healthcare: The Ugandan immunisation system

The paper suggests key leverage points which could substantially improve immunisation demand, effectiveness of the health system as well as vaccine management.The paper develops a system dynamics simulation model to understand the dynamics of immunisation with the aim of aiding decision making process by proposing policies that would enhance immunisation utilization. The model is designed with the intent to show how particular variables influence immunisation demand and coverage rather than predict immunisation coverage rates. The paper applies system dynamics modeling and field study research methods to capture the complex and dynamic nature of the immunization process, to enhance the understanding of the immunization health care problems and to generate insights that may increase the immunization coverage effectiveness. The model is divided into four sectors interacting with one another. The paper suggests key leverage points which could substantially improve immunisation demand, effectiveness of the health system as well as vaccine management