Downloaded 39 times
Uploaded byAneesa K Ayoob
SYSTEM THINKING IN PUBLIC HEALTH
This document provides an overview of systems thinking in public health. It discusses types of systems including simple, complicated, chaotic, and complex adaptive systems. It describes WHO building blocks for health systems strengthening and limitations of this approach. Feedback loops, path dependence, scale-free networks, emergent behavior, and phase transitions are discussed as concepts from complexity science. Theories of systems thinking like catastrophe theory, chaos theory, and systems dynamics modeling are outlined. The document concludes with an example of a safe deliveries pilot project in Uganda that demonstrated emergent behavior and a phase transition.
More Related Content
Similar to SYSTEM THINKING IN PUBLIC HEALTH
More from Aneesa K Ayoob
SYSTEM THINKING IN PUBLIC HEALTH
- 1. SYSTEMTHINKING IN PUBLICHEALTH Seminar no:15
- 2. CONTENTS • Introduction • Typesof systems • WHO “Building Blocks” for Health Systems Strengthening • Understanding Pathways for Scaling Up Health Services • Systems thinking theories and tools • Limitations • Challenges • References
- 3. Systems thinking isaimed at seeing how things are connected to each other within some notion of a whole entity. Rather than implicit models Use explicit models Identify assumptions Use data Can be repeated by others understanding of how “things stand together” as a whole Why Use SystemsThinking? SystemsThinking has multiple origins: • Multiple disciplines and problems being addressed • Many different types of theories, methods, and tools used in systems thinking
- 4. General SystemsTheory- Bertalanffy •A metatheory, not a single theory • More an approach to finding general theory across fields of scientific, philosophical, and technological inquiry • Focus on self-regulation and emergence that occurs in a wide range of settings—a transdisciplinary approach
- 5. System An interaction ofparts and their interconnections that come together for a purpose. Systems Non-systems Parts are connected Parts are independent Changing one part or connection affects other elements of the system Changing one part does not necessarily affect other elements Parts operate towards a purpose No explicit purpose
- 6. What Is aHealth System? • Any system that has a purpose related to health (Peters, origin obscure) • Not just health care, also population and public health Traditional health systems definitions: • “the combination of resources, organization, financing and management that culminate in the delivery of health services to the population” (Roemer, 1991) • “all the activities whose primary purpose is to promote, restore or maintain health” (WHO, 2000)
- 7. Simple Systems • Fewelements (factors, variables, agents) • Stable relationships between variables; limited types: causal, confounding, intermediating, effect modification • Deterministic or stochastic statistical patterns (e.g., linear, logit, probit) Complicated Systems • Many elements • Unknown or unstable relationships • No adaptation (cf. complexity) • Poor fit with statistical prediction Types of Systems:
- 8. Chaotic Systems • Manyelements • Dynamic relationships, critical role of initiating conditions (butterfly effect) • No adaptation • Apparently random appearance with underlying order, predictable through universal mathematic functions (fractal dimensions and equations) Lorenz Attractor (Water Flow Rate in Water Wheel)
- 9. Complex Adaptive Systems(CAS) • Many elements • Changing or metastable relationships, but acting as a system • Predictable but not in detail • Emergent behavior (adaptation, learning, self-organization) • Nonlinearity (e.g., scale free) • Divergence (unintended consequences and different outcomes from same inputs) • Convergence (many routes to same outcome) • Most biological, social, economic, and physical systems that have many interacting agents in a changing environment are CAS Source: http://www.safalniveshak.com/latticework-mental-models-complex-adaptive-systems/
- 10. WHO “Building Blocks”for Health Systems Strengthening
- 11. • Missing partsand linkages in a system • Where are the PEOPLE (demand side) and organizations (key actors)? • Where are the incentives and institutions? • Ignores dynamic nature of health systems • Limited and simplistic view: • Role of context • Fixed interventions • Intended outcomes • Ignore possibility for learning and adaptation • Replication model for scaling up
- 12. Health System Actors,Functions, and Outcomes
- 13. The Conventional Pathwayto Improving and Scaling Up Health Services 1. Choose the right (cost-effective) health interventions 2. Set common targets 3. Fund them 4. Implement interventions as designed Scaling-up a given practice in a complex health system requires strategic planning, collaboration, clear communication and a strong monitoring and evaluation component. Scaling Up Health Services
- 14. CAS Pathways:The Problemof Scaling Up • Intervention that may work on small scale, research setting, or one country cannot be simply replicated elsewhere on large scale • “Control” over behaviors of communities and providers is limited in real world • Even simple interventions involve complex social interventions • Small stimulus may produce large changes, large programs may have little effect • Unintended consequences are common
- 15. Understanding Pathways forScaling Up Health Services through the Lens of Complex Adaptive Systems- Ligia Paina and David Peters
- 16. • A feedbackloop is a mechanism by which change in a variable results in either an amplification (positive feedback) or a dampening (negative feedback) of that change. • Reinforcing: vicious and virtuous circles, “bubbles and bursts” • Balancing: regulates towards equilibrium CAS Pathways—Feedback
- 17. Feedback Loops: CausalLoop Patterns for Demand for Immunizations in Uganda Source: Stylized adaptation from Rwashana et al. (2009). Health Informatics, 15(2): 95-107. 7
- 18. CAS Pathways—Path Dependence •Path dependence is a phenomenon whereby history matters; what has occurred in the past persists because of resistance to change. • For example, QWERTY keyboard, technological standards
- 19. • Nonlinear growthrelated to attribute of component • Describes “tipping points” and why some hubs are more influential than others CAS Pathways—Scale Free Networks
- 21. Emergent Behavior • Elementsorganize themselves to form new structures • For example, flocking of birds—powerful groups get rationed services PhaseTransitions • Qualitative change in nature of entity • For example, transition of water to gas, liquid or solid; transition of a perception or belief to an expectation or norm
- 22. Example: Uganda SafeDeliveries Pilot Project • Problem of moderate antenatal care coverage, low skilled birth attendance, and high maternal mortality • Many years of training, supervision, and efforts to improve supplies and educate public with little effect • Research team met with community and providers to better understand “health market” and design intervention • Identified constraints to overcome: need to cover transport costs, incentives to health workers • Identified untapped resources: men with motorcycles Group discussion with pregnant women in Kidera Village in Kamuli District Pregnant woman being transported to Nkond Health Center in Kamuli District
- 23. Uganda Safe DeliveriesPilot Project: Emergent Behavior and Phase Transition
- 24. SystemsThinking vs CAS Traditional models assume Regularity Stable change(e.g., linear) Predictabilit y No adaptation Complexity models embrace Dynamism Irregularity Adaptation Instability Unpredictabil ity
- 25. Model for UnderstandingComplexity in Health Systems
- 26. SystemsThinking: SelectedTheories Source: Peters,D.H. (2014) The application of systems thinking in health: why use systems thinking? Health Research Policy and Systems, 12:51 Catastrophe theory Mathematics and geometry theory on how small changes in parameters of a nonlinear system can lead to sudden and large changes in system behavior Chaos theory Based in mathematics to explain a dynamic system and that is highly sensitive to the initial conditions, so that small changes in initial conditions produce wildly different results.The changes occur through fixed rules about changing relationships, and without randomness. Learning organizations theory Organizations that facilitate learning by its members to continuously transform itself. Involves personal learning, challenging and building of mental models, developing a shared vision and team learning. Path dependency theories Economics, social sciences, and physics theories to explain why a similar starting point can lead to different outcomes, even if they follow the same rules. Outcomes are sensitive not only to initial conditions, but also to bifurcations and choices made along the way, which may be irreversible. Punctuated equilibrium in social theory Explains long periods of stasis interrupted by rapid and radical change, particularly as applied to the evolution of policy change or conflict
- 27. Agent-based modeling (ABM) ABMs areused to create a virtual representation of a complex system, modeling individual agents who interact with each other and the environment. Interactions are based on simple, predefined rules, and allow for the identification of emergence and self-organization. Network analysis (or social network analysis) Network analysis uses graphical methods to demonstrate relations between objects. Applies network theory to social entities (e.g., people, groups, organizations), demonstrating nodes (individual actors within a network), and ties (the type of relationships) between the actors, and uses a range of tools for displaying the networks and analyzing the nature of the relationships. Systems dynamics modeling A range of methods to understand the behavior of complex systems over time. The methods are based on the concepts of stocks and flows and feedback loops.They are designed to solve the problem of simultaneity (mutual causation) by being able to change variables over small periods of time while allowing for feedback and various interactions and delays. SystemsThinking: Selected Research Methods
- 28. Causal loop diagrams (CLDs) Asystem dynamics tool that produces qualitative illustrations of mental models, highlighting causality and feedback loops. CLDs are often developed in a participatory approach. Stock and flow diagrams Stock and flow diagrams are quantitative system dynamics tools used for illustrating a system that can be used for model-based policy analysis in a simulated, dynamic environment. Stock and flow diagrams explicitly incorporate feedback to understand complex system behavior and capture nonlinear dynamics, often using CLDs. Innovation (or change management) history Innovation or change management history aims to generate knowledge about a system by compiling a systematic history of key events, intended and unintended outcomes and measures taken to address emergent issues. It involves in-depth interviews with as many key stakeholders as possible to build an understanding of the performance of the system from a number of different points of view. Participatory impact pathways analysis (PIPA) PIPA is a workshop-based approach that combines impact pathway logic models and network mapping through a process involving stakeholder engagement, making assumptions and mental models explicit and used to reach consensus on how to achieve impact. Process mapping A set of tools, such as flow charts, to provide a pictorial representation of a sequence of actions and responses. Their use can be quite flexible, such as to make clear current processes, as a basis for identifying bottlenecks or inefficient steps, or to produce an ideal map of how they’d like them to be. SystemsThinking Research: SelectedTools
- 29. How SystemsThinking InformsHealth Systems Interventions • Better understanding of the dynamics of disease transmission, and relationships with the health system, contextual factors, and population health • Identify root causes of variations in behaviors and services • Identify multisectoral factors which promote the spread of innovation • Better understanding of intended and unintended consequences • New tools and approaches to understand and facilitate decision making SystemsThinking Implications for Working in Complex Health Systems • Policy and planning needs flexibility to address dynamic and adaptive properties of health systems • Use data in frequent cycles of adaptation, experimentation, and planning, involving key players
- 30. WHO framework • 4articles six building blocks (service delivery, workforce, information services, access to medical technologies, financing and leadership and governance) • 16 articles- one or few of the 6 building blocks • 6 articles- different frameworks or modelsWHOS’s
- 33. How Can WeApply ‘SystemsThinking’ in Health System?
- 35. Systems Thinking isnecessary because it will help to: 1.Explore the problems in the health system from the systems perspective 2.Identify solutions that work across sub-systems 3.Promote dynamic networks of diverse stakeholders 4.Inspire and encourage learning from each other 5.Strengthen more system-wide planning, evaluation and research. 6.To think holistically about the consequences and different stakeholders
- 36. Limitations of ‘SystemsThinking’: •Application of system thinking in which and every step require lots of time and money. One may not have the luxury of such time and money. • It takes longer time to solve any issue with SystemThinking concept. • The concept of SystemsThinking in itself is very complex and difficult to turn into action. • As SystemsThinking is about the bigger picture, often the interventions developed or the tools designed may turn out to be complex in itself.
- 37. Challenges for ‘SystemsThinking’in Health System: • Engaging ‘street level’ policy implementer or ‘street level bureaucrats’ at the design stage of new interventions • Aligning priorities among multiple stakeholders • Coordination with and among the partners • Fulfilling and living up to the expectations of system stakeholders • Building capacity at the country level • Poor availability and quality of data • Limited multi-disciplinary skills and weak collaborations in different sectors
- 38. References • https://www.coursera.org/learn/systems-thinking/home/week/1 • https://publichealthnetwork.cymru/topic/systems-thinking-in-public-health/ •https://health-policy-systems.biomedcentral.com/articles/10.1186/1478-4505-12-51 • https://www.researchgate.net/publication/7323596_Systems_Thinking_and_Modeling_for_Public_He alth_Practice • Peters, D.H.The application of systems thinking in health: why use systems thinking?. Health Res Policy Sys 12, 51 (2014). https://doi.org/10.1186/1478-4505-12-51 • Savigny, Donald de, Adam, Taghreed, Alliance for Health Policy and Systems Research & World Health Organization. (2009). Systems thinking for health systems strengthening / edited by Don de Savigny andTaghreed Adam.World Health Organization. https://apps.who.int/iris/handle/10665/44204 • McNab D, McKay J, Shorrock S, et al Development and application of ‘systems thinking’ principles for quality improvement BMJ Open Quality 2020;9:e000714. doi: 10.1136/bmjoq-2019-000714 • https://www.publichealthnotes.com/systems-thinking-for-health-system-strengthening/ • https://www.sciencedirect.com/science/article/abs/pii/S0022437522001529
- 39.
Editor's Notes
- #4 Rather than use implicit models, systems thinking methods: Use explicit models Identify assumptions Use data Can be repeated by others Contribute to an understanding of how “things stand together” (sunistánai ) as a whole
- #10 Converge due to emergent behaviour and nonlineraity
- #11 For strengthening of health systems there is franmework or building blocks by WHO
- #12 What’s Wrong with this Model of a Health System?
- #21 a picture of a network of HIV transmission, and you can see that there's one hub that was particularly more important than others.
- #36 Systems Thinking is necessary because it will help to: Explore the problems in the health system from the systems perspective Identify solutions that work across sub-systems Promote dynamic networks of diverse stakeholders Inspire and encourage learning from each other Strengthen more system-wide planning, evaluation and research. To think holistically about the consequences and different stakeholders