Enhancing loco-regional adaptive governance for integrated chronic care through agent based modelling (ABM)

Introduction : Moving from existing segmented care to integrated care is complex and disruptive. It is complex in the sense that the type of changes and the timeframe of these changes are not completely predictable. It is disruptive in the sense that the process of change modifies but also is influenced by the nature of interactions at the individual and organisational level. As a consequence, building competences to govern the necessary changes towards integrated care should include capacity to adapt to unexpected situations. Therefore, the tacit knowledge of the stakeholders (“knowledge-in-practice developed from direct experience; subconsciously understood and applied”1) should be at the centre. However, the usual research and training practices using such a knowledge (i.e. action research or case studies), are highly time-consuming. New approaches are therefore needed to elicit tacit knowledge. One of them is agent based modelling (ABM)2  through computer simulation.   The aim of this paper is to make a “showcase” of an agent-based model that uses the emergence of tacit knowledge and enhances loco-regional adaptive governance for improving integrated chronic care. Theory/Methods : We used a complex adaptive system’s lens to study the health systems integration process. We applied key components of ABM to assess how health systems adapts through the dynamics of heterogeneous and interconnected agents (agents are characterised by their level of autonomy, heterogeneity, and interactions with other agents). The agent-based model was developed through a process where concept maps, causal loop diagrams, object-oriented unified modelling language diagrams and computer simulation (using Netlogo©) were iteratively used. Results : The agent-based model was presented to health professionals with variable experience in healthcare to elicit their perceptions and tacit knowledge. It  consisted of agents with certain characteristics and transition rules. Agents included providers, patients, networks’ or health systems’ managers. Agents can adopt or influence the adoption of integrated care through learning and because of being aware, motivated and capable of decision making. The environment   includes institutional arrangements (e.g., financing, training, information systems and legislation) and leadership. Different scenarios were created and discussed. Key rules to strengthen adaptive governance were reflected on. Discussion and conclusion : This study is an initial step of an exercise to use ABM as a means to elicit of and enhance tacit knowledge to strengthen governance for integrated care. It is expected that the study will foster dialogue between actors of loco-regional projects to integrate health and social care for chronic diseases in Belgium (a new program initiated by federal authorities). Suggestions for future research : Future research is expected to continue developing methods that combine ABM with participative exploration approaches to make better use of tacit knowledge in strengthening loco-regional governance for the development of integrated care. References : 1- Kothari, A. et al. The use of tacit and explicit knowledge in public health: a qualitative study. Implement. Sci. 2012;7, 20. 2- Anderson, J., Chaturvedi, A. & Cibulskis, M. Simulation tools for developing policies for complex systems: modeling the health and safety of refugee communities. Health Care Manag. Sci. 2007;10, 331–339.


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Macq, Jean ; Deconinck, Hedwig ; Van Durme, Thérèse ; Lambert, Anne-Sophie ; Karam, Marlène ; et. al. Enhancing loco-regional adaptive governance for integrated chronic care through agent based modelling (ABM) .17th International Conference on Integrated Care (Dublin, Ireland, du 08/05/2017 au 10/05/2017). http://hdl.handle.net/2078.1/184684 Le dépôt institutionnel DIAL est destiné au dépôt et à la diffusion de documents scientifiques émanant des membres de l'UCLouvain. Toute utilisation de ce document à des fins lucratives ou commerciales est strictement interdite. L'utilisateur s'engage à respecter les droits d'auteur liés à ce document, principalement le droit à l'intégrité de l'oeuvre et le droit à la paternité. La politique complète de copyright est disponible sur la page Copyright policy DIAL is an institutional repository for the deposit and dissemination of scientific documents from UCLouvain members. Usage of this document for profit or commercial purposes is stricly prohibited. User agrees to respect copyright about this document, mainly text integrity and source mention. Full content of copyright policy is available at Copyright policy Enhancing loco-regional adaptive governance for integrated chronic care through agent based modelling (ABM) Many countries (including Belgium) are attempting to Move from existing segmented care to integrated care.
It is complex in the sense that the type and timeframe of changes are not always predictable.
It is disruptive in the sense that the process of change modifies but also is influenced by the nature of interactions between agents.
Building competences to govern the necessary changes towards integrated care should consider this, particularly at loco-regional level (for networks covering between 100 000 and 500 000 people). Acknowledging the tacit knowledge and cognitive heuristic of the stakeholders is key for that learning process.
The aim of this paper is to make a "showcase" of an agent-based model (ABM) that build on and make explicit tacit knowledge and cognitive heuristics between stakeholder to enhance loco-regional adaptive governance for improving integrated chronic care.
Building competencies to govern health and social care at loco-regional level by taking into account tacit knowledge and cognitive heuristics

Making a « showcase » of ABM that foster sharing of tacit knowledge between stakeholders
We used a complex adaptive system's lens to study the health systems integration process.
Complex adaptive systems (CAS) are made of "agents" that interact, adapt, learn from experience, self-organise, and behave unpredictably. CAS are open systems. As a consequence, they are influenced by the environment and influence it.
Complex adaptive systems features amongst other the following behavior: path dependency; emergent "order", ttransition phases, causal loops, scale-free networks Generally, CAS seek equilibrium.

Using the lenses of complex adaptive system to study the health systems integration process
We applied components of ABM to assess how health systems adapts and move towards integrated care. ABM allows simulating the different behaviors of CAS.
The agent-based model was developed through a process where storytelling, concept maps, group voting process (with Wooclap ©) , object-oriented unified modelling language (UML) diagrams and computer simulation (using Netlogo ©) were iteratively used. With different groups of MPH d-students.
Story telling and UML was initially done with students following a course on "systemic approach in public health".
Based on that and on exchanges with the other authors, the main author developed progressively an ABM in Netlogo.
This was shown to student following an optional module on coordination and networks organization to improve its calibration It was finally exchanged with 1 st year MPH students to identify likely scenarios of changes and discuss it.
Simulating the behavior of a loco-regional system with Netlogo© and sharing it with MPH students to progressivelly improve it

System evolution
Chosing between best alternatives? Behavior of the system over time (centered on ratio « cost » over « health » simulated)

Sharing tacit knowledge and elicit cognitive heuristics
This is the initial step of an exercise to use ABM as a mean to take advantage and enhance tacit knowledge to strengthen governance for integrated care. It is expected that it will be used to foster dialogue between loco-regional projects to integrate health and social care for chronic diseases in Belgium (a new program initiated by federal authorities).
Future research should continue the development of methodology combining ABM with participative approaches to make better use of tacit knowledge in strengthening loco-regional governance for the development of integrated care.
Moving away from intervention evaluation towards system monitoring: promoting the development of methodology combining ABM with participative approaches to make better use of tacit knowledge