Reflecting on the efficacy of cognitive mapping for decision-making in intellectual disability care: a case study

Abstract

The central aspect of this study is a set of reflections on the efficacy of soft operational research techniques in understanding the dynamics of a complex system such as intellectual disability (ID) care providers. Organizations providing services to ID patients are complex and have many interacting stakeholders with often different and competing interests. Understanding the causes for failures in complex systems is crucial for appreciating the multiple perspectives of the key stakeholders of the system. Knowing the factors that adversely affect delivery of a patient-centred care by ID provider organizations offers the potential for identifying more effective resource-allocation solutions. The authors suggest cognitive mapping as a starting point for system dynamics modelling of optimal resource-allocation projects in ID care. The application of the method is illustrated via a case study in one of the ID care providers in the Netherlands. The paper discusses some of the practical implications of applying problem-structuring methods that support gathering feedback from vulnerable service users and front-line workers. The authors concluded that cognitive mapping technique can assist the management of healthcare organizations in strategic decision-making.

Using Cognitive Mapping and Qualitative System Dynamics to Support Decision Making in Intellectual Disability Care

“…Verifying a causal network by communicating it back to interviewees is a good way to strengthen the validity of the findings (Miles & Huberman, 1994). The CLD diagram (see Figure 3) and other results of analysis of cognitive maps (Duryan et al, 2013) supported debate among senior managers of the organization leading to identification of the most important aspects of the problems to be resolved to satisfy key stakeholders of the organization.…”

“…However, as there are delays involved with the feedbacks, it is not always possible to immediately see the impact of these actions in the long run (Duryan et al., ). For instance, as the interviews with the stakeholders demonstrated, frequent shifts cause stress to group leaders and the clients and could lead to increase in number of employee turnover (Duryan, Nikolik, van Merode, & Curfs, ). Thus, inefficient allocation of resources, especially considering their insufficiency and also fluctuations in the demand for services, may lead to a loss of capacity (Vissers, Bertrand, & De Vries, ).…”

“…The links between nodes on the cognitive map represent logical implications between the concepts. For example, the node 17 “be more transparent about strategic changes in the organization” influences the node 16 “improve bottom up and top down communication.” Then, individual cognitive maps were merged into two maps reflecting the individual views of family members and group leaders to provide a framework for group discussions (Duryan et al., ). The merged maps were reviewed, corrected, and elaborated with the group leaders and family members during group discussions conducted in small teams.…”

“…The merged cognitive maps were analyzed with the help of Decision Explorer software (Duryan et al., ). To identify the primary issues the organization should overcome to be able to deliver client‐centered care (from perspectives of the key stakeholders), we have chosen the most valuable analytic tools for the case study (Head, Centrality, Domain, Hierarchical cluster, Potency and Cotail analyses) (Duryan et al., ). In addition to that, Decision Explorer helped detecting causal feedback loops as perceived by the interviewees (Figure ).…”

“…After becoming aware of the results of the analysis of the merged cognitive maps (Duryan et al., ), the senior management was convinced that the reduction of the “flex pool” shifts was of high importance. One of the ways to reduce the shifts suggested by the directors was organizing a special group of “flex pool” workers who would replace group leaders on sick leave (only 20% of the workers in comparison with 70% as it is now).…”