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Updated: Dec 23, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Using Complexity Assessment to Inform the Development and Deployment of a Digital Dashboard for Schizophrenia Care:
Andreas Gremyr1,2, Boel Andersson Gäre2,3, Trisha Greenhalgh4
1Department of Schizophrenia Spectrum Disorders (Psykiatri Psykos), Sahlgrenska University Hospital, Mölndal, Sweden.
Background:
Health care is becoming more complex. For an increasing number of individuals, interacting with health care means addressing more than just one illness or disorder, engaging in more than one treatment, and interacting with more than one care provider. Individuals with severe mental illnesses such as schizophrenia are disproportionately affected by this complexity. Characteristic symptoms can make it harder to establish and maintain relationships. Treatment failure is common even where there is access to effective treatments, increasing suicide risk. Knowledge of complex adaptive systems has been increasingly recognized as useful in understanding and developing health care. A complex adaptive system is a collection of interconnected agents with the freedom to act based on their own internalized rules, affecting each other. In a complex health care system, relevant feedback is crucial in enabling continuous learning and improvement on all levels. New technology has potential, but the failure rate of technology projects in health care is high, arguably due to complexity. The Nonadoption, Abandonment, and challenges to Scale-up, Spread, and Sustainability (NASSS) framework and complexity assessment tool (NASSS-CAT) have been developed specifically to help identify and manage complexity in technology-related development projects in health care.
Objective:
This study aimed to use a pilot version of the NASSS-CAT instrument to inform the development and deployment of a point-of-care dashboard supporting schizophrenia care in west Sweden. Specifically, we report on the complexity profile of the project, stakeholders' experiences with using NASSS-CAT, and practical implications.
Methods:
We used complexity assessment to structure data collection and feedback sessions with stakeholders, thereby informing an emergent approach to the development and deployment of the point-of-care dashboard. We also performed a thematic analysis, drawing on observations and documents related to stakeholders' use of the NASSS-CAT to describe their views on its usefulness.
Results:
Application of the NASSS framework revealed different types of complexity across multiple domains, including the condition, technology, value proposition, organizational tasks and pathways, and wider system. Stakeholders perceived the NASSS-CAT tool as useful in gaining perspective and new insights, covering areas that might otherwise have been neglected. Practical implications derived from feedback sessions with managers and developers are described.
Conclusions:
This case study shows how stakeholders can identify and plan to address complexities during the introduction of a technological solution. Our findings suggest that NASSS-CAT can bring participants a greater understanding of complexities in digitalization projects in general.
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