A Learning Health System (LHS) promotes the patient being at the very center of his or her care. Patient coproduction of care in an LHS is enabled by a focus on improving outcomes through the use of tools and visualizations that use the harnessed knowledge obtained from every previous treatment of similar patients. Interest in the concept of LHS is growing, and there are promising results in real-world applications. Almost no research has focused on LHSs for severe mental illness (LHS4SMI). By using a user-centered system design approach, a persona and use-case scenarios were created to illustrate how schizophrenia care could be co-produced in an LHS compared to standard care in a non-LHS. The illustration highlight increased participation through decisions informed by all treatments for all similar patients through the use of user interfaces that support continuous evaluation, increased understanding, compensation for cognitive impairment and participation of next of kin in the care process. We propose that an LHS4SMIs like schizophrenia has enormous potential in enabling continuous learning, patient coproduction, and more effective care.

BACKGROUND: Co-production of health is defined as 'the interdependent work of users and professionals who are creating, designing, producing, delivering, assessing, and evaluating the relationships and actions that contribute to the health of individuals and populations'. It can assume many forms and include multiple stakeholders in pursuit of continuous improvement, as in Learning Health Systems (LHSs). There is increasing interest in how the LHS concept allows integration of different knowledge domains to support and achieve better health. Even if definitions of LHSs include engaging users and their family as active participants in aspects of enabling better health for individuals and populations, LHS descriptions emphasize technological solutions, such as the use of information systems. Fewer LHS texts address how interpersonal interactions contribute to the design and improvement of healthcare services.

OBJECTIVE: We examined the literature on LHS to clarify the role and contributions of co-production in LHS conceptualizations and applications.

METHOD: First, we undertook a scoping review of LHS conceptualizations. Second, we compared those conceptualizations to the characteristics of LHSs first described by the US Institute of Medicine. Third, we examined the LHS conceptualizations to assess how they bring four types of value co-creation in public services into play: co-production, co-design, co-construction and co-innovation. These were used to describe core ideas, as principles, to guide development.

RESULT: Among 17 identified LHS conceptualizations, 3 qualified as most comprehensive regarding fidelity to LHS characteristics and their use in multiple settings: (i) the Cincinnati Collaborative LHS Model, (ii) the Dartmouth Coproduction LHS Model and (iii) the Michigan Learning Cycle Model. These conceptualizations exhibit all four types of value co-creation, provide examples of how LHSs can harness co-production and are used to identify principles that can enhance value co-creation: (i) use a shared aim, (ii) navigate towards improved outcomes, (iii) tailor feedback with and for users, (iv) distribute leadership, (v) facilitate interactions, (vi) co-design services and (vii) support self-organization.

CONCLUSIONS: The LHS conceptualizations have common features and harness co-production to generate value for individual patients as well as for health systems. They facilitate learning and improvement by integrating supportive technologies into the sociotechnical systems that make up healthcare. Further research on LHS applications in real-world complex settings is needed to unpack how LHSs are grown through coproduction and other types of value co-creation.

Background: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS-2.0) is a self-administered instrument to assess functional impairment. It is used in the general population as well as different patient groups. However, its application to patients with psychotic disorders may be hampered by disease-specific difficulties of self-estimation. This study aimed to examine the psychometric properties of the short (12-item) WHODAS-2.0 in a naturalistic sample of outpatients attending a psychosis clinic in Gothenburg, Sweden. Methods: Annual data from two outpatient clinics registered 2016–2019 were analyzed retrospectively. The assessment of the short WHODAS-2.0 was based on the first questionnaire completed by 881 patients. Confirmatory factor analysis evaluated previously validated models. Item convergent and discriminant validity as well as internal reliability were computed. Construct validity was assessed by comparing mean differences in accord with previous research regarding patients’ characteristics associated with functioning such as advanced age, diagnosed comorbidities, antipsychotic treatment status, and symptom severity measured with PANSS-8 remission items. Results: A heterogeneous sample was obtained in terms of age (range: 20–92), various living situations, and different geographic areas of birth. Most patients (75%) had been diagnosed with psychotic disorders more than 10 years ago and the majority (89%) were on antipsychotic medication. We confirmed an adjusted two-level factor model with a single second-order disability factor and six first-order factors representing the six IFC dimensions. The WHODAS-2.0 sum score measuring general disability showed good reliability (Cronbach's alpha = 0.89). Construct validity was confirmed as older patients, patients with comorbidities, and patients in assisted living had higher WHODAS-2.0 scores. Patients with no or mild psychotic symptoms had significantly lower WHODAS-2.0 sum scores than patients with more severe symptoms. Conclusions: The findings further validate the 12-item WHODAS-2.0 in a naturalistic sample of outpatients with psychotic disorders. This study corroborates the clinical significance of the short, 12-item WHODAS-2.0 by demonstrating consistent associations between patients’ age, medical comorbidities, living situation, antipsychotic treatment status, and psychotic symptom severity.

Background

Individuals with psychotic disorders experience widespread treatment failures and risk early death. Sweden’s largest department specializing in psychotic disorders sought to improve patients’ health by developing a point-of-care dashboard to support joint planning and co-production of care. The dashboard was tested for 18 months and included more than 400 patients at two outpatient clinics.

Methods

This study evaluates the dashboard by addressing two questions:

1. Can differences in health-related outcome measures be attributed to the use of the dashboard?
2. How did the case managers experience the accessibility, use, and usefulness of the dashboard for co-producing care with individuals with psychotic disorders? 

This mixed-method case study used both Patient-Reported Outcome Measures (PROM) and data from a focus group interview with case managers. Data collection and analysis were framed by the Clinical Adoption Meta Model (CAMM) phases: i) accessibility, ii) system use, iii) behavior, and iv) clinical outcomes. The PROM used was the 12-item World Health Organization Disability Assessment Schedule (WHODAS 2.0), which assesses functional impairment and disability. Patients at clinics using the dashboard were matched with patients at clinics not using the dashboard. PROM data were compared using non-parametric statistics due to skewness in distribution. The focus group included five case managers who had experience using the dashboard with patients.

Results

Compared to patients from clinics that did not use the dashboard, patients from clinics that did use the dashboard improved significantly overall (p = 0.045) and in the domain self-care (p = 0.041). Focus group participants reported that the dashboard supported data feedback-informed care and a proactive stance related to changes in patients’ health. The dashboard helped users identify critical changes and enabled joint planning and evaluation.

Conclusion

Dashboard use was related to better patient health (WHODAS scores) when compared with matched patients from clinics that did not use the dashboard. In addition, case managers had a positive experience using the dashboard. Dashboard use might have lowered the risk for missing critical changes in patients’ health while increasing the ability to proactively address needs. Future studies should investigate how to enhance patient co-production through use of supportive technologies.

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.