Electronic Clinical Decision Support System for Stroke Risk Screening in Patients With Atrial Fibrillation in Mental Health Care: Mixed Methods Study.

Background: Electronic clinical decision support systems (eCDSSs) are key to the digital transformation of health care. Despite their growing adoption, little is known about the perspectives of mental health clinicians on the implementation of eCDSS to assist them in managing physical health conditions within mental health care settings. Objective: This study aimed to explore how clinicians in older adult mental health services manage stroke risk in patients with atrial fibrillation (AF) and comorbid serious mental illness who are admitted to the hospital under their care. It also sought to examine clinicians' views on the potential role of an eCDSS in enhancing stroke risk assessment and management. Methods: A cross-sectional mixed methods study was conducted between March and May 2023 in 3 inpatient wards for mental health of older adults at South London and Maudsley NHS (National Health Service) Foundation Trust. Health care professionals, including psychiatrists and pharmacists, participated in a web-based survey and individual semistructured interviews. Ethical approval and informed consent were obtained. A descriptive analysis was conducted on the survey data, while interview data were analyzed thematically using an inductive approach. Results: In total, 10 clinicians participated in the study. Thematic analysis revealed 2 primary themes. First, clinicians reported significant challenges in clinical practice, including difficulties accessing patient medical histories, limited expertise in managing physical health conditions, fragmented care pathways, and the impact of mental health symptoms such as psychotic beliefs on stroke prevention. Second, clinicians identified strategies to improve practice, such as embedding alerts in electronic records, establishing clear organizational policies, and providing tailored training on AF-related stroke management. Clinicians recognized the potential of an eCDSS to enhance clinical effectiveness, improve the identification of high-risk patients, ensure safer and more consistent care, and save time. However, they expressed concerns about potential risks, including rigidity in decision-making, overreliance on the tool, false positives, reduced critical thinking, annoyance, and increased workload. Conclusions: This study highlights the challenges and opportunities in managing AF-related stroke risk in mental health settings. While clinicians acknowledged the potential of an eCDSS to improve care quality and efficiency, addressing concerns about its design and implementation is essential. These insights can inform the development of eCDSS tools that effectively balance benefits with user needs, ultimately improving patient outcomes in mental health services.