Developing a case management program and clinical practice for high-risk sudden cardiac death patients through the lens of family systems theory
Year: 2026
Type: article
Study design: Clinical Trial
Abstract: Objective To develop a case management plan for patients at high risk of sudden cardiac death (SCD) from the perspective of family systems theory and evaluate its clinical practice effects. Methods By using the random sampling method, 100 patients at high risk of SCD who visited our hospital from March 2025 to June 2025 were selected as the research subjects. They were randomly divided into an experimental group ( n = 50) and a control group ( n = 50). The control group received routine care and follow-up, while the experimental group implemented a case management plan based on the family systems theory, with both interventions lasting for one year. Both groups were evaluated at baseline and endpoint using disease cognition assessments, the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Tampa Scale for Kinesiophobia Heart (TSK-SV Heart), General Self-Efficacy Scale (GSES), Family APGAR, and Major Adverse Cardiac Events (MACE). Results There were no statistically significant differences in baseline data between the two groups ( P > 0.05). After the intervention, the experimental group showed significantly better scores in disease cognition, PHQ-9, GAD-7, TSK-SV Heart, GSES, APGAR, and MACE compared to the control group ( P < 0.05). Conclusion The case management plan for high-risk SCD patients based on family systems theory is scientifically sound and feasible. It can effectively reduce anxiety and depression, alleviate kinesiophobia, improve disease cognition, and promote family care, thereby improving the patients’ quality of life and prognosis.
Institutions: Beijing Tsinghua Chang Gung Hospital, Tsinghua University
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7221781442
