Nurse Performance and Influence Factors in Discharge Planning Based on Knowledge Management SECI Model in Stroke Patients

Background: Implementation of discharge planning was found to be unsystematic and structured in stroke patients, resulting in gaps in knowledge transfer and knowledge between nurses, patients, and families regarding discharge planning directives. Discharge planning based on the Knowledge management SECI model is expected to overcome information and knowledge gaps in stroke patients. This study aims to analyze the influence of nurse factors, family factors, patient factors, and organizational factors on the SECI Model knowledge management-based discharge planning in Jombang Regency, Indonesia. Design and method: This research was conducted with a cross-sectional analytic study design. A sample of 133 stroke unit nurses at Jombang District Hospital, Ploso Hospital, and Jombang Hospital, was then analyzed and interpreted to test the model with SEM-PLS. Results: Nurse factors influence discharge planning (t-statistic 2.484 > 1.96 and p-value 0.014 <0.05). Patient factors influence knowledge management (t-statistic 2.582 > 1.96 and p-value 0.011 <0.05). Family factors influence knowledge management and discharge planning (t-statistic 21.207 > 1.96 and p-value 0.000 <0.05). Organizational factors influence knowledge management and discharge planning (t-statistic 2.504 > 1.96 and p-value 0.013 <0.05). Knowledge management influences discharge planning (t-statistic 6.618 > 1.96 and p-value 0.000 <0.05). Conclusion: The research findings prove that nurse factors, patient factors, family factors, and organizational factors influence discharge planning based on the SECI knowledge management model.