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Optimizing Early Discharge Planning in Oncology: Improving Health Service using Lean Six Sigma Methodologies
Abstract
Background
Early discharge planning (EDP) in oncology is essential for ensuring continuity of care, reducing prolonged hospital stays, and optimizing resource utilization. Prolonged hospital stays can increase the risk of infections, delay access to new admissions, and strain healthcare resources. Implementing Lean Six Sigma methodologies significantly improved discharge planning by reducing workflow inefficiencies, enhancing compliance, and optimizing resource utilization. The structured use of DMAIC and process capability analysis led to reduced hospital stays, lower bed occupancy, and improved patient transitions, highlighting LSS as a practical framework for continuous quality improvement in oncology care.
Purpose
This study aimed to improve workflow efficiency, compliance, and patient outcomes in oncology discharge planning by implementing Lean Six Sigma methodologies.
Methods
The study was conducted at the Sultan Qaboos Comprehensive Cancer Care and Research Center; this pre-and post-intervention study applied the DMAIC (Define, Measure, Analyze, Improve, Control) cycle to identify inefficiencies and implement targeted interventions. Cp (Process Capability Index) and Cpk (Process Capability Index for Centering) are key indicators used to evaluate a process's ability to meet specified limits. Length of stay, compliance rates, and bed occupancy were also analyzed. Qualitative data supplemented the findings from staff interviews and process mapping.
Results
Post-intervention, the mean compliance rate was increased to 89.54% from 68.10% (p-value <0.05). By 68.82%, the observations below 80% compliance threshold were reduced. Process capability indices improved, with Pp rising to 0.41 from 0.22 and Ppk increasing to 0.39 from -0.27. As reflected by improvements in the Z.Bench score, Variability was significantly reduced from -0.80 to 1.18. The bed occupancy rate experienced a noticeable decline to 77% in September 2024 from 95% in June 2024 (p-value <0.05). An overall decrease in the average length of stay (LOS) was shown to be 6.5 days in September 2024, compared to 9.0 days in June 2024 (p-value <0.05).
Conclusion
Implementing LSS in oncology discharge planning significantly improved process efficiency and compliance. The significant reduction in LOS reflects the success of Lean Six Sigma in enhancing efficiency, improving patient safety, and optimizing hospital resource utilization, leading to better patient outcomes in oncology care. The findings underscore the potential of Lean Six Sigma methodologies to optimize workflows and foster a culture of continuous improvement in healthcare.