Patient queue analysis as a component of Lean Six Sigma improvement in healthcare processes: a case study from a chemotherapy day unit.

Purpose: Oncology patients are a vulnerable group that faces multiple challenges, aggravated by long waiting times and service queues. This article aims to use Lean Six Sigma (LSS) to improve the chemotherapy preparation process and prospectively study the patient files' queue dynamics to prioritise process improvement remedies against adding resources strategy.

Design/methodology/approach: Six Sigma methodology has been employed together with Lean tools and queue dynamics in a case study research in a chemotherapy day unit to define, measure, analyse, improve and control the problematic process. The study population involved all internal customers and a sample of external customers (n = 450). The study processes were measured by 25 data points.

Findings: The most frequent problem was the "Long waiting time from oncologist assessment till receiving chemotherapy". Mean value-added time for chemotherapy preparation was 42 min, the defect was any patient's waiting time exceeding it. The average pre-intervention waiting time was 65.5 ± 27.20 min. The defect baseline sigma level was 0.78 sigma. Remedies involved assigning two pharmacists, arranging the pharmacy setting to satisfy chemotherapy preparation steps, adjusting the number of patients/hours, standardising patients' files interarrival time, delivering files to the pharmacy by piece, not by batch, and fixing the printers and landlines. Post-intervention mean patient waiting time was reduced significantly to 58.7 ± 23.44 min (p-value = 0.05), and the defect sigma level was raised to 0.91 sigma.

Research limitations/implications: This study draws attention to prioritising process improvement remedies in complex care settings with long queues.

Social implications: This study enhances service delivery and customer satisfaction.

Originality/value: This study serves as one of the few publications to study patient queue behaviour as a part of LSS improvements in healthcare projects.