[Use of the Lean methodology in the management of cancer patients in a University Hospital, Italy: First results]. / Applicazione di logiche lean nella gestione del paziente oncologico: primi risultati della sperimentazione in un policlinico universitario.

ABSTRACT

AIM: The aim of this study was to map a patient's journey along all stages of his daily care path in an Oncology outpatient department, to identify and eliminate "bottleneck" situations that interfere with the patient's flow of care. The main key performance indicators used in the study were waiting times for each stage of the care process, time required for each activity, and resources used. METHODS: The study was conducted from 17-30 January 2018 at the medical oncology clinic of a large university teaching and research hospital in Italy. We analyzed all the healthcare services provided during the monitoring period, dividing them into first appointments, therapy, visits for adjustments of the therapeutic plan, visits for i.v. therapy, visits for oral therapy, follow-up visits, other visits (e.g. for positioning of peripherally inserted central catheter). Data collection was performed by administering two questionnaires a Patient Journey (PJ) questionnaire to patients and a Medical Journey (MJ) questionnaire to clinicians. This project employed Lean principles in order to view the process and specify value through the patient's point of view, identify waste in processes and eliminate any steps lacking any added value, reduce variation of and leveling workload to improve quality and ?ow of care, engage patients and staff to redesign the process. RESULTS: The response rate in 1351 outpatients who were invited to participate was 63%; for doctors it was 81%. The mean waiting time for first visits and follow up visits performed in a single day was 50 minutes. An audit process was thus performed and a series of quality improvement measures were defined and shared with health professionals. CONCLUSIONS: The Lean methodology could provide a robust framework for improved understanding and management of complex system constraints in outpatient oncology clinics, and could result in improved access to treatment and reduced waiting times for patients.