Operations research methods improve chemotherapy patient appointment scheduling

Pablo Santibáñez, Ruben Aristizabal, Martin L Puterman, Vincent S Chow, Wenhai Huang, Christian Kollmannsberger, Travis Nordin, Nancy Runzer, Scott Tyldesley
Joint Commission Journal on Quality and Patient Safety 2012, 38 (12): 541-53

BACKGROUND: Clinical complexity, scheduling restrictions, and outdated manual booking processes resulted in frequent clerical rework, long waitlists for treatment, and late appointment notification for patients at a chemotherapy clinic in a large cancer center in British Columbia, Canada. A 17-month study was conducted to address booking, scheduling and workload issues and to develop, implement, and evaluate solutions.

METHODS: A review of scheduling practices included process observation and mapping, analysis of historical appointment data, creation of a new performance metric (final appointment notification lead time), and a baseline patient satisfaction survey. Process improvement involved discrete event simulation to evaluate alternative booking practice scenarios, development of an optimization-based scheduling tool to improve scheduling efficiency, and change management for implementation of process changes. Results were evaluated through analysis of appointment data, a follow-up patient survey, and staff surveys.

RESULTS: Process review revealed a two-stage scheduling process. Long waitlists and late notification resulted from an inflexible first-stage process. The second-stage process was time consuming and tedious. After a revised, more flexible first-stage process and an automated second-stage process were implemented, the median percentage of appointments exceeding the final appointment notification lead time target of one week was reduced by 57% and median waitlist size decreased by 83%. Patient surveys confirmed increased satisfaction while staff feedback reported reduced stress levels.

CONCLUSION: Significant operational improvements can be achieved through process redesign combined with operations research methods.

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