Computer model presents overbooking strategies to use when patients are no-show

The no-show rate and cancellation issues at clinics have been under scrutiny by researchers because they present a significant impact on cost and resource allocation. A recent paper published in the International Journal of Engineering Management and Economics presented a computer model to help assess current clinic performance under various no-show rates and patterns and test several overbooking strategies to improve clinic’s efficiency and enhance performance.

Researchers collected data from a US-based general practice clinic that operated from 8 am to 5 pm with 1-hour lunch from 12 pm to 1 pm, scheduling patients every 15 minutes and treating a patient every 15 minute on average. Eight scenarios were simulated so researchers could analyze the variability in scheduling and treatment times, the impact of patients reneging and walk-in patients. Researchers also developed a unified clinic utility function that analyzed the impact of overbooking on patients treated, utilization and wait time.

Researchers found that variability in arriving and treatment times disturbed clinical operation and resulted in fewer patients treated per day with longer waiting time and reduced utilization. Variability in treatment time also had a bigger negative impact vs. variability in patients’ inter-arrival times. The number of reneged patients decreased and the number of treated patients’ waiting time improved as the percentage of patients’ no-show increased, according to study results. However, with appointment overbooking, researchers saw an increase in patient waiting time and patient reneging.

Greater utility was found with overbooking when no-show rates were high because of the increased improvement opportunity. Researchers found that the best overbooking strategy was to overbook a patient periodically at double the treatment time when a clinic has patient-based dynamic overbooking with high no-show rates.

“The clinic manager has to assess the financial situation of the clinic and select the most effective overbooking strategy to improve clinic performance. Reducing variability in service time first and later in patient’s arrival times would be a major recommendation in this regard,” the researchers concluded. “The proposed simulation-based overbooking model accommodates a wide range of clinic sized and no-show rates, allowing its application in a variety of clinical practices. Other solution approaches that can also be evaluated include dynamic overbooking where overbooking rate changes with time of day and the two physician scheduling alignment.”

for more information:

Al-Aomar R, Awad M. Dynamic process modeling of patients’ no-show rates and overbooking strategies in healthcare clinics. Int J Engineering Management and Economics. 2012;3:3-21.

Disclosure: The researchers had no relevant financial disclosures.

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