Waiting time information services: how well do different statistics forecast a patient's wait?

Area of Science:

• Health Services Research
• Public Health
• Surgical Outcomes Analysis

Background:

• Accurate prediction of patient waiting times is crucial for managing elective surgery services.
• Web-based information services aim to provide transparency regarding surgical waiting lists.
• Previous research has not fully evaluated the predictive accuracy of disseminated statistics.

Purpose of the Study:

• To assess the accuracy of various statistics in predicting patient waiting times for elective surgery.
• To identify factors influencing the reliability of web-based waiting time information.
• To evaluate the performance of commonly used forecasting statistics.

Main Methods:

• Analysis of elective surgery activity and waiting list data from a public hospital in Sydney, Australia (July 1995 - June 1998).
• Inclusion of data from 46 surgeons across 10 surgical specialties.
• Evaluation of the predictive accuracy of different statistical measures used in web-based services.

Main Results:

• The accuracy of tested statistics varied significantly.
• Waiting list characteristics and surgeon behavior were more influential than statistical derivation methods.
• Commonly used statistics demonstrated poor forecasting ability for patients facing waits exceeding six months.

Conclusions:

• Current web-based waiting time statistics may not reliably predict patient wait times, especially for long waiting lists.
• Surgeon-specific waiting list dynamics are critical determinants of actual patient wait times.
• Improvements in forecasting accuracy require consideration of factors beyond statistical calculation methods.