Quantitative Assessment on Waiting Time in Quality Assurance of Screening Program With Application to Taiwanese Population-Based Organized Service Colorectal Cancer Screening

Abstract

Background: In a population-based organized service colorectal cancer (CRC) screening program, waiting time for confirmatory diagnosis for those who screened as positive test would be affected by coverage rate, positive rate, and compliance rate given clinical capacity of different settings. Long waiting time might cause the anxiety of patient and affect the quality of life. It is an essential index in the quality assurance of screening program. Aim: We aim to project the waiting time in different scenarios by changing the joint effect of these 3 factors (coverage rate, positive rate, and compliance rate). Methods: We proposed a stochastic process for modeling a complicated structure of screening data containing arrival rate for attending screening (coverage rate), positive rate, compliance rate, and waiting time for confirmatory diagnosis. It was applied to Taiwanese nationwide CRC screening program during the period of 2004 to 2009. The estimated parameters were used to project the waiting time by changing different scenarios. Results: Given positive rate and compliance rate, the waiting time was lengthened with increasing coverage rate. Under the similar scenario with Taiwanese nationwide population-based screening (7% of positive rate and 60% of compliance), the waiting time expanded from 10 days to 101 days as the coverage rate increased by 10-fold (from 5% to 50%). If the referral policy allows 2 months of waiting time for follow-up confirmatory, a 3-year CRC screening program can reach to 90% of coverage rate. If positive rate increases as a result of the cutoff value or compliance rate is enhanced, the waiting time can be prolonged in a quantitative manner. Conclusion: Waiting time for confirmatory examination usually plays an important role in the assessment of the quality assurance of screening program. After considering the change of 3 joint effects on coverage rate, positive rate, and compliance rate, we can project the waiting time and provide a quantitative assessment on referral policy to improve the quality of service for decision-maker.