Efficient Scheduling of Cystoscopies in Monitoring for Recurrent Bladder Cancer
Daniel L. Kent,
Ross Shachter,
Harold C. Sox,
Ng Seok Hui,
Linda D. Shortliffe,
Susan Moynihan and
Frank M. Torti
Medical Decision Making, 1989, vol. 9, issue 1, 26-37
Abstract:
Proper timing for repeated evaluations is difficult to assess. The authors analyzed scheduling of cystoscopy to monitor patients for detection of recurrent bladder cancer assuming that 1) minimizing tumor detection delay helps prevent cancer morbidities; 2) only limited numbers of cystoscopies are available; 3) prediction of recurrence or progression to invasive cancer is uncertain; 4) future tumors recur according to a Poisson process. Assumptions 3 and 4 permit estimation of each patient's recurrence rate. Thus, patients may be compared ac cording to their relative risks of future tumors. With these assumptions, nonlinear optimization theory was used to calculate monitoring schedules for a model practice. Given 5.4 available visits per week per 100 patients, cystoscopy was recommended in 9-11 weeks for high-risk patients and in 30-40 weeks for low-risk patients, depending on stages, grades, and numbers of previous tumors. In contrast, standard cystoscopy was recommended in 13, 26, or 52 weeks, depending only on time elapsed since last recurrence. The calculated schedule implied an average detection delay for potentially invasive tumors of eight weeks, while standard practice led to detection delays of 11 weeks (38% worse). These results suggest that inclusion of each patient's tumor history in an optimization approach may improve follow-up care for patients who have superficial bladder cancers. This approach is being evaluated in a larger clinical setting.
Keywords: Key words: bladder cancer; cystoscopy; follow-up; operations research; Bayes' rule; nonlinear optimization; health services. (Med Decis Making 1989; 9:26-37) (search for similar items in EconPapers)
Date: 1989
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:9:y:1989:i:1:p:26-37
DOI: 10.1177/0272989X8900900105
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