An Economic Model for Estimating Trial Costs with an Application to Placebo Surgery Trials

Journal article

BACKGROUND AND OBJECTIVE: Waste in clinical trials remains rife. We developed an economic model to predict the cost of trials based on input costs, duration, power, number of sites, recruitment eligibility and consenting rates. METHODS: We parameterised the model for three proxy placebo-controlled surgical trials using data from a systematic review, a bespoke cost survey, and from the literature. We used the model to compare target and actual trial performance for (i) a trial that was completed on time but with more sites, (ii) a trial that completed after a time extension, and (iii) an incomplete trial. RESULTS: Successful trials more accurately anticipated the true recruitment rate that they achieved and those that overestimated this were most likely to fail. The costs of overestimating recruitment rates were dramatic: all proxy trials had significantly higher costs than planned, with additional funding of at least AUD$600,000 (50% above budget) required for trials that completed after adding more sites or more time, and over AUD$2 million (260% above budget) for incomplete trials. CONCLUSIONS: This model shows the trade-offs between time and cost, or both, when recruitment is lower than anticipated. Greater consideration is needed to improve trial planning, reviewing, and funding of these trials to avoid costly overruns and incomplete trials.

Authors: Schilling, C; Tew, M; Bunzli, S; Shadbolt, C; Lohmander, LS

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: Applied Health Economics and Health Policy
• Volume: 21
• Issue: 2
• Pages: 263-273
• Publication date: 2022-12-28
• DOI: 10.1007/s40258-022-00775-4
• EISSN: 1179-1896
• ISSN: 1175-5652
• Language: English
• Keywords: Alternative medicine; Internal medicine; Public health; Health economics; Quality of Life Research; Proxy (statistics); Business; Bespoke; Placebo; Nursing; Cost–benefit analysis; Medicine; Computer science; Economics; Clinical trial; Actuarial science; Operations management