Value-based Clinical Trials: Selecting Recruitment Rates and Trial Lengths in Different Regulatory Contexts

65 Pages Posted: 2 Sep 2021

See all articles by Andres Alban

Andres Alban

MGH Institute for Technology Assessment, Harvard Medical School

Stephen E. Chick

INSEAD - Technology and Operations Management

Martin Foster

affiliation not provided to SSRN

Date Written: August 31, 2021

Abstract

Health systems are placing increasing emphasis on improving the design and operation of clinical trials, with the aim of making the health technology adoption process more value-based. We present a model of a value-based two-armed clinical trial in which both the recruitment rate and trial length are optimized. The model is value-based because it balances the cost of the trial with the expected benefit it generates for patients, valued by the relative health benefits and costs of the technologies. We consider a wide range of regulatory and practical contexts which address how patient health is valued (discount rate, time horizon, pragmatic trials, adaptive designs). We present comparative statics and asymptotic analysis, together with a retrospective application to a recent health technology assessment, and an extension for adaptive trials. Results challenge traditional perceptions concerning the efficiency, length, and knowledge that may be gained from clinical research for trial managers or funders charged with delivering value efficiently: we highlight trade-offs between trial costs and population health benefits influenced by trial outcomes and the importance of optimizing both recruitment rate and trial duration rather than sample size alone.

Keywords: Clinical Trials, Health Technology Assessment, Cost-effectiveness, Health Economics, Bayesian Statistics, Value of Information

Suggested Citation

Alban, Andres and Chick, Stephen E. and Foster, Martin, Value-based Clinical Trials: Selecting Recruitment Rates and Trial Lengths in Different Regulatory Contexts (August 31, 2021). INSEAD Working Paper No. 2021/46/TOM, Available at SSRN: https://ssrn.com/abstract=3914670 or http://dx.doi.org/10.2139/ssrn.3914670

Andres Alban

MGH Institute for Technology Assessment, Harvard Medical School ( email )

101 Merrimac Street
Boston, MA 02114
United States

Stephen E. Chick (Contact Author)

INSEAD - Technology and Operations Management ( email )

Boulevard de Constance
77 305 Fontainebleau Cedex
France

HOME PAGE: http://faculty.insead.edu/chick/

Martin Foster

affiliation not provided to SSRN

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
72
Abstract Views
297
rank
440,103
PlumX Metrics