Value-based Clinical Trials: Selecting Recruitment Rates and Trial Lengths in Different Regulatory Contexts
Autor: | Andres Alban, Stephen E. Chick, Martin Forster |
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Přispěvatelé: | Andres Alban, Stephen Chick, Martin Forster |
Rok vydání: | 2021 |
Předmět: |
History
Health economics Actuarial science Polymers and Plastics Computer science Cost effectiveness Strategy and Management cost-effectivene Health technology clinical trial Time horizon Population health Management Science and Operations Research Trial Length Industrial and Manufacturing Engineering Value of information health economics Bayesian statistics value of information Clinical trial health technology assessment Business and International Management |
Zdroj: | SSRN Electronic Journal. |
ISSN: | 1556-5068 0025-1909 |
DOI: | 10.2139/ssrn.3914670 |
Popis: | 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 that address how patient health is valued (discount rate, time horizon, pragmatic trials). 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. This paper was accepted by Stefan Scholtes, health. |
Databáze: | OpenAIRE |
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