The Global Value of Information: Optimal Trial Design and Decision Making Across Jurisdictions

Abstract

Value of information (VOI) methods allow decision makers to identify efficient trial design following a principle of maximising the expected value to decision makers of information from potential trial designs relative to their expected cost. In health technology assessment these methods have been applied to identify optimal trial designs within jurisdiction where decision makers face positive but uncertain incremental net benefit. However, previous applications in HTA have ignored new information arising outside of jurisdiction, implicitly making the restrictive assumption that there is only expected value from research commissioned within a jurisdiction. This paper relaxes this restrictive assumption to extend the framework and methods for optimal trial design and decision making within jurisdiction in Eckermann and Willan (2007) to allow for optimal trial design across jurisdictions. A principle of maximising the expected global value of non-rival information less expected costs of trial designs optimally allocated across jurisdictions allows identification of optimal decision making within jurisdictions and optimal trial design across jurisdictions. For non-rival trial information, estimates of expected value of sample information (EVSI) for each jurisdiction conditional on prior incremental net benefit (INB) and the context of adoption or delay are able to be summed across jurisdiction. Direct and opportunity costs of trial design can be minimised in allocating trial sample across jurisdictions. These principles and methods are illustrated in identifying optimal trial design for decision making across North America, the UK and Australia in the case of early versus late external cephalic version. The expected net gain (ENG) of locally optimal trial designs of US$0.72 million is shown to increase to US$1.14 million with optimal trial design across these jurisdictions. In general, the proposed method of global optimal trial design is shown to improve on optimal trial design within jurisdictions by: (i) Reflecting the global value of non-rival information; (ii) Allowing optimal allocation of trial sample across jurisdiction; (iii) Avoiding sub-optimal spreading of fixed costs and heterogeneity of trial information with multiple trials and; (iv) Permitting adoption and trial (AT) in jurisdictions with expected positive net clinical benefit, without AT being infeasible or unethical. Consequently, provided evidence can be translated across jurisdictions, optimal global trial design following the identified principles and methods increases ENG from any set of locally optimal trial designs. Eckermann S, Willan A. Expected Value of Information and Decision Making in HTA. Health Economics 16:195-209 (2007).