A Practical Guide to Value of Information Analysis

Abstract

Value of information analysis is a quantitative method to estimate the return on investment in proposed research projects. It can be used in a number of ways. Funders of research may find it useful to rank projects in terms of the expected return on investment from a variety of competing projects. Alternatively, trialists can use the principles to identify the efficient sample size of a proposed study as an alternative to traditional power calculations, and finally, a value of information analysis can be conducted alongside an economic evaluation as a quantitative adjunct to the 'future research' or 'next steps' section of a study write up. The purpose of this paper is to present a brief introduction to the methods, a step-by-step guide to calculation and a discussion of issues that arise in their application to healthcare decision making. Worked examples are provided in the accompanying online appendices as Microsoft Excel spreadsheets.

The Community IntraVenous Antibiotic Study (CIVAS): a mixed-methods evaluation of patient preferences for and cost-effectiveness of different service models for delivering outpatient parenteral antimicrobial therapy

“…Should the EVPI exceed the expected research cost for reducing uncertainty then investment in research is recommended. 163 We assumed that the population that could benefit from the services to be 21,000 patients with short-term infections. This figure is based on the assumption that 70,000 patients per year are hospitalised with SSTIs 164 and approximately one-third of these could be eligible for IVA.…”

Economic Evaluation Alongside a Randomized Controlled Crossover Trial of Modified Group Cognitive–Behavioral Therapy for Anxiety Compared to Treatment-as-Usual in Adults With Asperger Syndrome

“…EVSI was estimated by first calculating the expected reduction in variance of mean INB from a trial of sample size n s per arm and then multiplying by the unit normal loss (i.e., the proportion of the INB distribution that is associated with negative values) and the potentially beneficial population (total eligible population less those enrolled in the study). 26 The expected net gain of sampling (ENGS) for a wide range of sample sizes ( n s ) was then estimated by subtracting the cost of sampling from the EVSI to determine the optimal n s that maximizes the ENGS. The cost of sampling was estimated based on the research costs incurred during the conduct of the PAsSA trial and categorized by fixed and variable costs (£218,375/trial and £966/participant respectively).…”

The economic case for precision medicine

“…Additional research has the potential benefit of reducing decision uncertainty and ‘value of information’ methods can provide a quantitative estimate of whether such research has value in reducing uncertainty in the economic evidence base [89,90]. Further research has value, in the context of relative cost-effectiveness, if its expected cost is less than its expected benefit.…”