Signature
ENBS_w = EVSI_pop - C_n - N_w * max(INB, 0)
| Inputs | Definition | Unit |
|---|---|---|
EVSI_pop | Population expected value of sample information of the design, from HE-FM-EVSI-004 | currency |
C_n | Expected total cost of the design, from HE-FM-ENBS-002 | currency |
N_w | Number of people treated outside the study between its start and its report, who cannot receive the new treatment under only in research | people |
INB | Expected incremental net benefit per person of the new treatment over standard care on current information | currency per person |
ENBS_w | Expected net benefit of sampling of the design after the cost of waiting outside the study | currency |
|---|
Function
Expected net benefit of sampling as population sample information less the cost of a study
Maps one proposed study design, through its population expected value of sample information and its expected total cost, to the expected net benefit of sampling, the net value of that study. Per-person EVPI and its population form are on the Value of Information page (HE-FM-VOI-001 and HE-FM-VOI-002), and the expected net benefit that fixes the current decision is on the Expected Net Benefit page (HE-FN-ENB-001). EVSI is defined on the EVSI page (HE-FN-EVSI-001), and population EVSI, per-person EVSI scaled by the discounted beneficiary population, is HE-FM-EVSI-004 there. This package adds ENBS for one design, the expected cost of a study with the opportunity loss to participants, the cost of waiting under only in research, the ceiling set by population EVPI and a search for the efficient sample size. Notation follows the Expected Net Benefit of Sampling article.
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Implementations
Excel
ENBS under only in research in one Excel cell
With population EVSI in PopulationEVSI, the study cost in StudyCost, the number waiting in WaitingPatients and the expected incremental net benefit in ExpectedINB, MAX sets the waiting cost to zero when the new treatment is not expected to be better.
=PopulationEVSI-StudyCost-WaitingPatients*MAX(ExpectedINB,0)
Assumptions
New treatment withheld outside the study under only in research
Fenwick and colleagues explain that restricting a technology to people in research avoids committing irrecoverable costs, while patients outside the study would not have access to it and could miss the best treatment. McKenna and Claxton separate the effect of the research decision on patients enrolled, on those not enrolled and on those treated after the trial reports.
Population EVSI held fixed across access arrangements
The article's example keeps population EVSI the same under both arrangements. Fenwick and colleagues adjust the beneficiary population for the time the study takes and for patients enrolled when the reimbursement decision is delayed, so a full analysis also recomputes EVSI_pop for each design.
Worked examples
Article's 600-patient trial under only in research
In the article's illustrative example 2,000 people treated outside the 600-patient trial while it runs miss GBP 200 each, adding GBP 400,000 to the cost. ENBS falls to GBP 540,000.
EVSI_pop = 2400000; C_n = 1460000; N_w = 2000; INB = 200; ENBS_w = 540000
Article's 300-patient trial under only in research
The 300-patient trial reports sooner, with 1,000 people waiting, so its ENBS becomes GBP 570,000 and the smaller trial is now efficient, as in the article.
EVSI_pop = 1600000; C_n = 830000; N_w = 1000; INB = 200; ENBS_w = 570000
Article's 600-patient trial under approval with research
With approval with research nobody waits, N_w is zero and the formula returns the ENBS of GBP 940,000 from the article's table, a limiting case that checks the implementation.
EVSI_pop = 2400000; C_n = 1460000; N_w = 0; INB = 200; ENBS_w = 940000
Common errors
Cost of waiting left out under only in research
Ignoring the people who wait outside the study keeps the 600-patient trial as the efficient design at GBP 940,000. Under only in research it is worth GBP 540,000 and the 300-patient trial, worth GBP 570,000, is the better choice.
Waiting cost charged when the new treatment is expected to be worse
If the expected incremental net benefit were minus GBP 200, people outside the study would receive standard care, the expected best option, and lose nothing by waiting. Using the absolute value would wrongly subtract GBP 400,000 for 2,000 people waiting (computed here for illustration).
Sources
Only in research, irrecoverable costs and the beneficiary population
Fenwick E, Steuten L, Knies S, et al. Value of information analysis for research decisions, an introduction. Report 1 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force. Value in Health. 2020;23(2) 139-150. Introduction on only in research, which avoids committing irrecoverable costs while patients not involved in the research lack access to the new technology, and the section on establishing whether more research is potentially worthwhile with good practice recommendation 4, where the beneficiary population is adjusted for the time a study takes to finish and for patients enrolled if the reimbursement decision is delayed.
HEMA report on research warranted only when it repays the health forgone by waiting
Steuten L, Thavorn K, Cipriano LE, et al. Methods to Analyze and Present Uncertainty in Economic Evaluation to Support HTA Decisions (HEMA Report 2). Health Economics Methods Advisory; 2026. Section 5.4, page 36, where further research, only in research or managed access where routine adoption is compatible, is warranted only where the expected value of resolving the uncertainty exceeds the cost of that research and of the health forgone by waiting, where ENBS is positive.
Time to report and the population that benefits from a trial
Eckermann S, Willan AR. Time and expected value of sample information wait for no patient. Value in Health. 2008;11(3) 522-526. Abstract, checked on PubMed (18179665), where the number of patients who benefit from trial information is reduced by those treated outside and within the trial until the evidence is updated, lowering EVSI and the expected net gain at any trial size.
Adoption and research design decisions taken together
McKenna C, Claxton K. Addressing adoption and research design decisions simultaneously, the role of value of sample information analysis. Medical Decision Making. 2011;31(6) 853-865. Abstract, checked on PubMed (21393558), which distinguishes the effect of the research decision on patients enrolled in the trial, those not enrolled and those treated once it reports, and examines whether approval should be withheld until research reports.
Canonical Identity
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