Healthcare resource allocation decisions made under conditions of uncertainty may turn out to be suboptimal. In a resource constrained system in which there is a fixed budget, these suboptimal decisions will result in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to make better resource allocation decisions. This value can be quantified using a value of information (VOI) analysis. This report, from the ISPOR VOI Task Force, introduces VOI analysis, defines key concepts and terminology, and outlines the role of VOI for supporting decision making, including the steps involved in undertaking and interpreting VOI analyses. The report is specifically aimed at those tasked with making decisions about the adoption of healthcare or the funding of healthcare research. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing the results of VOI analyses.Keywords: decision making, expected net benefit of sampling, expected value of information, expected value of perfect information, value of information, value of research.
The allocation of healthcare resources among competing priorities requires an assessment of the expected costs and health effects of investing resources in the activities and of the opportunity cost of the expenditure. To date, much effort has been devoted to assessing the expected costs and health effects, but there remains an important need to also reflect the consequences of uncertainty in resource allocation decisions and the value of further research to reduce uncertainty. Decision making with uncertainty may turn out to be suboptimal, resulting in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to better inform resource decisions. This value can be quantified using value of information (VOI) analysis. This report from the ISPOR VOI Task Force describes methods for computing 4 VOI measures: the expected value of perfect information, expected value of partial perfect information (EVPPI), expected value of sample information (EVSI), and expected net benefit of sampling (ENBS). Several methods exist for computing EVPPI and EVSI, and this report provides guidance on selecting the most appropriate method based on the features of the decision problem. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing VOI analyses. The software needed to compute VOI is discussed, and areas for future research are highlighted.
Background: While the number of hospitalized patients in Dutch hospitals has increased since 1997, the demand for red blood cell units (RBCs) has simultaneously decreased. This implies a dramatic change in transfusion practice toward fewer blood transfusions on average per patient. Objectives: In order to explain the RBC reduction, different patient groups (surgical, medical, obstetrical, and specific age groups) were studied retrospectively in relation to RBC use. In addition, the use of combinations of RBCs, fresh frozen plasma, and platelets during a transfusion episode was examined for trends over time. Materials and methods: Data from the PROTON database, containing information on all transfusions in twelve Dutch hospitals in the period 1996-2005, including corresponding patient data (age, diagnosis, treatment, and hospitalizations) and blood unit data (type, amount, and date) were analyzed. Results: The proportion of RBCs used for surgical patients declined from 50% in 1996 to 40% in 2005, whereas medical use increased from 47% to 58% (the remaining 2%-3% went to obstetrical patients). Changes were more marked in the higher age groups. Also, a trend was observed toward the use of only one or two RBCs during a transfusion episode rather than three or more. Among surgical patients who received blood, the use of combinations of blood units, as compared to RBCs only, increased from 32% to 39%. Conclusion: The results suggest a more restrictive transfusion policy for surgical patients as well as an increase in medical indications for transfusion. This fits well with the current focus on more cost-effective transfusion policies.
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