Dataset Information

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

ABSTRACT: 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.

SUBMITTER: Rothery C

PROVIDER: S-EPMC7373630 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

Rothery Claire C Strong Mark M Koffijberg Hendrik Erik HE Basu Anirban A Ghabri Salah S Knies Saskia S Murray James F JF Sanders Schmidler Gillian D GD Steuten Lotte L Fenwick Elisabeth E

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 20200301 3

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 w ...[more]

PMID: 32197720

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Project description:Recent advances in instrumentation have moved analytical ultracentrifugation (AUC) closer to a possible validation in a Good Manufacturing Practices (GMP) environment. In order for AUC to be validated for a GMP environment, stringent requirements need to be satisfied; analysis procedures must be evaluated for consistency and reproducibility, and GMP capable data acquisition software needs to be developed and validated. These requirements extend to multiple regulatory aspects, covering documentation of instrument hardware functionality, data handling and software for data acquisition and data analysis, process control, audit trails and automation. Here we review the requirements for GMP validation of data acquisition software and illustrate software solutions based on UltraScan that address these requirements as far as they relate to the operation and data handling in conjunction with the latest analytical ultracentrifuge, the Optima AUC by Beckman Coulter. The software targets the needs of regulatory agencies, where AUC plays a critical role in the solution-based characterization of biopolymers and macromolecular assemblies. Biopharmaceutical and regulatory agencies rely heavily on this technique for characterizations of pharmaceutical formulations, biosimilars, injectables, nanoparticles, and other soluble therapeutics. Because of its resolving power, AUC is a favorite application, despite the current lack of GMP validation. We believe that recent advances in standards, hardware, and software presented in this work manage to bridge this gap and allow AUC to be routinely used in a GMP environment. AUC has great potential to provide more detailed information, at higher resolution, and with greater confidence than other analytical techniques, and our software satisfies an urgent need for AUC operation in the GMP environment. The software, including documentation, are publicly available for free download from Github. The multi-platform software is licensed by the LGPL v.3 open source license and supports Windows, Mac and Linux platforms. Installation instructions and a mailing list are available from ultrascan.aucsolutions.com.

Dataset Information

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

Publications

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

Similar Datasets

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