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Collaborative Network for Value of Information

Here you can find our work

2019 

1. Jackson CH, Presanis AM, Conti S, De Angelis D. Value of Information: Sensitivity Analysis and Research Prioritisation in Bayesian Evidence Synthesis. Journal of the Americal Statistical Association. (In press)

Methods

2. Kunst NR, Alarid-Escudero F, Paltiel AD, Wang SY. A Value of Information Analysis of Research on the 21-Gene Assay for Breast Cancer Management. Value in Health (In press)

Application

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3. Heath A, Manolopoulou I, Baio G. Estimating the Expected Value of Sample Information Across Different Sample Sizes Using Moment Matching and Nonlinear Regression. Medical Decision Making. 2019

Methods

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4. Thom H, Visan ACC, Keeney E, et al. Clinical and cost-effectiveness of the Ross procedure versus conventional aortic valve replacement in young adults. Open Heart. 2019

Application

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5. Alarid-Escudero F, Enns EA, Kuntz KM, Michaud TL, Jalal HJ. “Time Traveling Is Just Too Dangerous” But Some Methods Are Worth Revisiting: The Advantages of Expected Loss Curves Over Cost-Effectiveness Acceptability Curves and Frontier. Value Health. 2019

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6. Jutkowitz E, Alarid-Escudero F, Kuntz KM, Jalal HJ. The Curve of Optimal Sample Size (COSS): A Graphical Representation of the Optimal Sample Size from a Value of Information Analysis. PharmacoEconomics. 2019

Methods

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7. Johnson R, Woodcock J, de Nazelle A, de Sa T, Goel R, Tainio M, Jackson C. A guide to Value of Information methods for prioritising research in health impact modelling. (2019 preprint in arXiv)

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2018 

1. Jalal H, Alarid-Escudero F. A Gaussian approximation approach for value of information analysis. Medical Decision Making. 2018

Methods

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2. Heath A, Baio G. Calculating the Expected Value of Sample Information Using Efficient Nested Monte Carlo: A Tutorial. Value in Health. 2018

Methods

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3. Gc VS, Suhrcke M, Hardeman W, Sutton S, Wilson ECF & VBI Programme Team. Cost-Effectiveness and Value of Information Analysis of Brief Interventions to Promote Physical Activity in Primary Care. Value in Health. 2018

Application

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4. Heath A, Manolopoulou I, Baio G. Efficient Monte Carlo Estimation for the Expected Value of Sample Information using Moment Matching. Medical Decision Making. 2018

Methods

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5. Heath A. Bayesian computations for Value of Information measures using Gaussian processes, INLA and Moment Matching. Doctoral thesis (PhD), UCL (University College London). 2018

Methods

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6. Koffijberg H, Rothery C, Chalkidou K, Grutters J. Value of Information Choices that Influence Estimates: A Systematic Review of Prevailing Considerations. Medical Decision Making. 2018

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7. Woods BS, Rothery C, Revill P, Hallett T, Phillips A. Setting research priorities in Global Health: appraising the value of evidence generation activities to support decision-making in health care.  York: Centre for Health Economics, University of York. CHE Research Paper; no. 155. 2018

Application

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8. Ciani O, Epstein D, Rothery C, Taylor RS, Sculpher M. Decision uncertainty and value of further research: a case-study in fenestrated endovascular aneurysm repair for complex abdominal aortic aneurysms. Cost Effectiveness and Resource Allocation. 2018

Application

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9. Koffijberg H, Knies S, Janssen MP. The Impact of Decision Makers’ Constraints on the Outcome of Value of Information Analysis. Value in Health. 2018

Methods

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2017

1. Jutkowitz E, Alarid-Escudero F, Choi HK, Kuntz KM, Jalal H. Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of information Analysis. Pharmacoeconomics. 2017

Application

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2. Heath A, Manolopoulou I, Baio G. A Review of Methods for the Analysis of the Expected Value of Information. Medical Decision Making. 2017

Methods

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3. Thom H, Jackson C, Welton NJ, et al. Using Parameter Constraints to Choose State Structures in Cost-Effectiveness Modelling. PharmacoEconomics. 2017

Methods

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4. Grimm SE, Strong M, Brennan A, Wailoo A. The HTA Risk Analysis Chart: Visualising the Need for and Potential Value of Managed Entry Agreements in Health Technology Assessment. PharmacoEconomics. 2017

Methods

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5. Rothery C, Claxton K, Palmer S, Epstein D, Tarricone R, Sculpher M. Characterising uncertainty in the assessment of medical devices and determining future research needs.  Health Economics. 2017

Application

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2016 

1. Menzies N. An Efficient Estimator for the Expected Value of Sample Information. Medical Decision Making. 2016

Methods

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2. Heath A, Manolopoulou I, Baio G. Estimating the Expected Value of Partial Perfect Information in Health Economic Evaluations Using Integrated Nested Laplace Approximation. Statistics in Medicine. 2016

Methods

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3. Tuffaha HW, Strong M, Gordon LG, Scuffham PA. Efficient value of information calculation using a non-parametric regression approach: an applied perspective. Value in Health. 2016

Methods

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4. Wilson E, Mugford M, Barton G, Shepstone L. Efficient research design: using value-of-information analysis to estimate the optimal mix of top-down and bottom-up costing approaches in an economic evaluation alongside a clinical trial. Medical Decision Making. 2016

Methods

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5. McKenna C, Griffin S, Koffijberg H, Claxton K.  Methods to place a value on additional evidence are illustrated using a case study of corticosteroids after traumatic brain injury. Journal of Clinical Epidemiology. 2016

Application

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6. Claxton K, Palmer S, Longworth L, Bojke L, Griffin S, Soares M, Spackman E, Rothery C.  A comprehensive algorithm for approval of health technologies with, without, or only in research: the key principles for informing coverage decisions.  Value in Health. 2016

Application

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2015

1. Strong M, Oakley J, Brennan A, Breeze P. Estimating the Expected Value of Sample Information Using the Probabilistic Sensitivity Analysis Sample a Fast Nonparametric Regression-Based Method. Medical Decision Making. 2015

Methods

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2. Jalal H, Goldhaber-Fiebert JD, Kuntz K. Computing Expected Value of Partial Sample Information from Probabilistic Sensitivity Analysis Using Linear Regression Metamodeling. Medical Decision Making. 2015

Methods

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3. Wilson ECF. A Practical Guide to Value of Information Analysis. PharmacoEconomics. 2015

Methods

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4. Minelli C, Baio G. Value of Information: A Tool to Improve Research Prioritization and Reduce Waste. PLoS Medicine. 2015

Methods

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5. Welton NJ, Thom HHZ. Value of Information: We’ve Got Speed, What More Do We Need? Medical Decision Making. 2015

Methods

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6. Welton NJ, Soares M, Palmer SJ, Ades AE, Harrison DA, Shankar Hari M, Rowan KM. Accounting for heterogeneity in relative treatment effects for use in cost-effectiveness models and value of information analyses. Medical Decision Making. 2015

Methods

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7. McKenna C, Soares M, Claxton K, Bojke L, Griffin S, Palmer S, Spackman E. Unifying research and reimbursement decisions: Case studies demonstrating the sequence of assessment and judgements required. Value in Health. 2015

Methods

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8. Claxton K, Griffin S, Koffijberg H, McKenna C.  How to estimate the health benefits of additional research and changing clinical practice.  British Medical Journal. 2015

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2014 

1. Strong M, Oakley JE. When is a model good enough? Deriving the expected value of model improvement via specifying internal model discrepancies. SIAM/ASA Journal on Uncertainty Quantification. 2014

Methods

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2. Strong M, Oakley JE, Brennan A. Estimating multi-parameter partial Expected Value of Perfect Information from a probabilistic sensitivity analysis sample: a non-parametric regression approach. Medical Decision Making. 2014

Methods

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3. Wilson E. on behalf of the Cochrane Agenda & Priority Setting Methods Group and Campbell & Cochrane Economics Methods Group. Which study when? Proof of concept of a proposed automated tool to help Cochrane review groups decide which reviews to update first. Cochrane Methods. Cochrane DB Syst Rev. 2014

Methods

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4. Madan J, Ades AE, Price M, Maitland K, Jemutai J, Revill P, Welton NJ. Strategies for Efficient Computation of the Expected Value of Partial Perfect Information. Medical Decision Making 2014

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5. Welton NJ, Madan JJ, Caldwell DM, Peters TJ, Ades AE. Expected Value of Sample Information for Cluster Randomised Trials with Binary Outcomes. Medical Decision Making 2014

Methods

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6. Soares M,  Welton NJ, David A Harrison DA, Peuraa P, Shankar Hari M, Harvey SE, Madan JJ, Ades AE, Rowan KM, Palmer SJ. Intravenous immunoglobulin for severe sepsis and septic shock: clinical effectiveness, cost effectiveness, and value of a further randomised controlled trial. Critical Care 2014

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2013 

1. Thom H. Structural uncertainty in cost-effectiveness models. Doctoral thesis (PhD). University of Cambridge. 2013

Methods

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2. Strong M, Oakley JE. An efficient method for computing single-parameter partial expected value of perfect information. Medical Decision Making. 2013

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2012 

1. Strong M, Oakley JE, Chilcott J. Managing structural uncertainty in health economic decision models: a discrepancy approach. Journal of the Royal Statistical Society, Series C. 2012

Methods

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2. Soares M, Welton NJ, Harrison DA, Peura P, Shankar Hari M, Harvey SE, Madan J, Ades AE, Palmer SJ, Rowan KM. An evaluation of the feasibility, cost and value of information of a multicentre randomised controlled trial of intravenous immunoglobulin for sepsis (severe sepsis and septic shock): incorporating a systematic review, meta-analysis and value of information analysis. Health Technology Assessment 2012

Application

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3. Welton NJ, Ades AE. Research decisions in the face of heterogeneity: what can a new study tell us? Health Economics 2012

Methods

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4. Claxton K, Palmer S, Longworth L, Bojke L, Griffin S, McKenna C, Soares M, Spackman E, Youn, J. Informing a decision framework for when NICE should recommend the use of health technologies only in the context of an appropriately designed programme of evidence development. Health Technology Assessment. 2012

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2011 

1. Price MJ, Welton NJ, Briggs A, Ades AE. Model averaging in the presence of structural uncertainty about treatment effects: impact on treatment decision and Expected Value of Information. Value in Health 2011

Methods

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2. Welton NJ, Madan J, Ades AE. Are head-to-head trials of biologics needed: the role of value of information methods in arthritis research. Rheumatology 2011

Methods

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3. McKenna C, Claxton K. Addressing adoption and research design decisions simultaneously: the role of value of sample information analysis.  Medical Decision Making. 2011

Methods

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2010 

1. Wilson E, Gurusamy K, Gluud C, Davidson B. A cost-utility and value of information analysis of early versus delayed laparoscopic cholecystectomy for acute cholecystitis. British Journal of Surgery. 2010

Application

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2. Wilson E, Abrams K. From evidence-based economics to economics based evidence: using systematic review to inform the design of future research in Shemilt I, Donaldson C, Mugford M, et al. (eds) Evidence Based Decisions and Economics: health care, social welfare, education and criminal justice. Wiley 2010

Methods

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3. Griffin S, Welton NJ, Claxton KP. Exploring the research decision space: the expected value of information for sequential research designs. Medical Decision Making 2010

Methods

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4. McKenna C, Chalabi Z, Epstein D, Claxton K. Budgetary policies and available actions: a generalisation of decision rules for allocation and research decisions. Journal of Health Economics. 2010

Application

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5. Janssen MP, Koffijberg H. Enhancing value of information analyses. Value in Health. 2009

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2008

1. Welton NJ, Ades, AE Caldwell DM, Peters TJ. Research Prioritisation Based on Expected Value of Partial Perfect Information: a Case Study on Interventions to Increase Uptake of Breast Cancer Screening. JRSS A: Statistics in Society 2008.

Methods

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2. Coyle D, Oakley J. Estimating the expected value of partial perfect information: a review of methods.  European Journal of Health Economics 2008

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2007 

1. Brennan A, Kharroubi S. Efficient Computation of Partial Expected Value of Sample Information Using Bayesian Approximation. Journal of Health Economics. 2007

Methods

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2. Brennan A, Kharroubi S. Expected Value of Sample Information for Weibull Survival Data. Health Economics. 2007

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3. Brennan A, Kharroubi S, O’Hagan A, Chilcott J. Calculating Partial Expected Value of Perfect Information via Monte Carlo Sampling Algorithms. Medical Decision Making. 2007

Methods

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2003

1. Coyle D, Buxton MJ, O’Brien BJ. Measures of importance for economic analysis based on decision modeling. Journal of Clinical Epidemiology 2003

Methods

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1. Kunst NR, Wilson E, Alarid-Escudero F, Baio G, Brennan A, Fairley M, Glynn D, Goldhaber-Fiebert JD, Jackson C, Jalal H, Menzies NA, Strong M, Thom H, Heath A, and on behalf of the ConVOI. Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods. Value in Health (In press)

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2. Heath A, Kunst NR, Jackson C, Strong M, Alarid-Escudero F, Goldhaber-Fiebert JD, Baio G, Menzies NA, Jalal J, and on behalf of the ConVOI. Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies. Medical Decision Making(In press)

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1. Heath A, Kunst NR, Jackson C, Strong M, Alarid-Escudero F, Goldhaber-Fiebert JD, Baio G, Menzies NA, Jalal J, and on behalf of the ConVOI. Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies. (Abstract accepted for oral presentation at the SMDM 2019)

2. Kunst NR, Wilson ECF, Alarid-Escudero F, Baio G, Brennan A, Fairley M, Glynn D, Goldhaber-Fiebert JD, Jackson C, Jalal H, Menzies NA, Strong M, Thom H, Heath A, and on behalf of the ConVOI.  Practical Considerations for the Efficient Computation of the Expected Value of Sample Information to Prioritise Research in Health Care. (Abstract accepted for poster presentation at the SMDM 2019)

1. SMDM 2019 Short Course: AM5 – Research Prioritisation and Study Design Using Value of Information Analysis (Course level: Beginner) 

Sunday, October 20, 2019 –  9:00 a.m. – 12:30 p.m.

Awarded the best short course at the 2019 Society for Medical Decision Making (SMDM) North American Meeting

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2. SMDM 2019 Short Course: PM3 – Optimal Research Design Using Value of Information (Course level: Advanced)

Sunday, October 20, 2019 –  2:00 p.m. – 5:30 p.m.

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