In this issue of Value in Health, we publish our second themed section—this one on the incorporation of patient preferences into health care decision making. The section contains 8 papers, and an accompanying editorial. The main focus is on the use of patient-centered benefit-risk assessment to support regulatory decision making, since this is currently being explored in a number of jurisdictions, including Canada, the European Union and the US. However, the themed section also contains a number of papers exploring the incorporation of patient preferences in a range of other decision making settings.
We also publish the report from the ISPOR Good Research Practices Task Force on Estimating Health State Utility for Economic Models in Clinical Studies. The Task Force Report appears with an accompanying editorial from Karen Kuntz and a subsequent response from the Task Force authors.
A paper by Grimm et al, our issue highlight, discusses the modeling of future price and diffusion in health technology assessments (HTAs) of medical devices. The authors argue that future changes in price and uptake have the potential to affect incremental cost-effectiveness ratios and that modeling these should be considered for medical devices that may otherwise be rejected in the context of HTAs.
We also publish two papers that compare the properties of different outcomes measures. Van Dongen et al. compare the EQ-5D-5L with the EORTC QLD-C30 in leukemia patients and Goranitis et al. compare the ICECAP-A and EQ-5D-5L in the context of opiate dependence.
Michael F. Drummond, MCom, DPhil and C. Daniel Mullins, PhD
Co-Editors-in-Chief, Value in Health
Decision Modeling for Cost-Utility Analysis
Response to Editorial: Estimating Health-State Utility for Economic Models in Clinical Studies: An ISPOR Good Research Practices Task Force Report
ISPOR Task Force Report
Estimating Health-State Utility for Economic Models in Clinical Studies: An ISPOR Good Research Practices Task Force Report
Sorrel Wolowacz, Andrew H Briggs, Vasily Belozeroff, Philip Clarke, Lynda Doward, Ron Goeree, Andrew Lloyd, Norman Richard
Cost-utility analyses are increasingly used in many countries to establish whether the cost of a new intervention can be justified in terms of health benefits and these decisions affect access to treatments and manufacturers return on investment. Clinical trials represent an important opportunity for the collection of health-utility data; however, careful planning is needed in the trial designed. This report provides a framework for researchers to plan the collection of health-utility data in clinical studies to provide the high-quality HSU estimates needed for economic modeling.
When Future Change Matters: Modelling Future Price and Diffusion in Health Technology Assessments of Medical Devices
Sabine Elisabeth Grimm, Simon Dixon, John Stevens
This article will explore the impact of future price reductions caused by increasing uptake on HTAs and decision making for medical devices.
Themed Section: Incorporating Patient Preferences Into Regulatory Decision Making
International Experiences in Quantitative Benefit-Risk Analysis to Support Regulatory Decisions
Shelby D. Reed
Regulatory Decision-Making in Canada—Exploring New Frontiers in Patient Involvement
Patient-Focused Benefit-Risk Analysis to Inform Regulatory Decisions: The EU Perspective
Axel C. Mühlbacher
Patient Preferences in Regulatory Benefit-Risk Assessments: A U.S. Perspective
F. Reed Johnson
A Framework for Incorporating Patient Preferences Regarding Benefits and Risks into Regulatory Assessment of Medical Technologies
Developing a Patient-Centered Benefit-Risk Survey: A Community-Engaged Approach
Attribute Development Using Continuous Stakeholder Engagement to Prioritize Treatment Decisions: A Framework for Patient-Centered Research
Measuring High-risk Patients' Preferences for Pharmacogenetic Testing to Reduce Severe Adverse Drug Reaction: A Discrete Choice Experiment
First and Foremost Battle the Virus: Eliciting Patient Preferences in Antiviral Therapy for Hepatitis C Using a Discrete Choice Experiment
Axel C. Mühlbacher
Impact of Treatment Subsidies and Cash Pay-Outs on Treatment Choices at the End of Life
Eric Andrew Finkelstein
This commentary critically reviews the ability of these questionnaires to measure and value capability.
Patient Heterogeneity in Health Economic Decision Models for Chronic Obstructive Pulmonary Disease: Are Current Models Suitable to Evaluate Personalized Medicine?
Martine Hoogendoorn, Talitha L. Feenstra, Yumi Asukai, Andrew H. Briggs, Sixten Borg, Roberto W. Dal Negro, Ryan N. Hansen, Sven-Arne Jansson, Reiner Leidl, Nancy Risebrough, Yevgeniy Samyshkin, Margarethe E. Wacker, Maureen P. Rutten-van Mölken
This evaluation assess how suitable current chronic obstructive pulmonary disease (COPD) cost-effectiveness models are to evaluate personalized treatment options for COPD by exploring the type of heterogeneity included in current models and by validating outcomes for subgroups of patients.
Measuring Health and Broader Well-Being Benefits in the Context of Opiate Dependence: The Psychometric Performance of the ICECAP-A and EQ-5D-5L
Ilias Goranitis, Joanna Coast, Ed Day, Alex Copello, Nick Freemantle, Jennifer Seddon, Carmel Bennett, and Emma Frew
The purpose of this article is to assess the construct validity of the ICECAP-A and EQ-5D-5L, in terms of convergent and discriminative validity, and sensitivity to change based on standard clinical measures (CORE-OM, TOP, ISEL, LDQ, and SSQ).
Which Questionnaire Should Be Used to Measure Quality of Life Utilities in Acute Leukemia Patients? An Evaluation of the Validity and Interpretability of The EQ-5D-5L and Preference-Based Questionnaires Derived from The EORTC QLQ-C30
Annemieke van Dongen, William K. Redekop, Carin A. Uyl-de Groot
The aim of this study was to assess the validity and interpretability of different preference-based questionnaires (i.e., generic EuroQol 5 Dimension 5-level (EQ-5D-5L), cancer-specific Quality of Life Questionnaire Preference Based Measure (QLQ-PBM) and European Organization of Randomized Controlled Trials 8 Dimension (EORTC-8D)) in patients with acute leukemia.
Comparative Effectiveness Research/Health Technology Assessment
Adherence to Self-Care Behaviors Among Patients With Type 2 Diabetes: The Role of Risk Preferences Comparative- Effectiveness Research / HTA
Tzahit Simon-Tuval, Amir Shmueli, Ilana Harman-Boehm
This article examines whether the degree of risk aversion is associated with adherence to disease self-management among adults with type 2 diabetes.
Health Policy Analysis
Financing a Cure For Diabetes in a Multi-Payer Environment
Anirban Basu, Prasun Subedi, Sachin Kamal-Bahl
In this paper, the authors develop the precise conditions needed for a financing mechanism, HealthCoin, to work between a private payer and Medicare, to incentivize the former to invest in breakthrough therapies or cures in the US.
Did it Matter That the Cancer Drugs Fund Was Not NICE? A Retrospective Review
Padraig Dixon, Charlotte Chamberlain, William Hollingworth
This article reviews the means by which the Cancer Drugs Fund (CDF) made recent funding decisions for cancer drugs in order to provide an assessment of the merits of ž˙the CDF model as a basis for allocation decisions.
A Comprehensive Algorithm for Approval of Health Technologies with, without, or only in Research: The Key Principles for Informing Coverage Decisions
Claire Rothery, Karl Claxton, Stephen Palmer, Louise Longworth, Laura Bojke, Susan Griffin, Marta Soares, Eldon Spackman
This article aims to outline the key principles of what assessments are needed to inform 'only in research' or 'approval with research' recommendations, in addition to approval or rejection.
Economic Impact of Integrated Care Models for Patients with Chronic Diseases: A Systematic Review
Melissa Desmedt, Sonja Vertriest, Johan Hellings, Jochen Bergs, Ezra Dessers, Patrick Vankrunkelsven, Hubertus Vrijhoef, Lieven Annemans, Nick Verhaeghe, Mirko Petrovic, Dominique Vandijck
This present study aimed to assess the costs and potential financial benefit of integrated care models for patients with chronic diseases, (i.e. type 2 diabetes mellitus, schizophrenia, or multiple sclerosis).
Also in this issue