Use of Value of Information in Healthcare Decision Making: Exploring Multiple Perspectives

Estimating the Potential Benefits of Confirmatory Trials for Drugs with Accelerated Approval: A Comprehensive Value of Information Framework

BACKGROUND

The US Food and Drug Administration's Accelerated Approval (AA) policy provides a pathway for patients to access potentially life-saving drugs rapidly. However, the use of surrogate endpoints, single-arm designs, and small sample sizes in preliminary trials that support AAs can lead to uncertainty regarding the clinical benefits of such drugs. This study aims to develop a comprehensive value of information (VOI) framework for assessing the potential benefits of future confirmatory trials, accounting for the various uncertainties inherent in preliminary trials.

METHODS

I formulated an expected value of information from confirmatory trial (EVICT) metric, which evaluates the potential benefits of a confirmatory trial that would reduce those uncertainties by using a clinically meaningful endpoint, a randomized control, and increased sample size. The EVICT metric can quantify the expected benefits of a well-designed confirmatory trial or an inadequately designed one that continues to use surrogate endpoints or single-arm design. The framework was illustrated using a hypothetical AA drug for metastatic breast cancer.

RESULTS

The case study demonstrates that a highly uncertain preliminary trial of an AA drug was associated with a substantial EVICT. A confirmatory trial with an increased sample size for this AA drug, utilizing a clinically meaningful endpoint and randomized control, yielded a population-level EVICT of $12.6 million. Persistently using a surrogate endpoint and single-arm trial design would reduce the EVICT by 60%.

CONCLUSIONS

This framework can provide accurate VOI estimates to guide coverage policies, value-based pricing, and the design of confirmatory trials for AA drugs.

Toward an Ecologically Valid Conceptual Framework for the Use of Artificial Intelligence in Clinical Settings: Need for Systems Thinking, Accountability, Decision-making, Trust, and Patient Safety Considerations in Safeguarding the Technology and Clinicians

The health care management and the medical practitioner literature lack a descriptive conceptual framework for understanding the dynamic and complex interactions between clinicians and artificial intelligence (AI) systems. As most of the existing literature has been investigating AI's performance and effectiveness from a statistical (analytical) standpoint, there is a lack of studies ensuring AI's ecological validity. In this study, we derived a framework that focuses explicitly on the interaction between AI and clinicians. The proposed framework builds upon well-established human factors models such as the technology acceptance model and expectancy theory. The framework can be used to perform quantitative and qualitative analyses (mixed methods) to capture how clinician-AI interactions may vary based on human factors such as expectancy, workload, trust, cognitive variables related to absorptive capacity and bounded rationality, and concerns for patient safety. If leveraged, the proposed framework can help to identify factors influencing clinicians' intention to use AI and, consequently, improve AI acceptance and address the lack of AI accountability while safeguarding the patients, clinicians, and AI technology. Overall, this paper discusses the concepts, propositions, and assumptions of the multidisciplinary decision-making literature, constituting a sociocognitive approach that extends the theories of distributed cognition and, thus, will account for the ecological validity of AI.

Implementation Barriers to Value of Information Analysis in Health Technology Decision Making: Results From a Process Evaluation

OBJECTIVES

Value of information (VOI) analysis can support health technology assessment decision making, but it is a long way from being standard use. The objective of this study was to understand barriers to the implementation of VOI analysis and propose actions to overcome these.

METHODS

We performed a process evaluation of VOI analysis use within decision making on tomosynthesis versus digital mammography for use in the Dutch breast cancer population screening. Based on steering committee meeting attendance and regular meetings with analysts, we developed a list of barriers to VOI use, which were analyzed using an established diffusion model. We proposed actions to address these barriers. Barriers and actions were discussed and validated in a workshop with stakeholders representing patients, clinicians, regulators, policy advisors, researchers, and the industry.

RESULTS

Consensus was reached on groups of barriers, which included characteristics of VOI analysis itself, stakeholder's attitudes, analysts' and policy makers' skills and knowledge, system readiness, and implementation in the organization. Observed barriers did not only pertain to VOI analysis itself but also to formulating the objective of the assessment, economic modeling, and broader aspects of uncertainty assessment. Actions to overcome these barriers related to organizational changes, knowledge transfer, cultural change, and tools.

CONCLUSIONS

This in-depth analysis of barriers to implementation of VOI analysis and resulting actions and tools may be useful to health technology assessment organizations that wish to implement VOI analysis in technology assessment and research prioritization. Further research should focus on application and evaluation of the proposed actions in real-world assessment processes.

Cost-Effectiveness and Value of Information of Cabozantinib Treatment for Patients with Advanced Renal Cell Carcinoma After Failure of Prior Therapy in South Korea

OBJECTIVE

To estimate the cost-effectiveness and value of information of cabozantinib compared to nivolumab in advanced renal cell carcinoma (RCC) patients, who previously failed treatment from a societal perspective in South Korea.

METHODS

A partitioned survival model was used to evaluate the incremental cost-utility ratio (ICUR) of cabozantinib versus nivolumab. Overall survival (OS) and progression-free survival (PFS) curves were obtained from a network meta-analysis that included METEOR and CheckMate 025 trial results. Utility values for health states and adverse events were estimated based on the EQ-5D-5L data of METEOR trial with a Korean-specific tariff. Costs were estimated by a micro-costing approach using healthcare claims data and expert consultation. The impact of uncertainties in the model were explored by scenario analyses, and deterministic and probabilistic sensitivity analyses. The expected value of perfect information (EVPI) was estimated to assess the value of future research to decrease decision uncertainty.

RESULTS

Compared to nivolumab, cabozantinib was associated with improved OS, PFS, and quality-adjusted life-years (QALYs) at greater cost. The ICUR was $34,445 per QALY. In sensitivity analysis, drug costs had the greatest influence on the ICUR. Cabozantinib had a 68.0% probability of being cost-effective at a threshold of 2 times gross domestic product (GDP) per capita. The population EVPI was $82.6 million at 2 GDP threshold.

CONCLUSIONS

Cabozantinib was found to be cost-effective for advanced RCC patients after failure of prior therapy at a 2 GDP threshold. Future research that costs less than the estimated population EVPI would be worth considering for a comparison of cabozantinib and nivolumab.

Developing a whole-school mental health and wellbeing intervention through pragmatic formative process evaluation: a case-study of innovative local practice within The School Health Research network

Background

The evidence-base for whole school approaches aimed at improving student mental health and wellbeing remains limited. This may be due to a focus on developing and evaluating de-novo, research-led interventions, while neglecting the potential of local, contextually-relevant innovation that has demonstrated acceptability and feasibility. This study reports a novel approach to modelling and refining the programme theory of a whole-school restorative approach, alongside plans to scale up through a national educational infrastructure in order to support robust scientific evaluation.

Methods

A pragmatic formative process evaluation was conducted of a routinized whole-school restorative approach aimed at improving student mental health and wellbeing in Wales.

Results

The study reports the six phases of the pragmatic formative process evaluation. These are: 1) identification of innovative local practice; 2) scoping review of evidence-base to identify potential programme theory; outcomes; and contextual characteristics that influence implementation; 3) establishment of a Transdisciplinary Action Research (TDAR) group; 4) co-production and confirmation of an initial programme theory with stakeholders; 5) planning to optimise intervention delivery in local contexts; and 6) planning for feasibility and outcome evaluation. The phases of this model may be iterative and not necessarily sequential.

Conclusions

Formative, pragmatic process evaluations can support researchers, policy-makers and practitioners in developing robust scientific evidence-bases for acceptable and feasible local innovations that do not already have a clear evidence base. The case of a whole-school restorative approach provides a case example of how such an evaluation may be undertaken.

How can we adapt complex population health interventions for new contexts? Progressing debates and research priorities

INTRODUCTION

The UK Medical Research Council and National Institute for Health Research have funded the ADAPT study (2018-2020), to develop methodological guidance for the adaptation of complex population health interventions for new contexts. While there have been advances in frameworks, there are key theoretical and methodological debates to progress. The ADAPT study convened a panel meeting to identify and enrich these debates. This paper presents the panel's discussions and suggests directions for future research.

METHODS

Sixteen researchers and one policymaker convened for a 1-day meeting in July 2019. The aim was to reflect on emerging study findings (systematic review of adaptation guidance; scoping review of case examples; and qualitative interviews with funders, journal editors, researchers and policymakers), progress theoretical and methodological debates, and consider where innovation may be required to address research gaps.

DISCUSSION

Despite the proliferation of adaptation frameworks, questions remain over the definition of basic concepts (eg, adaptation). The rationale for adaptation, which often focuses on differences between contexts, may lead to adaptation hyperactivity. Equal emphasis should be placed on similarities. Decision-making about intervention modification currently privileges the concept of 'core components', and work is needed to progress the use and operationalisation of 'functional fidelity'. Language and methods must advance to ensure meaningful engagement with diverse stakeholders in adaptation processes. Further guidance is required to assess the extent of re-evaluation required in the new context. A better understanding of different theoretical perspectives, notably complex systems thinking, implementation science and realist evaluation may help in enhancing research on adaptation.

Economic Evaluations of Pharmacological Treatments in Heart Failure Patients: A Methodological Review with a Focus on Key Model Drivers

Various decision analytic models exist for evaluating the cost-effectiveness of pharmacological interventions for heart failure (HF). Despite this, studies that explore drivers influencing these modeling approaches remain scarce. Through a systematic review of the literature, the present study sought to identify model drivers that emerge from economic evaluations of HF pharmacological interventions. Among the 72 cost effectiveness papers evaluating HF drug interventions, the most frequently identified, top 5 ranked model drivers impacting the incremental cost-effectiveness ratio (ICER) were cost of treatment and utility, identified in 10% of studies, respectively. Other drivers that emerged as top 5 ranked drivers in > 5% of studies included treatment effect on mortality (or cardiovascular mortality), duration of treatment, and baseline cardiovascular mortality. Model drivers reported at the top of tornado diagrams were treatment effect on mortality or on cardiovascular mortality. Collectively, these observations highlight the key importance of treatment effect in driving cost-effectiveness models for HF.

Value of Information Analysis for Research Decisions-An Introduction: Report 1 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force

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.

Value of information analysis of an early intervention for subthreshold panic disorder: Healthcare versus societal perspective

Background

Panic disorder is associated with high productivity costs. These costs, which should be included in cost-effectiveness analyses (CEA) from a societal perspective, have a considerable impact on cost-effectiveness estimates. However, they are often omitted in published CEAs. It is therefore uncertain whether choosing a societal perspective changes priority setting in future research as compared to a healthcare perspective.

Objectives

To identify research priorities regarding the cost-effectiveness of an early intervention for subthreshold panic disorder using value of information (VOI) analysis and to investigate to what extent priority setting depends on the perspective.

Methods

We calculated the cost-effectiveness of an early intervention for panic disorder from a healthcare perspective and a societal perspective. We performed a VOI analysis, which estimates the expected value of eliminating the uncertainty surrounding cost-effectiveness estimates, for both perspectives.

Results

From a healthcare perspective the early intervention was more effective at higher costs compared to usual care (€17,144 per QALY), whereas it was cost-saving from a societal perspective. Additional research to eliminate parameter uncertainty was valued at €129.7 million from a healthcare perspective and €29.5 million from a societal perspective. Additional research on the early intervention utility gain was most valuable from a healthcare perspective, whereas from a societal perspective additional research would generate little added value.

Conclusions

Priority setting for future research differed substantially according to the perspective. Our study underlines that the health-economic perspective of CEAs on interventions for panic disorder must be chosen carefully in order to avoid inappropriate choices in research priorities.

Value of Information Choices that Influence Estimates: A Systematic Review of Prevailing Considerations

Background. Although value of information (VOI) analyses are increasingly advocated and used for research prioritization and reimbursement decisions, the interpretation and usefulness of VOI outcomes depend critically on the underlying choices and assumptions used in the analysis. In this article, we present a structured overview of all items reported in literature to potentially influence VOI outcomes. Use of this overview increases awareness and transparency of choices and assumptions underpinning VOI outcomes. Methods. A systematic literature review was performed to identify aspects of VOI analyses that were found to potentially influence VOI outcomes. Identified aspects were grouped to develop a structured overview. Explanations were defined for all items included in the overview. Results. We retrieved 687 unique papers, of which 71 original papers and 8 reviews were included. In the full text of these 79 papers, 16 aspects were found that may influence VOI outcomes. These aspects related to the underlying evidence (bias, synthesis, heterogeneity, correlation), uncertainty (structural, future pricing), model (relevance, approach, population), choices in VOI calculation (estimation technique, implementation level, population size, perspective), and aspects specifically for assessing the value of future study designs (reversal costs, efficient estimator). These aspects were aggregated into 7 items to provide a structured overview. Conclusion. The developed overview should increase awareness of key choices underlying VOI analysis and facilitate structured reporting of such choices and interpretation of the ensuing VOI outcomes by researchers and policy makers. Use of this overview should improve prioritization and reimbursement decisions.

Integrating value of research into NCI Clinical Trials Cooperative Group research review and prioritization: A pilot study

Background

The Institute of Medicine has called for approaches to help maximize the return on investments (ROI) in cancer clinical trials. Value of Research (VOR) is a health economics technique that estimates ROI and can inform research prioritization. Our objective was to evaluate the impact of using VOR analyses on the clinical trial proposal review process within the SWOG cancer clinical trials consortium.

Methods

We used a previously developed minimal modeling approach to calculate VOR estimates for 9 phase II/III SWOG proposals between February 2015 and December 2016. Estimates were presented to executive committee (EC) members (N = 12) who determine which studies are sent to the National Cancer Institute for funding consideration. EC members scored proposals from 1 (best) to 5 based on scientific merit and potential impact before and after receiving VOR estimates. EC members were surveyed to assess research priorities, proposal evaluation process satisfaction, and the VOR process.

Results

Value of Research estimates ranged from −$2.1B to $16.46B per proposal. Following review of VOR results, the EC changed their score for eight of nine proposals. Proposal rankings were different in pre‐ vs postscores (P value: 0.03). Respondents had mixed views of the ultimate utility of VOR for their decisions with most supporting (42%) or neutral (41%) to the idea of adding VOR to the evaluation process.

Conclusions

The findings from this pilot study indicate use of VOR analyses may be a useful adjunct to inform proposal reviews within NCI Cooperative Clinical Trials groups.

The Australian Managed Entry Scheme: Are We Getting it Right?

In 2010, the Australian Government introduced the managed entry scheme (MES) to improve patient access to subsidised drugs on the Pharmaceutical Benefits Scheme and enhance the quality of evidence provided to decision makers. The aim of this paper was to critically review the Australian MES experience. We performed a comprehensive review of publicly available Pharmaceutical Benefits Advisory Committee online documents from January 2010 to July 2017. Relevant information on each MES agreement was systematically extracted, including its rationale, the conditions that guided its implementation and its policy outcomes. We identified 11 drugs where an MES was considered. Most of the identified drugs (75%) were antineoplastic agents and the main uncertainty was the overall survival benefit. More than half of the MES proposals were made by sponsors and most of the schemes were considered after previous rejected/deferred submissions for reimbursement. An MES was not established in 8 of 11 drugs (73%) despite the high evidence uncertainty. Nevertheless, six of these eight drugs were listed after the sponsors reduced their prices. Three MESs were established and implemented by Deeds of Agreement. The three cases were concluded and the required data were submitted within the agreed time frames. The need for feasibility and value of an MES should be carefully considered by stakeholders before embarking on such an agreement. It is essential to engage major stakeholders, including patient representatives, in this process. The conditions governing MESs should be clear, transparent and balanced to address the expectations of various stakeholders.

The Impact of Decision Makers' Constraints on the Outcome of Value of Information Analysis

BACKGROUND

When proven effective, decision making regarding reimbursement of new health technology typically involves ethical, social, legal, and health economic aspects and constraints. Nevertheless, when applying standard value of information (VOI) analysis, the value of collecting additional evidence is typically estimated assuming that only cost-effectiveness outcomes guide such decisions.

OBJECTIVES

To illustrate how decision makers' constraints can be incorporated into VOI analyses and how these may influence VOI outcomes.

METHODS

A simulation study was performed to estimate the cost-effectiveness of a new hypothetical technology compared with usual care. Constraints were defined for the new technology on 1) the maximum acceptable rate of complications and 2) the maximum acceptable additional budget. The expected value of perfect information (EVPI) for the new technology was estimated in various scenarios, both with and without incorporating these constraints.

RESULTS

For a willingness-to-pay threshold of €20,000 per quality-adjusted life-year, the probability that the new technology was cost-effective equaled 57%, with an EVPI of €1868 per patient. Applying the complication rate constraint reduced the EVPI to €1137. Similarly, the EVPI reduced to €770 when applying the budget constraint. Applying both constraints simultaneously further reduced the EVPI to €318.

CONCLUSIONS

When decision makers explicitly apply additional constraints, beyond a willingness-to-pay threshold, to reimbursement decisions, these constraints can and should be incorporated into VOI analysis as well, because they may influence VOI outcomes. This requires continuous interaction between VOI analysts and decision makers and is expected to improve both the relevance and the acceptance of VOI outcomes.

The INVEST project: investigating the use of evidence synthesis in the design and analysis of clinical trials

BACKGROUND

When designing and analysing clinical trials, using previous relevant information, perhaps in the form of evidence syntheses, can reduce research waste. We conducted the INVEST (INVestigating the use of Evidence Synthesis in the design and analysis of clinical Trials) survey to summarise the current use of evidence synthesis in trial design and analysis, to capture opinions of trialists and methodologists on such use, and to understand any barriers.

METHODS

Our sampling frame was all delegates attending the International Clinical Trials Methodology Conference in November 2015. Respondents were asked to indicate (1) their views on the use of evidence synthesis in trial design and analysis, (2) their own use during the past 10 years and (3) the three greatest barriers to use in practice.

RESULTS

Of approximately 638 attendees of the conference, 106 (17%) completed the survey, half of whom were statisticians. Support was generally high for using a description of previous evidence, a systematic review or a meta-analysis in trial design. Generally, respondents did not seem to be using evidence syntheses as often as they felt they should. For example, only 50% (42/84 relevant respondents) had used a meta-analysis to inform whether a trial is needed compared with 74% (62/84) indicating that this is desirable. Only 6% (5/81 relevant respondents) had used a value of information analysis to inform sample size calculations versus 22% (18/81) indicating support for this. Surprisingly large numbers of participants indicated support for, and previous use of, evidence syntheses in trial analysis. For example, 79% (79/100) of respondents indicated that external information about the treatment effect should be used to inform aspects of the analysis. The greatest perceived barrier to using evidence synthesis methods in trial design or analysis was time constraints, followed by a belief that the new trial was the first in the area.

CONCLUSIONS

Evidence syntheses can be resource-intensive, but their use in informing the design, conduct and analysis of clinical trials is widely considered desirable. We advocate additional research, training and investment in resources dedicated to ways in which evidence syntheses can be undertaken more efficiently, offering the potential for cost savings in the long term.