Background

The growth of "big data" and the emphasis on patient-centered health care have led to the increasing use of two key technologies: personalized medicine and digital medicine. For these technologies to move into mainstream health care and be reimbursed by insurers, it will be essential to have evidence that their benefits provide reasonable value relative to their costs. These technologies, however, have complex characteristics that present challenges to the assessment of their economic value. Previous studies have identified the challenges for personalized medicine and thus this work informs the more nascent topic of digital medicine.

Objectives

To examine the methodological challenges and future opportunities for assessing the economic value of digital medicine, using personalized medicine as a comparison.

Methods

We focused specifically on digital biomarker technologies and multigene tests. We identified similarities in these technologies that can present challenges to economic evaluation: multiple results, results with different types of utilities, secondary findings, downstream impact (including on family members), and interactive effects.

Results

Using a structured review, we found that there are few economic evaluations of digital biomarker technologies, with limited results.

Conclusions

We conclude that more evidence on the effectiveness of digital medicine will be needed but that the experiences with personalized medicine can inform what data will be needed and how such analyses can be conducted. Our study points out the critical need for typologies and terminology for digital medicine technologies that would enable them to be classified in ways that will facilitate research on their effectiveness and value.

Aims

Knowledge of consumer perspectives of personalized medicine (PM) is limited. Our study assessed consumer perspectives of PM, with a focus on oncology care, to inform industry, clinician and payer stakeholders' programs and policy.

Materials & methods

A nationally representative survey of 602 US consumers' ≥30 years old explored familiarity, perspectives and expected value of PM.

Results

Most (73%) respondents have not heard of 'personalized medicine,' though after understanding the term most (95%) expect PM to have a positive beneft. Consumer's willingness to pay is associated with products' impact on survival, rather than predicting disease risk. If testing indicates consumers are not candidates for oncology therapies, most (84%) would seek a second opinion or want therapy anyway.

Conclusions

Understanding heterogeneity in consumer perspectives of PM can inform program and policy development.

Objectives

The objective of this article is to describe the unique challenges and present potential solutions and approaches for economic evaluations of precision medicine (PM) interventions using simulation modeling methods.

Methods

Given the large and growing number of PM interventions and applications, methods are needed for economic evaluation of PM that can handle the complexity of cascading decisions and patient-specific heterogeneity reflected in the myriad testing and treatment pathways. Traditional approaches (eg, Markov models) have limitations, and other modeling techniques may be required to overcome these challenges. Dynamic simulation models, such as discrete event simulation and agent-based models, are used to design and develop mathematical representations of complex systems and intervention scenarios to evaluate the consequence of interventions over time from a systems perspective.

Results

Some of the methodological challenges of modeling PM can be addressed using dynamic simulation models. For example, issues regarding companion diagnostics, combining and sequencing of tests, and diagnostic performance of tests can be addressed by capturing patient-specific pathways in the context of care delivery. Issues regarding patient heterogeneity can be addressed by using patient-level simulation models.

Conclusion

The economic evaluation of PM interventions poses unique methodological challenges that might require new solutions. Simulation models are well suited for economic evaluation in PM because they enable patient-level analyses and can capture the dynamics of interventions in complex systems specific to the context of healthcare service delivery.

BACKGROUND: Prognostic disclosure is essential to informed decision making in oncology, yet many oncologists are unsure how to successfully facilitate this discussion. This scoping review determines what prognostic communication models exist, compares and contrasts these models, and explores the supporting evidence. METHOD: A protocol was created for this study using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols extension for Scoping Reviews. Comprehensive literature searches of electronic databases MEDLINE, EMBASE, PsycINFO and Cochrane CENTRAL were executed to identify relevant publications between 1971 and 2020. RESULTS: In total, 1532 articles were identified, of which 78 met inclusion criteria and contained 5 communication models. Three of these have been validated in randomised controlled trials (the Serious Illness Conversation Guide, the Four Habits Model and the ADAPT acronym) and have demonstrated improved objective communication measures and patient reported outcomes. All three models emphasise the importance of exploring patients illness understanding and treatment preferences, communicating prognosis and responding to emotion. CONCLUSION: Communicating prognostic estimates is a core competency skill in advanced cancer care. This scoping review highlights available communication models and identifies areas in need of further assessment. Such areas include how to maintain learnt communication skills for lifelong practice, how to assess patient and caregiver understanding during and after these conversations, and how to best scale these protocols at the institutional and national levels.

The emergence of next-generation genomic sequencing (NGS) tests for use in clinical care has generated widespread interest around the globe, but little is known about the availability and funding of these tests worldwide. We examined NGS availability across world regions and countries, with a particular focus on availability of three key NGS tests-Whole-Exome Sequencing or Whole-Genome Sequencing for diagnosis of suspected genetic diseases such as intellectual disability disorders or rare diseases, non-invasive prenatal testing for common genetic abnormalities in fetuses and tumor sequencing for therapy selection and monitoring of cancer treatment. We found that these NGS tests are available or becoming available in every major region of the world. This includes both high-income countries with robust genomic programmes such as the USA and the UK, and growing availability in countries with upper-middle-income economies. We used exploratory case studies across three diverse health care systems (publicly funded/national (UK), publicly funded/provincial (Canada) and mixed private/public system (USA)) to illustrate the funding challenges and approaches used to address those challenges that might be adopted by other countries. We conclude by assessing what type of data and initiatives will be needed to better track and understand the use of NGS around the world as such testing continues to expand.

Background

Clinical use of next-generation sequencing (NGS) tests has been increasing, but few studies have examined their economic value. Several studies have noted that there are methodological challenges to conducting economic evaluations of NGS tests.

Objective

Our objective was to examine key methodological challenges for conducting economic evaluations of NGS tests, prioritize these challenges for future research, and identify how studies have attempted solutions to address these challenges.

Methods

We identified challenges for economic evaluations of NGS tests using prior literature and expert judgment of the co-authors. We used a modified Delphi assessment to prioritize challenges, based on importance and probability of resolution. Using a structured literature review and article extraction we then assessed whether published economic evaluations had addressed these challenges.

Results

We identified 11 challenges for conducting economic evaluations of NGS tests. The experts identified three challenges as the top priorities for future research: complex model structure, timeframe, and type of analysis and comparators used. Of the 15 published studies included in our literature review, four studies described specific solutions relevant to five of the 11 identified challenges.

Conclusions

Major methodological challenges to economic evaluations of NGS tests remain to be addressed. Our results can be used to guide future research and inform decision-makers on how to prioritize research on the economic assessment of NGS tests.

The American College of Medical Genetics and Genomics (ACMG) recommends that mutations in 56 genes for 24 conditions are clinically actionable and should be reported as secondary findings after whole-genome sequencing (WGS). Our aim was to identify published economic evaluations of detecting mutations in these genes among the general population or among targeted/high-risk populations and conditions and identify gaps in knowledge. A targeted PubMed search from 1994 through November 2014 was performed, and we included original, English-language articles reporting cost-effectiveness or a cost-to-utility ratio or net benefits/benefit-cost focused on screening (not treatment) for conditions and genes listed by the ACMG. Articles were screened, classified as targeting a high-risk or general population, and abstracted by two reviewers. General population studies were evaluated for actual cost-effectiveness measures (e.g., incremental cost-effectiveness ratios (ICER)), whereas studies of targeted populations were evaluated for whether at least one scenario proposed was cost-effective (e.g., ICER of ≤$100,000 per life-year or quality-adjusted life-year gained). A total of 607 studies were identified, and 32 relevant studies were included. Identified studies addressed fewer than one-third (7 of 24; 29%) of the ACMG conditions. The cost-effectiveness of screening in the general population was examined for only 2 of 24 conditions (8%). The cost-effectiveness of most genetic findings that the ACMG recommends for return has not been evaluated in economic studies or in the context of screening in the general population. The individual studies do not directly address the cost-effectiveness of WGS.