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There is a tremendous public health need to identify potentially lethal cancers at earlier stages, when there is a greater chance for improved survival. Although in the US there are currently screening recommendations for only five cancers (breast, colorectal, cervical, lung, and prostate), new tests can screen for up to fifty cancers simultaneously based on a simple blood draw. However, these multicancer screening tests (also called "liquid biopsy" tests) will also present challenges to payers because of intrinsic features of the tests and the complexity of payer coverage assessments for screening tests. We describe these considerations while also offering potential solutions that can inform payers' decision making if these tests prove to be beneficial.

ObjectivesGiven the potential of real-world evidence (RWE) to inform understanding of the risk-benefit profile of next-generation sequencing (NGS)-based testing, we undertook a study to describe the current landscape of whether and how payers use RWE as part of their coverage decision making and potential solutions for overcoming barriers.MethodsWe performed a scoping literature review of existing RWE evidentiary frameworks for evaluating new technologies and identified barriers to clinical integration and evidence gaps for NGS. We synthesized findings as potential solutions for improving the relevance and utility of RWE for payer decision-making.ResultsPayers require evidence of clinical utility to inform coverage decisions, yet we found a relatively small number of published RWE studies, and these are predominately focused on oncology, pharmacogenomics, and perinatal/pediatric testing. We identified 3 categories of innovation that may help address the current undersupply of RWE studies for NGS: (1) increasing use of RWE to inform outcomes-based contracting for new technologies, (2) precision medicine initiatives that integrate clinical and genomic data and enable data sharing, and (3) Food and Drug Administration reforms to encourage the use of RWE. Potential solutions include development of data and evidence review standards, payer engagement in RWE study design, use of incentives and partnerships to lower the barriers to RWE generation, education of payers and providers concerning the use of RWE and NGS, and frameworks for conducting outcomes-based contracting for NGS.ConclusionsWe provide numerous suggestions to overcome the data, methodologic, infrastructure, and policy challenges constraining greater integration of RWE in assessments of NGS.

BackgroundClinical 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.ObjectiveOur 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.MethodsWe 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.ResultsWe 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.ConclusionsMajor 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.

Genetic testing and spending on that testing have grown rapidly since the mapping of the human genome in 2003. However, it is not widely known how many tests there are, how they are used, and how they are paid for. Little evidence from large data sets about their use has emerged. We shed light on the issue of genetic testing by providing an overview of the testing landscape. We examined test availability and spending for the full spectrum of genetic tests, using unique data sources on test availability and commercial payer spending for privately insured populations, focusing particularly on tests measuring multiple genes in the period 2014-17. We found that there were approximately 75,000 genetic tests on the market, with about ten new tests entering the market daily. Prenatal tests accounted for the highest percentage of spending on genetic tests, and spending on hereditary cancer tests accounted for the second-highest. Our results provide insights for those interested in assessing genetic testing markets, test usage, and health policy implications, including current debates over the most appropriate regulatory and payer coverage mechanisms.

Comparative effectiveness research (CER) in genomic medicine (GM) measures the clinical utility of using genomic information to guide clinical care in comparison to appropriate alternatives. We summarized findings of high-quality systematic reviews that compared the analytic and clinical validity and clinical utility of GM tests. We focused on clinical utility findings to summarize CER-derived evidence about GM and identify evidence gaps and future research needs. We abstracted key elements of study design, GM interventions, results, and study quality ratings from 21 systematic reviews published in 2010 through 2015. More than half (N = 13) of the reviews were of cancer-related tests. All reviews identified potentially important clinical applications of the GM interventions, but most had significant methodological weaknesses that largely precluded any conclusions about clinical utility. Twelve reviews discussed the importance of patient-centered outcomes, although few described evidence about the impact of genomic medicine on these outcomes. In summary, we found a very limited body of evidence about the effect of using genomic tests on health outcomes and many evidence gaps for CER to address.Genet Med advance online publication 13 April 2017.

PurposeCell-free DNA (cfDNA) prenatal screening tests have been rapidly adopted into clinical practice, due in part to positive insurance coverage. We evaluated the framework payers used in making coverage decisions to describe a process that should be informative for other sequencing tests.MethodsWe analyzed coverage policies from the 19 largest US private payers with publicly available policies through February 2016, building from the University of California San Francisco TRANSPERS Payer Coverage Policy Registry.ResultsAll payers studied cover cfDNA screening for detection of trisomies 21, 18, and 13 in high-risk, singleton pregnancies, based on robust clinical validity (CV) studies and modeled evidence of clinical utility (CU). Payers typically evaluated the evidence for each chromosomal abnormality separately, although results are offered as part of a panel. Starting in August 2015, 8 of the 19 payers also began covering cfDNA screening in average-risk pregnancies, citing recent CV studies and updated professional guidelines. Most payers attempted, but were unable, to independently assess analytic validity (AV).ConclusionPayers utilized the standard evidentiary framework (AV/CV/CU) when evaluating cfDNA screening but varied in their interpretation of the sufficiency of the evidence. Professional guidelines, large CV studies, and decision analytic models regarding health outcomes appeared highly influential in coverage decisions.Genet Med advance online publication 22 September 2016.

Background: Hereditary cancer panels (HCPs), testing for multiple genes and syndromes, are rapidly transforming cancer risk assessment but are controversial and lack formal insurance coverage. We aimed to identify payers' perspectives on barriers to HCP coverage and opportunities to address them. Comprehensive cancer risk assessment is highly relevant to the Precision Medicine Initiative (PMI), and payers' considerations could inform PMI's efforts. We describe our findings and discuss them in the context of PMI priorities. Methods: We conducted semi-structured interviews with 11 major US payers, covering >160 million lives. We used the framework approach of qualitative research to design, conduct, and analyze interviews, and used simple frequencies to further describe findings. Results: Barriers to HCP coverage included poor fit with coverage frameworks (100%); insufficient evidence (100%); departure from pedigree/family history-based testing toward genetic screening (91%); lacking rigor in the HCP hybrid research/clinical setting (82%); and patient transparency and involvement concerns (82%). Addressing barriers requires refining HCP-indicated populations (82%); developing evidence of actionability (82%) and pathogenicity/penetrance (64%); creating infrastructure and standards for informing and recontacting patients (45%); separating research from clinical use in the hybrid clinical-research setting (44%); and adjusting coverage frameworks (18%). Conclusions: Leveraging opportunities suggested by payers to address HCP coverage barriers is essential to ensure patients' access to evolving HCPs. Our findings inform 3 areas of the PMI: addressing insurance coverage to secure access to future PMI discoveries; incorporating payers' evidentiary requirements into PMI's research agenda; and leveraging payers' recommendations and experience to keep patients informed and involved.

OBJECTIVES:The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions. METHODS:We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study. RESULTS:Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73-100 percent), clinical studies in 69 percent (50-87 percent), technology assessments 47 percent (33-86 percent), systematic reviews or meta-analyses 31 percent (7-71 percent), and CEAs 5 percent (0-7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types. CONCLUSIONS:Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.

BackgroundNew payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs.ObjectivesTo understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations.MethodsWe interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis.ResultsWe found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs' decision making in terms of achieving a balance between the components of the Triple Aim-improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs' decisions and ACOs' insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients' interest in personalized medicine.ConclusionsAs new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations.

Germline genetic testing for inherited cancer risk has shifted to multi-gene panel tests (MGPTs). While MGPTs detect more pathogenic variants, they also detect more variants of uncertain significance (VUSs) that increase the possibility of harms such as unnecessary surgery. Data sharing by laboratories is critical to addressing the VUS problem. However, barriers to sharing and an absence of incentives have limited laboratory contributions to the ClinVar database. Payers can play a crucial role in the expansion of knowledge and effectiveness of genetic testing. Current policies affecting MGPT reimbursement are complex and create perverse incentives. Trends in utilization and coverage for private payers and Medicare illustrate opportunities and challenges for data sharing to close knowledge gaps and improve clinical utility. Policy options include making data sharing (i) a condition of payment, and (ii) a metric of laboratory quality in payment contracts, yielding preferred coverage or enhanced reimbursement. Mandating data sharing sufficient to verify interpretations and resolve discordance among labs under Medicare and federal health programs is an option for the US Congress. Such policies can reduce the current waste of valuable data needed for precision oncology and improved patient outcomes, enabling a learning health system. [ABSTRACT FROM AUTHOR]

Patients covered by a health care plan that uses a drug formulary may stop taking some drugs that are necessary, according to a study of two health care plans that implemented a three-tier drug formulary. This type of formulary charges patients higher co-payments if they use a three-tier brand-name drug that is not preferred by the organization. Twenty-one percent of the patients who were taking a statin drug stopped taking it when the formulary was implemented.