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Purpose: Healthcare stakeholders' perspectives on the value of genomic testing vary widely and directly impact the access and practice of genomic medicine. A review of United States healthcare payers' perspectives on genomic testing has not been performed., Methods: We conducted a systematic literature review of US payers' perspectives on genomic testing in the MEDLINE, PubMed and CINAHL databases. Of the 161 nonduplicate records screened, we summarized findings from 20 included records and using the framework method, common domains were recorded., Results: Domains included clinical utility, coverage decision frameworks, potential harms, costs, "paying for research," demand/pressure, the flexibility of outcomes considered, and personal utility. There was consensus on the definition of clinical utility as improved health outcomes, and the nuances of genomic testing were reported as challenging to fit within existing coverage decision frameworks. Perspectives varied on accepting broader outcomes or uses of genomic testing and whether costs influence coverage decisions. Study methodologies were heterogeneous., Conclusion: A deeper understanding of how payers approach genomic testing may allow comparison to other stakeholders' perspectives and may identify challenges, opportunities, and solutions to align a conceptual and evidentiary framework better to demonstrate the value of genomic testing., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: As population-based screening programs to identify genetic conditions in adults using genomic sequencing (GS) are increasingly available, validated patient-centered outcome measures are needed to understand participants' experience. We aimed to develop and validate an instrument to assess the perceived utility of GS in the context of adult screening., Methods: Informed by a 5-domain conceptual model, we used a 5-step approach to instrument development and validation: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Adults undergoing risk-based or population-based GS who had received GS results as part of ongoing research studies participated in structured cognitive interviews and 2 rounds of surveys. After item pool refinement, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments., Results: We derived the 18-item Adult Screening version of the GENEtic Utility scale (total sum score α = .87). Mirroring the Pediatric Diagnostic version, the instrument has a 2-factor structure, including an Informational Utility subscale (14 items, α = .89) and an Emotional Utility subscale (4 items, α = .75). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS. Correlations of the Emotional Utility subscale with psychosocial impact and anxiety and depression were weak to moderate., Conclusion: Initial psychometric testing of the Adult Screening GENEtic Utility scale demonstrates its promise, and additional validation in translational genomics research is warranted., Competing Interests: Conflict of Interest Dr Smith’s work has been funded by the NIH. She has received compensation as a consultant for Illumina, Inc and RTI International, unrelated to this work. Mr Buchanan has an equity stake in MeTree, Inc and You, Inc, unrelated to this work. Dr McGuire is a member of the Scientific Advisory Board for Nurture Genomics. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Elective genomic testing (EGT) is increasingly available clinically. Limited real-world evidence exists about attitudes and knowledge of EGT recipients., Methods: After web-based education, patients who enrolled in an EGT program at a rural nonprofit health care system completed a survey that assessed attitudes, knowledge, and risk perceptions., Results: From August 2020 to April 2022, 5920 patients completed the survey and received testing. Patients most frequently cited interest in learning their personal disease risks as their primary motivation. Patients most often expected results to guide medication management (74.0%), prevent future disease (70.4%), and provide information about risks to offspring (65.4%). Patients were "very concerned" most frequently about the privacy of genetic information (19.8%) and how well testing predicted disease risks (18.0%). On average, patients answered 6.7 of 11 knowledge items correctly (61.3%). They more often rated their risks for colon and breast cancers as lower rather than higher than the average person but more often rated their risk for a heart attack as higher rather than lower than the average person (all P < .001)., Conclusion: Patients pursued EGT because of the utility expectations but often misunderstood the test's capabilities., Competing Interests: Conflict of Interest Robert C. Green, Kurt D. Christensen, Emilie S. Zoltick, Madison R. Hickingbotham, Jessica L. LeBlanc, and Lauren N. Galbraith were supported by a research grant from Sanford Health. Madison R. Hickingbotham, Madison R. Hickingbotham, Ann Chen Wu, Lauren N. Galbraith, and Jessica L. LeBlanc have been funded by National Center for Advancing Translational Sciences (NCATS), National Heart, Lung, and Blood Institute (NHLBI), and National Institute of Child Health and Human Development (NICHD). Ann Chen Wu has received grants from NICHD, NHLBI, and GlaxoSmithKline. Catherine Hajek is an employee of Helix OpCo. Christine Y. Lu undertook contract work with Illumina Inc outside the submitted work and has received research grants and contracts from National Human Genome Research Institute (NHGRI), NIMH, NICHD, National Cancer Institute, and Centers for Disease Control and Prevention. Emilie S. Zoltick has been funded by NIMHD. Hadley Stevens Smith has been funded by NHGRI and NICHD, has consulted for Illumina, Inc and received compensation, and has received compensation from Elsevier and the Eastern Society of Pediatric Research. Kurt D. Christensen has received research grants from NHGRI, NCATS, NHLBI, and NICHD. Lauren N. Galbraith is an employee of Pfizer, Inc. Robert C. Green has received compensation for advising the following companies: AIA, Allelica, Atria, Fabric, Genome Web, Genomic Life, Verily, and VinBigData; is cofounder of Genome Medical and Nurture Genomics; and has received research grants from NCATS, NHLBI, the Danaher Foundation, the Southcentral Foundation, GRAIL, and Beaumont Health. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Measuring the effects of genomic sequencing (GS) on patients and families is critical for translational research. We aimed to develop and validate an instrument to assess parents' perceived utility of pediatric diagnostic GS., Methods: Informed by a 5-domain conceptual model, the study comprised 5 steps: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Parents of pediatric patients who had received results of clinically indicated GS participated in structured cognitive interviews and 2 rounds of surveys. After eliminating items based on theory and quantitative performance, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments., Results: We derived the 21-item Pediatric Diagnostic version of the GENEtic Utility (GENE-U) scale, which has a 2-factor structure that includes an Informational Utility subscale (16 items, α = 0.91) and an Emotional Utility subscale (5 items, α = 0.71). Scores can be summed to calculate a Total scale score (α = 0.87). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS, and the Emotional Utility subscale was moderately associated with psychosocial impact and depression and anxiety., Conclusion: The pediatric diagnostic GENE-U scale demonstrated good psychometric performance in this initial evaluation and could be a useful tool for translational genomics researchers, warranting additional validation., Competing Interests: Conflict of Interest Hadley Stevens Smith’s work has been funded by the NIH. She has received compensation as a consultant for Illumina, Inc unrelated to this work. Amy L. McGuire is a member of the Scientific Advisory Board for Nurture Genomics. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Cascade testing, the process of testing a proband's at-risk relatives, is integral to realizing the full value of genomic sequencing. However, there is little empirical evidence on the uptake of cascade testing after a positive exome sequencing (ES) result in a population of probands with diverse clinical indications., Methods: We retrospectively reviewed administrative data from 2 US clinical laboratories that perform ES. For each proband with a positive ES result, we used linked family data to describe the frequency of relatives' cascade testing performed at the same laboratory, variant detection yield of cascade tests, and characteristics of probands and relatives categorized on the basis of cascade testing completion., Results: Among the 3723 positive ES results across both laboratories, 426 relatives of 282 probands completed cascade testing (uptake = 7.6%). An average of 1.5 relatives (SD = 0.9) were tested per proband. Of the 426 relatives tested, 200 had a variant of interest detected (variant detection yield = 47.0%)., Conclusion: In our real-world data analysis, a small proportion of probands with a positive ES result subsequently had relatives complete cascade testing at the same laboratory. However, approximately half of the tested relatives received a clinically significant result that could have implications for clinical management or reproductive planning. Additional research on ways to increase cascade testing uptake is warranted., Competing Interests: Conflict of Interest H.S.S. and H.S. declare no conflict of interest. J.S. and M.T. are salaried employees at Ambry Genetics, a Konica Minolta, Inc company. Baylor College of Medicine and Miraca Holdings Inc have formed a joint venture with shared ownership and governance of Baylor Genetics, which performs genetic testing and derives revenue. P.L. is an employee of Baylor College of Medicine and derives support through a professional services agreement with Baylor Genetics., (Copyright © 2023 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Little is known about how Medicaid coverage policies affect access to genetic tests for pediatric patients. Building upon and extending a previous analysis of prior authorization requests (PARs), we describe expected coverage of genetic tests submitted to Texas Medicaid and the PAR and diagnostic outcomes of those tests., Methods: We retrospectively reviewed genetic tests ordered at 3 pediatric outpatient genetics clinics in Texas. We compared Current Procedural Terminology (CPT) codes with the Texas Medicaid fee-for-service schedule (FFSS) to determine whether tests were expected to be covered by Medicaid. We assessed completion and diagnostic yield of commonly ordered tests., Results: Among the 3388 total tests submitted to Texas Medicaid, 68.9% (n = 2336) used at least 1 CPT code that was not on the FFSS and 80.7% (n = 2735) received a favorable PAR outcome. Of the tests with a CPT code not on the FFSS, 60.0% (n = 1400) received a favorable PAR outcome and were completed and 20.5% (n = 287) were diagnostic. The diagnostic yield of all tests with a favorable PAR outcome that were completed was 18.7% (n = 380/2029)., Conclusion: Most PARs submitted to Texas Medicaid used a CPT code for which reimbursement from Texas Medicaid was not guaranteed. The frequency with which clinically indicated genetic tests were not listed on the Texas Medicaid FFSS suggests misalignment between genetic testing needs and coverage policies. Our findings can inform updates to Medicaid policies to reduce coverage uncertainty and expand access to genetic tests with high diagnostic utility., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Background: Increasing diversity in clinical trial participation is necessary to improve health outcomes and requires addressing existing social, structural, and geographic barriers. The Clinical Sequencing Evidence-Generating Research Consortium (CSER) included six research projects to enroll historically underrepresented/underserved (UR/US) populations in clinical genomics research. Delays and project re-designs emerged shortly after work began. Understanding common experiences of these projects may inform future trial implementation., Methods: Semi-structured interviews with six CSER principal investigators and seven project managers were performed. An interview guide included questions of research/clinical infrastructure, logistics across sites, language, communication, and allocation of grant-related resources. Interviews were recorded, transcribed verbatim; transcripts were analyzed using inductive coding, thematic analysis and consensus building., Results: All projects collaborating with new clinical sub-sites to recruit UR/US populations. Refining trial logistics continued long after enrollment for all projects. Themes of challenges included: sub-site customization for workflow and genetics support, conflicting input from participant advisory groups and approval bodies, developing research personnel, complex data management structures, and external changes (e.g. subcontractors ending contracts) that required redesign. Themes of beneficial lessons included: domains with prior experience were easier, develop project champions at each sub-site, structure communication within the research team, and simplify research design when possible., Conclusions: The operational aspects of expanding clinical research into novel sub-sites are significant and require investment of time and resources. The themes arising from these interviews suggest priority areas for more quantitative analyses in the future including multi-institutional approval policies and processes, data management structures, and incremental research complexity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: Methodological challenges have limited economic evaluations of genome sequencing (GS) and exome sequencing (ES). Our objective was to develop conceptual frameworks for model-based cost-effectiveness analyses (CEAs) of diagnostic GS/ES., Methods: We conducted a scoping review of economic analyses to develop and iterate with experts a set of conceptual CEA frameworks for GS/ES for prenatal testing, early diagnosis in pediatrics, diagnosis of delayed-onset disorders in pediatrics, genetic testing in cancer, screening of newborns, and general population screening., Results: Reflecting on 57 studies meeting inclusion criteria, we recommend the following considerations for each clinical scenario. For prenatal testing, performing comparative analyses of costs of ES strategies and postpartum care, as well as genetic diagnoses and pregnancy outcomes. For early diagnosis in pediatrics, modeling quality-adjusted life years (QALYs) and costs over ≥20 years for rapid turnaround GS/ES. For hereditary cancer syndrome testing, modeling cumulative costs and QALYs for the individual tested and first/second/third-degree relatives. For tumor profiling, not restricting to treatment uptake or response and including QALYs and costs of downstream outcomes. For screening, modeling lifetime costs and QALYs and considering consequences of low penetrance and GS/ES reanalysis., Conclusion: Our frameworks can guide the design of model-based CEAs and ultimately foster robust evidence for the economic value of GS/ES., Competing Interests: Conflict of Interest K.F.M. has received institutional support from GE Healthcare. D.L.V has received institutional support from Foundation Medicine. All other authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. All rights reserved.)

Purpose: There is limited payer coverage for genome sequencing (GS) relative to exome sequencing (ES) in the U.S. Our objective was to assess payers' considerations for coverage of GS versus coverage of ES and requirements payers have for coverage of GS. The study was conducted by the NIH-funded Clinical Sequencing Evidence-Generating Research Consortium (CSER)., Methods: We conducted semi-structured interviews with representatives of private payer organizations (payers, N = 12) on considerations and evidentiary and other needs for coverage of GS and ES. Data were analyzed using thematic analysis., Results: We described four categories of findings and solutions: demonstrated merits of GS versus ES, enhanced methods for evidence generation, consistent laboratory processes/sequencing methods, and enhanced implementation/care delivery. Payers see advantages to GS vs. ES and are open to broader GS coverage but need more proof of these advantages to consider them in coverage decision-making. Next steps include establishing evidence of benefits in specific clinical scenarios, developing quality standards, ensuring transparency of laboratory methods, developing clinical centers of excellence, and incorporating the role of genetic professionals., Conclusion: By comparing coverage considerations for GS and ES, we identified a path forward for coverage of GS. Future research should explicitly address payers' conditions for coverage., Competing Interests: Conflict of Interest Dr. Phillips receives consulting income from Illumina, Inc, not related to this manuscript. Mr. Douglas receives consulting income from Illumina, Inc, not related to this manuscript. Dr. Slavotinek receives consulting income from UptoDate, Inc and income for editorial duties from John Wiley & Sons, Inc. All other authors: declare no conflicts of interest., (Copyright © 2021 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Genetic testing is an important diagnostic tool in pediatric genetics clinics, yet many patients face barriers to testing. We describe the outcomes of prior authorization requests (PARs) for genetic tests, one indicator of patient access to clinically recommended testing, in pediatric genetics clinics., Methods: We retrospectively reviewed PARs for genetic tests (n = 4,535) recommended for patients <18 years of age (n = 2,798) by pediatric medical geneticists at two children's hospitals in Texas, 2017-2018. We described PAR outcomes, accompanying diagnostic codes, and diagnostic yield., Results: The majority (79.9%) of PARs received a favorable outcome. PARs submitted to public payers were more likely to receive a favorable outcome compared with private payers (85.5% vs. 70.3%, respectively; p < 0.001). No diagnostic codes were associated with higher likelihood of PAR approval for exome sequencing. Among the 2,685 tests approved and completed, 522 (19.4%) resulted in a diagnosis., Conclusion: Though there was a high PAR approval rate, our findings suggest that insurance coverage remains one barrier to genetic testing. When completed, genetic testing had a high yield in our sample. Further evidence of clinical utility and development of clinical practice guidelines may inform payer medical policy development and improve access to testing in the future.

Purpose: As exome sequencing (ES) is increasingly used as a diagnostic tool, we aimed to compare ES with status quo genetic diagnostic workup for infants with suspected genetic disorders in terms of identifying diagnoses, survival, and cost of care., Methods: We studied newborns and infants admitted to intensive care with a suspected genetic etiology within the first year of life at a US quaternary-referral children's hospital over 5 years. In this propensity-matched cohort study using electronic medical record data, we compared patients who received ES as part of a diagnostic workup (ES cohort, n = 368) with clinically similar patients who did not receive ES (No-ES cohort, n = 368)., Results: Diagnostic yield (27.4% ES, 25.8% No-ES; p = 0.62) and 1-year survival (80.2% ES, 84.8% No-ES; p = 0.10) were no different between cohorts. ES cohort patients had higher cost of admission, diagnostic investigation, and genetic testing (all p < 0.01)., Conclusion: ES did not differ from status quo genetic testing collectively in terms of diagnostic yield or patient survival; however, it had high yield as a single test, led to complementary classes of diagnoses, and was associated with higher costs. Further work is needed to define the most efficient use of diagnostic ES for critically ill newborns and infants.

Purpose: Availability of clinical genomic sequencing (CGS) has generated questions about the value of genome and exome sequencing as a diagnostic tool. Analysis of reported CGS application can inform uptake and direct further research. This scoping literature review aims to synthesize evidence on the clinical and economic impact of CGS., Methods: PubMed, Embase, and Cochrane were searched for peer-reviewed articles published between 2009 and 2017 on diagnostic CGS for infant and pediatric patients. Articles were classified according to sample size and whether economic evaluation was a primary research objective. Data on patient characteristics, clinical setting, and outcomes were extracted and narratively synthesized., Results: Of 171 included articles, 131 were case reports, 40 were aggregate analyses, and 4 had a primary economic evaluation aim. Diagnostic yield was the only consistently reported outcome. Median diagnostic yield in aggregate analyses was 33.2% but varied by broad clinical categories and test type., Conclusion: Reported CGS use has rapidly increased and spans diverse clinical settings and patient phenotypes. Economic evaluations support the cost-saving potential of diagnostic CGS. Multidisciplinary implementation research, including more robust outcome measurement and economic evaluation, is needed to demonstrate clinical utility and cost-effectiveness of CGS.