The Value of Genomic Testing: A Contingent Valuation Across Six Child- and Adult-Onset Genetic Conditions

Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework

INTRODUCTION

Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention's cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations. The objective of this study was to explore approaches for incorporating preferences into model-based economic evaluations of genomic medicine and to develop a conceptual framework to consider preferences in health economic models.

METHODS

We conducted a critical interpretive synthesis of published literature guided by the following question: how have preferences been incorporated into model-based economic evaluations of genomic medicine interventions? We integrated findings from the literature and expert opinion to develop a conceptual framework of ways in which preferences influence economic value in the context of genomic medicine.

RESULTS

Our synthesis included 14 articles. Revealed and stated preference data were used to estimate choice probabilities and to value outcomes. Our conceptual framework situates preference data in the context of health system, patient, clinician, and family characteristics. Preference data were sourced from clinicians, patients and families impacted by a condition or intervention, and the general public. Evaluations employed various types of models, including discrete event simulation, microsimulation, Markov, and decision tree models.

CONCLUSION

When evaluating the broad benefits and costs of implementing new interventions, sufficiently accounting for preferences in the form of model inputs and valuation of outcomes in economic evaluations is important to avoid biased implementation decisions. Incorporation of preference data may improve alignment between predicted and real-world uptake and more accurately estimate welfare impacts, and this study provides critical insights to support researchers who seek to incorporate preference information into model-based health economic evaluations.

Beyond the Diagnosis: Valuing Genome-Wide Sequencing for Rare Disease Diagnosis Using Contingent Valuation

BACKGROUND AND OBJECTIVE

The utility of genome-wide sequencing is often quantified in terms of its diagnostic yield. Although obtaining a diagnosis is a fundamental aspect of value, service users also value broader clinical, informational, process and psychological factors in the provision of genomic testing. This study aims to value genome-wide sequencing from the user perspective in Scotland.

METHODS

A survey was developed and administered to 1014 patients and families with experience of genome-wide sequencing to diagnose a rare condition in Scotland. Participants' willingness to pay for genomic testing was elicited using a contingent valuation payment card. The survey included two genomic-related patient-reported outcome measures: (i) the Personal Utility Scale (PrU) to generate scores for the personal utility of genome-wide sequencing; and (ii) a subscale of the Feelings About Genomic Testing Results (FACTOR) questionnaire to measure negative psychological outcomes. Data were also collected on participants' prior experiences of genomic testing services. A double-hurdle regression model investigated the predictors of patients' willingness to pay for genomic testing.

RESULTS

Of the 1014 invitations sent, 171 contingent valuation questionnaires were returned. Diagnosed participants reported higher personal utility on PrU than undiagnosed participants. However, both groups reported similar negative psychological outcomes on FACTOR. Diagnosed participants were willing to pay £2043 for genome-wide sequencing, compared with £835 for undiagnosed participants. Diagnostic status, waiting time for results and FACTOR scores (negative psychological outcomes) influenced users' valuations of genome-wide sequencing.

CONCLUSIONS

Obtaining a diagnosis is a fundamental component of utility in the provision of genomic testing. However, there is still value to those who do not receive a diagnosis. These results have implications for service delivery, such as providing targeted pre-test and post-test genetic counselling, and investing in efficient genome sequencing pipelines to reduce waiting times. Valuing the user experience of genomic testing aligns with patient-centred approaches to the provision of healthcare.

A Standardized Measurement and Valuation Scale of Genomic Utility for Policy Decisions: The GUV Scale

OBJECTIVES

The multifaceted ways in which genomics can be valuable to clinicians, patients, families, and society are important for informing prioritization decisions by policy makers. This study aims to develop a standardized, cumulative, and preference-weighted genomic utility valuation (GUV) on a scale of 0% to 100%.

METHODS

A multicriteria decision analysis was conducted with experts involved in policy, clinical, research, and consumer advocacy leadership in Australia for the valuation of policy priority indicators of genomic utility. The use of the GUV scale to support policy decisions is illustrated through a stylized example, and benchmark scoring thresholds of genomic utility were identified by mapping evidence from real-world health technology assessments leading to the public reimbursement of genomic testing in Australia onto the GUV scale.

RESULTS

In total, 33 (73%) invited experts participated in the study. Clinical utility had the highest priority, followed by societal, diagnostic, economic, and family utilities. Improving health outcomes had the highest preference value (29.5%), followed by improving equity (22.6%), Having high diagnostic yield (22.2%), improving symptom management (15.5%), being cost saving (14.3%), having average diagnostic yield (13.1%), enabling access to clinical trials (12.3%), and enabling reproductive family planning (11.5%). Genomic testing scores from real-world health technology assessments ranged from 46% for syndromic and nonsyndromic intellectual disability to about 60% for mitochondrial conditions and genetic kidney diseases.

CONCLUSIONS

Comparisons of genomic utility across different clinical contexts may seem difficult because of the multiple criteria required to be weighted to support policy decisions. This comparison is now facilitated in a standardized manner with the GUV scale.

The value of genomic testing in severe childhood speech disorders

With increasing gene discoveries for severe speech disorders, genomic testing can alter the diagnostic and clinical paradigms, enabling better life outcomes for children and their families. However, evidence on the value of the outcomes generated is lacking, impeding optimal translation into health care. This study aims to estimate the value and uptake of genomic testing for severe childhood speech disorders. A discrete choice experiment was undertaken to elicit preferences for genomic testing from the perspective of the Australian public (n = 951) and parents of children experiencing severe speech disorder (n = 56). Choice attributes associated with genomic testing were identified through focus groups. A Bayesian D-efficient design was used to develop choice scenarios and choice data were analyzed using a panel error component mixed logit model and a latent class model. Statistically significant preferences were identified across all seven attributes. The mean monetary value of the benefits of genomic testing relative to standard diagnostic care in Australia was estimated at AU$7489 (US$5021) and AU$4452 (US$2985) from the perspectives of the Australian public and families with lived experience of severe speech disorders, with a corresponding test uptake of 94.2% and 99.6%. To ensure fair prioritization of genomics, decision-makers need to consider the wide range of risks and benefits associated with genomic information.

Genomic testing for suspected monogenic kidney disease in children and adults: A health economic evaluation

PURPOSE

To assess the relative cost-effectiveness of genomic testing compared with standard non-genomic diagnostic investigations in patients with suspected monogenic kidney disease from an Australian health care system perspective.

METHODS

Diagnostic and clinical information was used from a national cohort of 349 participants. Simulation modelling captured diagnostic, health, and economic outcomes during a time horizon from clinical presentation until 3 months post-test results based on the outcome of cost per additional diagnosis and lifetime horizon based on cost per quality-adjusted life-year (QALY) gained.

RESULTS

Genomic testing was Australian dollars (AU$) 1600 more costly per patient and led to an additional 27 diagnoses out of a 100 individuals tested, resulting in an incremental cost-effectiveness ratio of AU$5991 per additional diagnosis. Using a lifetime horizon, genomic testing resulted in an additional cost of AU$438 and 0.04 QALYs gained per individual compared with standard diagnostic investigations, corresponding to an incremental cost-effectiveness ratio of AU$10,823 per QALY gained. Sub-group analyses identified that the results were largely driven by the cost-effectiveness in glomerular diseases.

CONCLUSION

Based on established or expected thresholds of cost-effectiveness, our evidence suggests that genomic testing is very likely to be cost saving for individuals with suspected glomerular diseases, whereas no evidence of cost-effectiveness was found for non-glomerular diseases.

Determining the utility of diagnostic genomics: a conceptual framework

BACKGROUND

Diagnostic efficacy is now well established for diagnostic genomic testing in rare disease. Assessment of overall utility is emerging as a key next step, however ambiguity in the conceptualisation and measurement of utility has impeded its assessment in a comprehensive manner. We propose a conceptual framework to approach determining the broader utility of diagnostic genomics encompassing patients, families, clinicians, health services and health systems to assist future evidence generation and funding decisions. BODY: Building upon previous work, our framework posits that utility of diagnostic genomics consists of three dimensions: the domain or type and extent of utility (what), the relationship and perspective of utility (who), and the time horizon of utility (when). Across the description, assessment, and summation of these three proposed dimensions of utility, one could potentially triangulate a singular point of utility axes of type, relationship, and time. Collectively, the multiple different points of individual utility might be inferred to relate to a concept of aggregate utility.

CONCLUSION

This ontological framework requires retrospective and prospective application to enable refinement and validation. Moving forward our framework, and others which have preceded it, promote a better characterisation and description of genomic utility to inform decision-making and optimise the benefits of genomic diagnostic testing.

Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.