Preferences and values for rapid genomic testing in critically ill infants and children: a discrete choice experiment

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.

Preferences for public health insurance coverage of new anticancer drugs: a discrete choice experiment among non-small cell lung cancer patients in China

BACKGROUND

Ensuring equal access to affordable, high-quality, and satisfied healthcare for cancer patients is a challenge worldwide. Our study aimed to investigate preferences for public health insurance coverage of new anticancer drugs among non-small cell lung cancer (NSCLC) patients in China.

METHODS

We identified six attributes of new anticancer drugs and adopted a Bayesian-efficient design to generate choice scenarios for a discrete choice experiment (DCE). The one-on-one, face-to-face DCE was conducted in four cities in Jiangsu Province. The mixed logit regression model was used to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity.

RESULTS

Data from 486 patients were available for analysis. The most valuable attribute was the out-of-pocket cost if reimbursed (RI = 32.25%), followed by extension of overall survival (RI = 15.99%), and low incidence of serious side effects (RI = 14.45%). Patients had the highest willingness to pay for the comparative 9-month' extension of overall survival. Patients with advanced NSCLC were more likely to expect new anticancer drugs could improve HRQoL (p < 0.01) and require fewer out-of-pocket costs (p < 0.01). Older patients and patients with low income cared more about the out-of-pocket costs (p < 0.001).

CONCLUSION

Health insurance policymakers need to consider the affordability, comparative survival benefits, comparative safety, and comparative patient-reported outcomes of new anticancer drugs. The findings also highlight the need to ensure affordability for older patients, low-income patients, and patients with advanced cancer.

Determining priority indicators of utility for genomic testing in rare disease: A Delphi study

PURPOSE

Determining the value of genomic tests in rare disease necessitates a broader conceptualization of genomic utility beyond diagnostic yield. Despite widespread discussion, consensus toward which aspects of value to consider is lacking. This study aimed to use expert opinion to identify and refine priority indicators of utility in rare disease genomic testing.

METHODS

We used 2 survey rounds following Delphi methodology to obtain consensus on indicators of utility among experts involved in policy, clinical, research, and consumer advocacy leadership in Australia. We analyzed quantitative and qualitative data to identify, define, and determine priority indicators.

RESULTS

Twenty-five experts completed round 1 and 18 completed both rounds. Twenty indicators reached consensus as a priority in value assessment, including those relating to prognostic information, timeliness of results, practical and health care outcomes, clinical accreditation, and diagnostic yield. Whereas indicators pertaining to discovery research, disutility, and factors secondary to primary reason for testing were considered less of a priority and were removed.

CONCLUSION

This study obtained expert consensus on different utility indicators that are considered a priority in determining the value of genomic testing in rare disease in Australia. Indicators may inform a standardized approach to evidence generation and assessment to guide future research, decision making, and implementation efforts.

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.

Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments

BACKGROUND

Understanding service user preferences is key to effective health care decision making and efficient resource allocation. It is of particular importance in the management of high-risk patients in whom predictive genetic testing can alter health outcomes.

PURPOSE

This review aims to identify the relative importance and willingness to pay for attributes of genetic testing in hereditary cancer syndromes.

DATA SOURCES

Searches were conducted in Medline, Embase, PsycINFO, HMIC, Web of Science, and EconLit using discrete choice experiment (DCE) terms combined with terms related to hereditary cancer syndromes, malignancy synonyms, and genetic testing.

STUDY SELECTION

Following independent screening by 3 reviewers, 7 studies fulfilled the inclusion criteria, being a DCE investigating patient or public preferences related to predictive genetic testing for hereditary cancer syndromes.

DATA EXTRACTION

Extracted data included study and respondent characteristics, DCE attributes and levels, methods of data analysis and interpretation, and key study findings.

DATA SYNTHESIS

Studies covered colorectal, breast, and ovarian cancer syndromes. Results were summarized in a narrative synthesis and the quality assessed using the Lancsar and Louviere framework.

LIMITATIONS

This review focuses only on DCE design and testing for hereditary cancer syndromes rather than other complex diseases. Challenges also arose from heterogeneity in attributes and levels.

CONCLUSIONS

Test effectiveness and detection rates were consistently important to respondents and thus should be prioritized by policy makers. Accuracy, cost, and wait time, while also important, showed variation between studies, although overall reduction in cost may improve uptake. Patients and the public would be willing to pay for improved detection and clinician over insurance provider involvement. Future studies should seek to contextualize findings by considering the impact of sociodemographic characteristics, health system coverage, and insurance policies on preferences.

HIGHLIGHTS

Test effectiveness and detection rates are consistently important to respondents in genetic testing for hereditary cancer syndromes.Reducing the cost of genetic testing for hereditary cancer syndromes may improve uptake.Individuals are most willing to pay for a test that improves detection rates, identifies multiple cancers, and for which results are shared with a doctor rather than with an insurance provider.

Eliciting parental preferences and values for the return of additional findings from genomic sequencing

Health economic evidence is needed to inform the design of high-value and cost-effective processes for returning genomic results from analyses for additional findings (AF). This study reports the results of a discrete-choice experiment designed to elicit preferences for the process of returning AF results from the perspective of parents of children with rare conditions and to estimate the value placed on AF analysis. Overall, 94 parents recruited within the Australian Genomics and Melbourne Genomics programmes participated in the survey, providing preferences in a total of 1128 choice scenarios. Statistically significant preferences were identified for the opportunity to change the choices made about AF; receiving positive AF in person from a genetic counsellor; timely access to a medical specialist and high-quality online resources; receiving automatic updates through a secure online portal if new information becomes available; and lower costs. For AF uptake rates ranging between 50-95%, the mean per person value from AF analysis was estimated at AU$450-$1700 (US$300-$1140). The findings enable the design of a value-maximising process of analysis for AF in rare-disease genomic sequencing.

QALYs and rare diseases: exploring the responsiveness of SF-6D, EQ-5D-5L and AQoL-8D following genomic testing for childhood and adult-onset rare genetic conditions in Australia

BACKGROUND

Genomic testing transforms the diagnosis and management of rare conditions. However, uncertainty exists on how to best measure genomic outcomes for informing healthcare priorities. Using the HTA-preferred method should be the starting point to improve the evidence-base. This study explores the responsiveness of SF-6D, EQ-5D-5L and AQoL-8D following genomic testing across childhood and adult-onset genetic conditions.

METHOD

Self-reported patient-reported outcomes (PRO) were obtained from: primary caregivers of children with suspected neurodevelopmental disorders (NDs) or genetic kidney diseases (GKDs) (carers' own PRO), adults with suspected GKDs using SF-12v2; adults with suspected complex neurological disorders (CNDs) using EQ-5D-5L; and adults with dilated cardiomyopathy (DCM) using AQol-8D. Responsiveness was assessed using the standardised response mean effect-size based on diagnostic (having a confirmed genomic diagnosis), personal (usefulness of genomic information to individuals or families), and clinical (clinical usefulness of genomic information) utility anchors.

RESULTS

In total, 254 people completed PRO measures before genomic testing and after receiving results. For diagnostic utility, a nearly moderate positive effect size was identified by the AQoL-8D in adult DCM patients. Declines in physical health domains masked any improvements in mental or psychosocial domains in parents of children affected by NDs and adult CNDs and DCM patients with confirmed diagnosis. However, the magnitude of the changes was small and we did not find statistically significant evidence of these changes. No other responsiveness evidence related to diagnostic, clinical, and personal utility of genomic testing was identified.

CONCLUSION

Generic PRO measures may lack responsiveness to the diagnostic, clinical and personal outcomes of genomics, but further research is needed to establish their measurement properties and relevant evaluative space in the context of rare conditions. Expected declines in the physical health of people experiencing rare conditions may further challenge the conventional application of quality of life assessments.

Case report: Two unexpected cases of DGUOK-related mitochondrial DNA depletion syndrome presenting with hyperinsulinemic hypoglycemia

Timely diagnosis of persistent neonatal hypoglycemia is critical to prevent neurological sequelae, but diagnosis is complicated by the heterogenicity of the causes. We discuss two cases at separate institutions in which clinical management was fundamentally altered by the results of molecular genetic testing. In both patients, critical samples demonstrated hypoketotic hypoglycemia and a partial glycemic response to glucagon stimulation, thereby suggesting hyperinsulinism (HI). However, due to rapid genetic testing, both patients were found to have deoxyguanosine kinase (DGUOK)-related mitochondrial DNA depletion syndrome, an unexpected diagnosis. Patients with this disease typically present with either hepatocerebral disease in the neonatal period or isolated hepatic failure in infancy. The characteristic features involved in the hepatocerebral form of the disease include lactic acidosis, hypoglycemia, cholestasis, progressive liver failure, and increasing neurologic dysfunction. Those with isolated liver involvement experience hepatomegaly, cholestasis, and liver failure. Although liver transplantation is considered, research has demonstrated that for patients with DGUOK-related mitochondrial DNA depletion syndrome and neurologic symptoms, early demise occurs. Our report advocates for the prompt initiation of genetic testing in patients presenting with persistent neonatal hypoglycemia and for the incorporation of mitochondrial DNA depletion syndromes in the differential diagnosis of HI.

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.

Rapid Genetic Testing in Pediatric and Neonatal Critical Care: A Scoping Review of Emerging Ethical Issues

BACKGROUND

Rapid genome-wide sequencing (rGWS) is being increasingly used to aid in prognostication and decision-making for critically ill newborns and children. Although its feasibility in this fast-paced setting has been described, this new paradigm of inpatient genetic care raises new ethical challenges.

OBJECTIVE

A scoping review was performed to (1) identify salient ethical issues in this area of practice; and (2) bring attention to gaps and ethical tensions that warrant more deliberate exploration.

METHODS

Data sources, Ovid Medline and Cochrane Central Register of Controlled Trials, were searched up to November 2021. Articles included were those in English relating to rGWS deployed rapidly in a critical care setting. Publications were examined for ethical themes and were further characterized as including a superficial or in-depth discussion of that theme. New themes were inductively identified as they emerged.

RESULTS

Ninety-nine studies, published in 2012 or thereafter, met inclusion criteria. Themes identified elaborated upon established ethical principles related to beneficence and nonmaleficence (ie, clinical utility, medical uncertainty, impact on family, and data security) autonomy (ie, informed consent), and justice (ie, resource allocation and disability rights). Many themes were only narrowly discussed.

CONCLUSIONS

The application of rGWS in neonatal and pediatric acute care is inherently tied to ethically charged issues, some of which are reported here. Attention to the ethical costs and benefits of rGWS is not always discussed, with important gaps and unanswered questions that call for ongoing focus on these ethical considerations in this next application of acute care genomics.

Is faster better? An economic evaluation of rapid and ultra-rapid genomic testing in critically ill infants and children

PURPOSE

To evaluate whether the additional cost of providing increasingly faster genomic results in pediatric critical care is outweighed by reductions in health care costs and increases in personal utility.

METHODS

Hospital costs and medical files from a cohort of 40 children were analyzed. The health economic impact of rapid and ultra-rapid genomic testing, with and without early initiation, relative to standard genomic testing was evaluated.

RESULTS

Shortening the time to results led to substantial economic and personal benefits. Early initiation of ultra-rapid genomic testing was the most cost-beneficial strategy, leading to a cost saving of AU$26,600 per child tested relative to standard genomic testing and a welfare gain of AU$12,000 per child tested. Implementation of early ultra-rapid testing of critically ill children is expected to lead to an annual cost saving of AU$7.3 million for the Australian health system and an aggregate welfare gain of AU$3.3 million, corresponding to a total net benefit of AU$10.6 million.

CONCLUSION

Early initiation of ultra-rapid genomic testing can offer substantial economic and personal benefits. Future implementation of rapid genomic testing programs should focus not only on optimizing the laboratory workflow to achieve a fast turnaround time but also on changing clinical practice to expedite test initiation.

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

OBJECTIVES

The aim of this study was to elicit the willingness-to-pay (WTP) for genomic testing, using contingent valuation, among people with lived experience of genetic conditions in Australia.

METHODS

Parents of children with suspected mitochondrial disorders, epileptic encephalopathy, leukodystrophy, or malformations of cortical development completed a dynamic triple-bounded dichotomous choice (DC) contingent valuation. Adult patients or parents of children with suspected genetic kidney disease or complex neurological and neurodegenerative conditions completed a payment card (PC) contingent valuation. DC data were analyzed using a multilevel interval regression and a multilevel probit model. PC data were analyzed using a Heckman selection model.

RESULTS

In total, 360 individuals participated in the contingent valuation (CV), with 141 (39%) and 219 (61%) completing the DC and PC questions, respectively. The mean WTP for genomic testing was estimated at AU$2830 (95% confidence interval [CI] 2236-3424) based on the DC data and AU$1914 (95% CI 1532-2296) based on the PC data. The mean WTP across the six cohorts ranged from AU$1879 (genetic kidney disease) to AU$4554 (leukodystrophy).

CONCLUSIONS

Genomic testing is highly valued by people experiencing rare genetic conditions. Our findings can inform cost-benefit analyses and the prioritization of genomics into mainstream clinical care. While our WTP estimates for adult-onset genetic conditions aligned with estimates derived from discrete choice experiments (DCEs), for childhood-onset conditions our estimates were significantly lower. Research is urgently required to directly compare, and critically evaluate, the performance of CV and DCE methods.

Rapid genomic testing for critically ill children: time to become standard of care?

Rapid genomic testing in critically ill neonatal and paediatric patients has transformed the paradigm of rare disease diagnosis, delivering results in real time to inform patient management. More than 20 studies totalling over 1500 patients from diverse healthcare settings worldwide have now been published, forming a compelling evidence base for healthcare system implementation. We review the reported diagnostic and clinical outcomes, as well as broader evaluations of family and professional experiences, cost effectiveness, implementation challenges and bioethical issues arising from rapid testing. As rapid genomic testing transitions from the research to the healthcare setting to become a 'standard of care' test, there is a need to develop effective service delivery models to support scalability at both the laboratory and clinical level and promote equity of access, prompt test initiation, integrated multidisciplinary input and holistic family support. Harnessing the high level of professional engagement with rapid genomic testing programmes will continue to drive innovation and adoption, while close integration with emerging precision medicine approaches will be necessary to deliver on the promise of reduced infant and child mortality.