Clinical genomic testing: what matters to key stakeholders?

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.

A micro-costing study of mass-spectrometry based quantitative proteomics testing applied to the diagnostic pipeline of mitochondrial and other rare disorders

BACKGROUND

Mass spectrometry-based quantitative proteomics has a demonstrated utility in increasing the diagnostic yield of mitochondrial disorders (MDs) and other rare diseases. However, for this technology to be widely adopted in routine clinical practice, it is crucial to accurately estimate delivery costs. Resource use and unit costs required to undertake a proteomics test were measured and categorized into consumables, equipment, and labor. Unit costs were aggregated to obtain a total cost per patient, reported in 2023 Australian dollars (AUD). Probabilistic and deterministic sensitivity analysis were conducted to evaluate parameter uncertainty and identify key cost drivers.

RESULTS

The mean cost of a proteomics test was $897 (US$ 607) per patient (95% CI: $734-$1,111). Labor comprised 53% of the total costs. At $342 (US$ 228) per patient, liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was the most expensive non-salary component. An integrated analysis pipeline where all the standard analysis are performed automatically, as well as discounts or subsidized LC-MS/MS equipment or consumables can lower the cost per test.

CONCLUSIONS

Proteomics testing provide a lower-cost option and wider application compared to respiratory chain enzymology for mitochondrial disorders and potentially other functional assays in Australia. Our analysis suggests that streamlining and automating workflows can reduce labor costs. Using PBMC samples may be a cheaper and more efficient alternative to generating fibroblasts, although their use has not been extensively tested yet. Use of fibroblasts could potentially lower costs when fibroblasts are already available by avoiding the expense of isolating PBMCs. A joint evaluation of the health and economic implications of proteomics is now needed to support its introduction to routine clinical care.

Potential clinical applications of advanced genomic analysis in cerebral palsy

Cerebral palsy (CP) has historically been attributed to acquired insults, but emerging research suggests that genetic variations are also important causes of CP. While microarray and whole-exome sequencing based studies have been the primary methods for establishing new CP-gene relationships and providing a genetic etiology for individual patients, the cause of their condition remains unknown for many patients with CP. Recent advancements in genomic technologies offer additional opportunities to uncover variations in human genomes, transcriptomes, and epigenomes that have previously escaped detection. In this review, we outline the use of these state-of-the-art technologies to address the molecular diagnostic challenges experienced by individuals with CP. We also explore the importance of identifying a molecular etiology whenever possible, given the potential for genomic medicine to provide opportunities to treat patients with CP in new and more precise ways.

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.

Balancing the safeguarding of privacy and data sharing: perceptions of genomic professionals on patient genomic data ownership in Australia

There are inherent complexities and tensions in achieving a responsible balance between safeguarding patients' privacy and sharing genomic data for advancing health and medical science. A growing body of literature suggests establishing patient genomic data ownership, enabled by blockchain technology, as one approach for managing these priorities. We conducted an online survey, applying a mixed methods approach to collect quantitative (using scale questions) and qualitative data (using open-ended questions). We explored the views of 117 genomic professionals (clinical geneticists, genetic counsellors, bioinformaticians, and researchers) towards patient data ownership in Australia. Data analysis revealed most professionals agreed that patients have rights to data ownership. However, there is a need for a clearer understanding of the nature and implications of data ownership in this context as genomic data often is subject to collective ownership (e.g., with family members and laboratories). This research finds that while the majority of genomic professionals acknowledge the desire for patient data ownership, bioinformaticians and researchers expressed more favourable views than clinical geneticists and genetic counsellors, suggesting that their views on this issue may be shaped by how closely they interact with patients as part of their professional duties. This research also confirms that stronger health system infrastructure is a prerequisite for enabling patient data ownership, which needs to be underpinned by appropriate digital infrastructure (e.g., central vs. decentralised data storage), patient identity ownership (e.g., limited vs. self-sovereign identity), and policy at both federal and state levels.

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.

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.

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.

Eliciting Societal Preferences for Non-health Outcomes: A Person Trade-Off Study in the Context of Genomics

PURPOSE

Economic evaluations of health technologies traditionally aim to maximize population health outcomes measured by using quality-adjusted life-years (QALYs). Non-health outcomes, however, may have high social value, and their exclusion has the potential to bias decisions regarding allocation of health care resources. This research positions Australian participants as societal decision-makers to explore their willingness to trade-off health gains in adults for non-health benefits in families with a child affected by a rare disease.

METHODS

To estimate the social value of the different health care interventions, a person trade-off (PTO) method was used. PTOs present participants with groups of beneficiaries that vary in terms of the number of individuals who will benefit, the individuals' characteristics, their expected benefits, or a combination, and ask which group should be prioritized. Each trade-off presented health gains from the treatment of moderate physical and mental health conditions described by the 3-level version of the EuroQol 5-Dimension (EQ-5D-3L) health states. The health gains in these groups were traded-off against non-health gains in families accessing diagnostic genomic testing, and equivalence values were calculated, using median and ratio of means methods, based on the ratio of the group sizes at the point of equivalence. Participants were recruited through Prolific and were stratified according to age, sex, and education. The impact of participant characteristics on equivalence values was assessed using Kruskal-Wallis H tests and ordinary least-squares log-linear regressions.

FINDINGS

Participants (N = 434) positioned as societal decision-makers were generally willing to trade-off adult health gains with the familial non-health benefits of genomic testing, showing a preference for valuing both types of outcomes within public health policy. The aggregation of preferences generated 2 weightings for genomic testing against each health treatment, an unadjusted value and a reweighted value to match target demographic characteristics. Converted into QALY value per test, it was found that participants valued the non-health benefits of genomic testing between 0.730 and 0.756 QALY. A minority of participants always prioritized diagnostic genomic testing over the physical (6.0%) or mental (4.6%) health treatments, with a larger minority always prioritizing the physical (15.4%) or mental (14.8%) health treatments.

IMPLICATIONS

The findings indicate that participants perceived the non-health parental benefits in children experiencing rare disease to have comparable value to health gains in adults experiencing the moderate physical or mental health conditions described using EQ-5D-3L. These findings suggest that the benefits of genomic tests would be underestimated if only health benefits are included in economic evaluations.

Aligning intuition and theory: a novel approach to identifying the determinants of behaviours necessary to support implementation of evidence into practice

BACKGROUND

Disentangling the interplay between experience-based intuition and theory-informed implementation is crucial for identifying the direct contribution theory can make for generating behaviour changes needed for successful evidence translation. In the context of 'clinicogenomics', a complex and rapidly evolving field demanding swift practice change, we aimed to (a) describe a combined clinician intuition- and theory-driven method for identifying determinants of and strategies for implementing clinicogenomics, and (b) articulate a structured approach to standardise hypothesised behavioural pathways and make potential underlying theory explicit.

METHODS

Interview data from 16 non-genetic medical specialists using genomics in practice identified three target behaviour areas across the testing process: (1) identifying patients, (2) test ordering and reporting, (3) communicating results. The Theoretical Domains Framework (TDF) was used to group barriers and facilitators to performing these actions. Barriers were grouped by distinct TDF domains, with 'overarching' TDF themes identified for overlapping barriers. Clinician intuitively-derived implementation strategies were matched with corresponding barriers, and retrospectively coded against behaviour change techniques (BCTs). Where no intuitive strategies were provided, theory-driven strategies were generated. An algorithm was developed and applied to articulate how implementation strategies address barriers to influence behaviour change.

RESULTS

Across all target behaviour areas, 32 identified barriers were coded across seven distinct TDF domains and eight overarching TDF themes. Within the 29 intuitive strategies, 21 BCTs were represented and used on 49 occasions to address 23 barriers. On 10 (20%) of these occasions, existing empirical links were found between BCTs and corresponding distinct TDF-coded barriers. Twenty additional theory-driven implementation strategies (using 19 BCTs on 31 occasions) were developed to address nine remaining barriers.

CONCLUSION

Clinicians naturally generate their own solutions when implementing clinical interventions, and in this clinicogenomics example these intuitive strategies aligned with theoretical recommendations 20% of the time. We have matched intuitive strategies with theory-driven BCTs to make potential underlying theory explicit through proposed structured hypothesised causal pathways. Transparency and efficiency are enhanced, providing a novel method to identify determinants of implementation. Operationalising this approach to support the design of implementation strategies may optimise practice change in response to rapidly evolving scientific advances requiring swift translation into healthcare.

Framing the Family: A Qualitative Exploration of Factors That Shape Family-Level Experience of Pediatric Genomic Sequencing

Families of children with rare and undiagnosed conditions face many psychosocial and logistical challenges that may affect their approach to decisions about their child's care and their family's well-being. As genomic sequencing (GS) is increasingly incorporated into pediatric diagnostic workups, assessing the family-level characteristics that shape the experience of pediatric GS is crucial to understanding how families approach decision-making about the test and how they incorporate the results into their family life. We conducted semi-structured interviews with parents and other primary caregivers of pediatric patients who were evaluated for a suspected genetic condition and who were recommended to have GS (n = 20) or who had recently completed GS (n = 21). We analyzed qualitative data using multiple rounds of thematic analysis. We organized our thematic findings into three domains of factors that influence the family-level experience of GS: (1) family structure and dynamics; (2) parental identity, relationships, and philosophies; and (3) social and cultural differences. Participants conceptualized their child's family in various ways, ranging from nuclear biological family to support networks made up of friends and communities. Our findings can inform the design and interpretation of preference research to advance family-level value assessment of GS as well as genetic counseling for families.

Key drivers of family-level utility of pediatric genomic sequencing: a qualitative analysis to support preference research

Given that pediatric genomic sequencing (GS) may have implications for the health and well-being of both the child and family, a clearer understanding of the key drivers of the utility of GS from the family perspective is needed. The purpose of this study is to explore what is important to caregivers of pediatric patients regarding clinical GS, with a focus on family-level considerations. We conducted semi-structured interviews with caregivers (n = 41) of pediatric patients who had been recommended for or completed GS that explored the scope of factors caregivers considered when deciding whether to pursue GS for their child. We analyzed the qualitative data in multiple rounds of coding using thematic analysis. Caregivers raised important family-level considerations, in addition to those specifically for their child, which included wanting the best chance at good quality of life for the family, the ability to learn about family health, the impact on the caregiver's well-being, privacy concerns among family members, and the cost of testing to the family. We developed a framework of key drivers of utility consisting of four domains that influenced caregivers' decision making: underlying values, perceived benefits, perceived risks, and other pragmatic considerations regarding GS. These findings can inform measurement approaches that better capture the utility of pediatric GS for families and improve assessments of the value of clinical GS.

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.

Patient and Clinician Preferences for Genetic and Genomic Testing in Non-Small Cell Lung Cancer: A Discrete Choice Experiment

Precision (personalised) medicine for non-small cell lung cancer (NSCLC) adopts a molecularly guided approach. Standard-of-care testing in Australia is via sequential single-gene testing which is inefficient and leads to tissue exhaustion. The purpose of this study was to understand preferences around genetic and genomic testing in locally advanced or metastatic NSCLC. A discrete choice experiment (DCE) was conducted in patients with NSCLC (n = 45) and physicians (n = 44). Attributes for the DCE were developed based on qualitative interviews, literature reviews and expert opinion. DCE data were modelled using a mixed multinomial logit model (MMNL). The results showed that the most important attribute for patients and clinicians was the likelihood of an actionable test, followed by the cost. Patients significantly preferred tests with a possibility for reporting on germline findings over those without (β = 0.4626) and those that required no further procedures over tests that required re-biopsy (β = 0.5523). Physician preferences were similar (β = 0.2758 and β = 0.857, respectively). Overall, there was a strong preference for genomic tests that have attribute profiles reflective of comprehensive genomic profiling (CGP) and whole exome sequencing (WES)/whole genome sequencing (WGS), irrespective of high costs. Participants preferred tests that provided actionable outcomes, were affordable, timely, and negated the need for additional biopsy.

Toward the diagnosis of rare childhood genetic diseases: what do parents value most?

Genomic testing is becoming routine for diagnosing rare childhood genetic disease. Evidence underlying sustainable implementation is limited, focusing on short-term endpoints such as diagnostic yield, unable to fully characterize patient and family valued outcomes. Although genomic testing is becoming widely available, evidentiary and outcomes uncertainty persist as key challenges for implementation. We examine whether the current evidence base reflects public tolerance for uncertainty for genomics to diagnose rare childhood genetic disease. We conducted focus groups with general population parents in Vancouver, Canada, and Oxford, United Kingdom, to discuss expectations and concerns related to genomic testing to diagnose rare childhood genetic disease. Applying a purposive sampling technique, recruitment continued until thematic saturation was reached. Transcripts were analysed using thematic analysis. Thirty-three parents participated across four focus groups. Participants valued causal diagnoses alongside management strategies to improve patient health and wellbeing. Further, participants valued expanding the evidence base to reduce evidentiary uncertainty while ensuring security of information. Willingness to pay out of pocket for testing reflected perceived familial health benefit. Diagnostic yield fails to fully capture valued outcomes, and efforts to resolve uncertainty better reflect public priorities. Evaluations of genomic testing that fully integrate valued endpoints are necessary to ensure consistency with best practices and public willingness to accept the uncertain familial benefit.

Organizational perspectives on implementing complex health interventions: clinical genomics in Australia

PURPOSE

Clinical genomics is a complex, innovative medical speciality requiring clinical and organizational engagement to fulfil the clinical reward promised to date. Focus thus far has been on gene discovery and clinicians' perspectives. The purpose of this study was to use implementation science theory to identify organizational barriers and enablers to implementation of clinical genomics along an organizations' implementation journey from Preadoption through to Adoption and Implementation.

DESIGN/METHODOLOGY/APPROACH

We used a deductive qualitative approach study design drawing on implementation science theory - (1) Translation Science to Population Impact Framework, to inform semi structured interviews with organizational decision-makers collaborating with Australian and Melbourne Genomics, alongside and (2) Theoretical Domains Framework (TDF), to guide data analysis.

FINDINGS

We identified evolving organizational barriers across the implementation journey from Preadoption to Implementation. Initially the organizational focus is on understanding the value of clinical genomics (TDF code: belief about consequences) and setting the scene (TDF code: goals) before organizational (TDF codes: knowledge and belief about consequences) and clinician (TDF codes: belief about capability and intentions) willingness to adopt is apparent. Once at the stage of Implementation, leadership and clarity in organizational priorities (TDF codes: intentions, professional identity and emotion) that include clinical genomics are essential prerequisites to implementing clinical genomics in practice. Intuitive enablers were identified (e.g. 'providing multiple opportunities for people to come on board) and mapped hypothetically to barriers.

ORIGINALITY/VALUE

Attention to date has centred on the barriers facing clinicians when introducing clinical genomics into practice. This paper uses a combination of implementation science theories to begin to unravel the organizational perspectives of implementing this complex health intervention.

Genomic sequencing for the diagnosis of childhood mitochondrial disorders: a health economic evaluation

The diagnostic and clinical benefits of genomic sequencing are being increasingly demonstrated across multiple rare genetic conditions. Despite the expanding clinical literature, there is a significant paucity of health economics evidence to inform the prioritization and implementation of genomic sequencing. This study aims to evaluate whether genomic sequencing for pediatric-onset mitochondrial disorders (MDs) is cost-effective and cost-beneficial relative to conventional care from an Australian healthcare system perspective. Two independent and complementary health economic modeling approaches were used. Approach 1 used a decision tree to model the costs and outcomes associated with genomic sequencing and conventional care. Approach 2 used a discrete-event simulation to incorporate heterogeneity in the condition and clinical practice. Deterministic and probabilistic sensitivity analyses were performed. Genomic sequencing was less costly and more effective compared with conventional care, saving AU$1997 (Approach 1) to AU$8823 (Approach 2) per child tested, while leading to an additional 11 (Approach 1) to 14 (Approach 2) definitive diagnoses per 100 children tested. The mean monetary value of the incremental benefits of genomic sequencing was estimated at AU$5890 (95% CI: AU$5730-$6046). Implementation of genomic sequencing for MDs in Australia could translate to an annual cost-saving of up to AU$0.7 million. Genomic sequencing is cost-saving relative to traditional investigative approaches, while enabling more diagnoses to be made in a timely manner, offering substantial personal benefits to children and their families. Our findings support the prioritization of genomic sequencing for children with MDs.

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

Healthcare systems are increasingly considering widespread implementation of rapid genomic testing of critically ill children, but evidence on the value of the benefits generated is lacking. This information is key for an optimal implementation into healthcare systems. A discrete choice experiment survey was designed to elicit preferences and values for rapid genomic testing in critically ill children. The survey was administered to members of the Australian public and families with lived experience of rapid genomic testing. A Bayesian D-efficient explicit partial profiles design was used, and data were analysed using a panel error component mixed logit model. Preference heterogeneity was explored using a latent class model and fractional logistic regressions. The public (n = 522) and families with lived experiences (n = 25) demonstrated strong preferences for higher diagnostic yield and clinical utility, faster result turnaround times, and lower cost. Society on average would be willing to pay an additional AU$9510 (US$6657) for rapid (2 weeks results turnaround time) and AU$11,000 (US$7700) for ultra-rapid genomic testing (2 days turnaround time) relative to standard diagnostic care. Corresponding estimates among those with lived experiences were AU$10,225 (US$7158) and AU$11,500 (US$8050), respectively. Our work provides further evidence that rapid genomic testing for critically ill children with rare conditions generates substantial utility. The findings can be used to inform cost-benefit analyses as part of broader healthcare system implementation.

A dynamic systems view of clinical genomics: a rich picture of the landscape in Australia using a complexity science lens

BACKGROUND

Clinical genomics represents a paradigm shifting change to health service delivery and practice across many conditions and life-stages. Introducing this complex technology into an already complex health system is a significant challenge that cannot be managed in a reductionist way. To build robust and sustainable, high quality delivery systems we need to step back and view the interconnected landscape of policymakers, funders, managers, multidisciplinary teams of clinicians, patients and their families, and health care, research, education, and philanthropic institutions as a dynamic whole. This study holistically mapped the landscape of clinical genomics within Australia by developing a complex graphic: a rich picture. Using complex systems theory, we then identified key features, challenges and leverage points of implementing clinical genomics.

METHODS

We used a multi-stage, exploratory, qualitative approach. We extracted data from grey literature, empirical literature, and data collected by the Australian Genomic Health Alliance. Nine key informants working in clinical genomics critiqued early drafts of the picture, and validated the final version.

RESULTS

The final graphic depicts 24 stakeholder groups relevant to implementation of genomics into Australia. Clinical genomics lies at the intersection of four nested systems, with interplay between government, professional bodies and patient advocacy groups. Barriers and uncertainties are also shown. Analysis using complexity theory showed far-reaching interdependencies around funding, and identified unintended consequences.

CONCLUSION

The rich picture of the clinical genomic landscape in Australia is the first to show key stakeholders, agencies and processes and their interdependencies. Participants who critiqued our results were instantly intrigued and engaged by the graphics, searching for their place in the whole and often commenting on insights they gained from seeing the influences and impacts of other stakeholder groups on their own work. Funding patterns showed unintended consequences of increased burdens for clinicians and inequity of access for patients. Showing the system as a dynamic whole is the only way to understand key drivers and barriers to largescale interventions.

TRIAL REGISTRATION

Not applicable.

The personal utility and uptake of genomic sequencing in pediatric and adult conditions: eliciting societal preferences with three discrete choice experiments

Purpose

To estimate the personal utility and uptake of genomic sequencing (GS) across pediatric and adult-onset genetic conditions.

Methods

Three discrete choice experiment (DCE) surveys were designed and administered to separate representative samples of the Australian public. Bayesian D-efficient explicit partial profile designs were used. Choice data were analyzed using a panel error component random parameter logit model.

Results

Overall, 1913 participants completed the pediatric (n = 533), symptomatic adult (n = 700) and at-risk adult (n = 680) surveys. The willingness-to-pay for GS information in pediatric conditions was estimated at $5470–$15,250 (US$3830–$10,675) depending on the benefits of genomic information. Uptake ranged between 60% and 81%. For symptomatic adults, the value of GS was estimated at $1573–$8102 (US$1100–$5671) and uptake at 34–82%. For at-risk adults, GS was valued at $2036–$5004 (US$1425–$3503) and uptake was predicted at 35–61%.

Conclusion

There is substantial personal utility in GS, particularly for pediatric conditions. Personal utility increased as the perceived benefits of genomic information increased. The clinical and regulatory context, and individuals’ sociodemographic and attitudinal characteristics influenced the value and uptake of GS. Society values highly the diagnostic, clinical, and nonclinical benefits of GS. The personal utility of GS should be considered in health-care decision-making.