To estimate the personal utility and uptake of genomic sequencing (GS) across pediatric and adult-onset genetic conditions.
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.
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%.
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.
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.
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.
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.
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.
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.
To estimate the value of genomic sequencing for complex pediatric neurological disorders of suspected genetic origin.
A discrete choice experiment (DCE) was undertaken to elicit societal preferences ...and values. A Bayesian D-efficient and explicit partial profile design was used. The design included 72 choice tasks, split across six blocks, with eight attributes (three overlapping per choice task) and three alternatives. Choice data were analyzed using a panel error component mixed logit model and a latent class model. Preference heterogeneity according to personal socioeconomic, demographic, and attitudinal characteristics was explored using linear and fractional logistic regressions.
In total, 820 members of the Australian public were recruited. Statistically significant preferences were identified across all eight DCE attributes. We estimated that society on average would be willing to pay AU$5650 more (95% confidence interval CI: AU$5500 to $5800) (US$3955 95% CI: US$3850 to $4060) for genomic sequencing relative to standard care. Preference heterogeneity was identified for some personal characteristics.
On average, society highly values all diagnostic, process, clinical, and nonclinical components of personal utility. To ensure fair prioritization of genomics, decision makers need to consider the wide range of risks and benefits associated with genomic information.
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.
Beyond a narrow focus on cost and outcomes, robust evidence of what is valued in genomic medicine is scarce. We gathered views on value from key stakeholders (clinical genomic staff, operational ...genomic staff and community representatives) in relation to three testing contexts (General Healthcare, Acute Care and Neurodevelopmental Conditions). We conducted an iterative focus group in three stages over a week using a multiphase mixed methods study, i.e. quantitative ratings and qualitative discussion. For each testing context, the characteristics of genomic testing were generated and ranked by the group using a co-productive approach. Up to 17 characteristics were identified in one scenario with several characteristics featuring in all three testing contexts. The likelihood of getting an answer was consistently reported as most highly valued, followed by the potential for the test to impact on clinical management (or wellbeing/health for Neurodevelopmental Conditions). Risk of discrimination did not feature highly across the different settings (and not at all in Acute Care). While cost was an issue in the general health setting, it was one of the least-valued characteristics in the other two testing contexts. In conclusion, co-producing an understanding of what is valued in different testing contexts, and identifying the areas of differences or commonalities, is important to maximise value provision and inform future policy to ensure that clinical genomic services meet the needs of the community and service providers.
Abstract
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.
Purpose
The complexity and severity of rare genetic conditions pose substantial burden to families. While the importance of spillovers on carers’ health in resource allocation decisions is ...increasingly recognised, there is significant lack of empirical evidence in the context of rare diseases. The objective of this study was to estimate the health spillovers of paediatric rare genetic conditions on parents.
Methods
Health-related quality-of-life (HRQoL) data from children with rare genetic conditions (genetic kidney diseases, mitochondrial diseases, epileptic encephalopathies, brain malformations) and their parents were collected using the CHU9D and SF-12 measures, respectively. We used two approaches to estimate parental health spillovers. To quantify the ‘absolute health spillover’, we matched our parent cohort to the Australian general population. To quantify the ‘relative health spillover’, regression models were applied using the cohort data.
Results
Parents of affected children had significantly lower HRQoL compared to matched parents in the general public (− 0.06; 95% CIs − 0.08, − 0.04). Multivariable regression demonstrated a positive association between parental and child health. The mean magnitude of HRQoL loss in parents was estimated to be 33% of the HRQoL loss observed in children (95% CIs 21%, 46%).
Conclusion
Paediatric rare genetic conditions appear to be associated with substantial parental health spillovers. This highlights the importance of including health effects on family members and caregivers into economic evaluation of genomic technologies and personalised medicine. Overlooking spillover effects may undervalue the benefits of diagnosis and management in this context. This study also expands the knowledge of family spillover to the rare disease spectrum.
Abstract Background Avoidable mortality is an important outcome indicator of the effectiveness of health care. It is commonly used to quantify the contribution of health care to changes in life ...expectancy among people dying prematurely. This method assumes that the only determinants of avoidable mortality are those of health care, which can be separated into prevention and treatment contributions. However, there might be other determinants. If so, the apportionment into prevention or treatment gives an erroneous picture; this occurs when a new disease manifests itself, and mortality increases. We illustrate this by examining the history of HIV infection since its emergence as a new disease, and propose an alternative method for dealing with this anomaly. Methods We tried to examine what might have happened to premature mortality in England and Wales during 1980–2010 if there had been no means of preventing or treating HIV infection. We hoped to compare that scenario with what actually happened. The difference in mortality from HIV infection between the two scenarios would then have to be apportioned to prevention and treatment. However, because this scenario is unobservable, the case of South Africa, which allocated far fewer resources for prevention, was used as counterfactual. Findings With the existing methodology, prevention and treatment of HIV were estimated to have a negative contribution of 0·3% to the 2·02 years gained in life expectancy during 1980–94 and a positive contribution of 0·2% to the 1·62 years gained during 1994–2010. A negative contribution makes sense only when health care is failing. A comparison of what could have happened in life expectancy (a decline of 1·84 years) under lower levels of HIV prevention and what actually happened (the increase of 1·62 years) can be used to estimate the effect of the combination of prevention and treatment of HIV. This led to a positive and significantly larger estimate of a 73% contribution of HIV control to the decline in premature mortality. Interpretation Existing methodology of apportioning changes in life expectancy into prevention and treatment effects cannot deal with situations that result in increased mortality, particularly in the public health context where the effect can be large. Funding None.
Abstract Background Measuring outcomes in economic evaluations of social care interventions is challenging because both health and well-being benefits are evident. The ICEpop CAPability instrument ...for adults (ICECAP-A) and the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) are measures potentially suitable for the economic evaluation of treatments for substance use disorders. Evidence for their validity in this context is, however, lacking. Objectives To assess the construct validity of the ICECAP-A and the EQ-5D-5L in terms of convergent and discriminative validity and sensitivity to change on the basis of standard clinical measures (Clinical Outcomes in Routine Evaluation-Outcome Measure, Treatment Outcomes Profile, Interpersonal Support Evaluation List, Leeds Dependence Questionnaire, and Social Satisfaction Questionnaire). Methods A secondary analysis of pilot trial data for heroin users in opiate substitution treatment was conducted. Baseline convergence with clinical measures was assessed using the Pearson correlation coefficient. Discriminative validity was assessed using one-way analysis of variance and stepwise regressions. Sensitivity to changes in clinical indicators was assessed at 3 and 12 months using the standardized response mean statistic and parametric and nonparametric testing. Results Both measures had the same level of construct validity, except for clinical indicators of well-being, for which the ICECAP-A performed better. The ICECAP-A was sensitive to changes in both health and well-being indicators. The EQ-5D-5L had lower levels of sensitivity to change, and a ceiling effect (27%), particularly evident in the dimensions of self-care (89%), mobility (75%), and usual activities (72%). Conclusions The findings support the construct validity of both measures, but the ICECAP-A gives more attention to broader impacts and is more sensitive to change. The ICECAP-A shows promise in evaluating treatments for substance use disorders for which recovery is the desired outcome.
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