The Healthcare and Societal Costs of Familial Intellectual Disability.

Most of the studies on the cost of intellectual disability are limited to a healthcare perspective or cohorts composed of individuals where the etiology of the condition is a mixture of genetic and non-genetic factors. When used in policy development, these can impact the decisions made on the optimal allocation of resources. In our study, we have developed a static microsimulation model to estimate the healthcare, societal, and lifetime cost of individuals with familial intellectual disability, an inheritable form of the condition, to families and government. The results from our modeling show that the societal costs outweighed the health costs (approximately 89.2% and 10.8%, respectively). The lifetime cost of familial intellectual disability is approximately AUD 7 million per person and AUD 10.8 million per household. The lifetime costs to families are second to those of the Australian Commonwealth government (AUD 4.2 million and AUD 9.3 million per household, respectively). These findings suggest that familial intellectual disability is a very expensive condition, representing a significant cost to families and government. Understanding the drivers of familial intellectual disability, especially societal, can assist us in the development of policies aimed at improving health outcomes and greater access to social care for affected individuals and their families.

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.

Whole exome and genome sequencing in mendelian disorders: a diagnostic and health economic analysis.

Whole genome sequencing (WGS) improves Mendelian disorder diagnosis over whole exome sequencing (WES); however, additional diagnostic yields and costs remain undefined. We investigated differences between diagnostic and cost outcomes of WGS and WES in a cohort with suspected Mendelian disorders. WGS was performed in 38 WES-negative families derived from a 64 family Mendelian cohort that previously underwent WES. For new WGS diagnoses, contemporary WES reanalysis determined whether variants were diagnosable by original WES or unique to WGS. Diagnostic rates were estimated for WES and WGS to simulate outcomes if both had been applied to the 64 families. Diagnostic costs were calculated for various genomic testing scenarios. WGS diagnosed 34% (13/38) of WES-negative families. However, contemporary WES reanalysis on average 2 years later would have diagnosed 18% (7/38 families) resulting in a WGS-specific diagnostic yield of 19% (6/31 remaining families). In WES-negative families, the incremental cost per additional diagnosis using WGS following WES reanalysis was AU$36,710 (£19,407;US$23,727) and WGS alone was AU$41,916 (£22,159;US$27,093) compared to WES-reanalysis. When we simulated the use of WGS alone as an initial genomic test, the incremental cost for each additional diagnosis was AU$29,708 (£15,705;US$19,201) whereas contemporary WES followed by WGS was AU$36,710 (£19,407;US$23,727) compared to contemporary WES. Our findings confirm that WGS is the optimal genomic test choice for maximal diagnosis in Mendelian disorders. However, accepting a small reduction in diagnostic yield, WES with subsequent reanalysis confers the lowest costs. Whether WES or WGS is utilised will depend on clinical scenario and local resourcing and availability.

Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency.

Massively parallel sequencing has markedly improved mendelian diagnostic rates. This study assessed the effects of custom alterations to a diagnostic genomic bioinformatic pipeline in response to clinical need and derived practice recommendations relative to diagnostic rates and efficiency. The Genomic Annotation and Interpretation Application (GAIA) bioinformatics pipeline was designed to detect panel, exome, and genome sample integrity and prioritize gene variants in mendelian disorders. Reanalysis of selected negative cases was performed after improvements to the pipeline. GAIA improvements and their effect on sensitivity are described, including addition of a PubMed search for gene-disease associations not in the Online Mendelian Inheritance of Man database, inclusion of a process for calling low-quality variants (known as QPatch), and gene symbol nomenclature consistency checking. The new pipeline increased the diagnostic rate and reduced staff costs, resulting in a saving of US$844.34 per additional diagnosis. Recommendations for genomic analysis pipeline requirements are summarized. Clinically responsive bioinformatics pipeline improvements increase diagnostic sensitivity and increase cost-effectiveness.

Impacts of genomics on the health and social costs of intellectual disability.

BACKGROUND: This study provides an integrated assessment of the economic and social impacts of genomic sequencing for the detection of monogenic disorders resulting in intellectual disability (ID). METHODS: Multiple knowledge bases were cross-referenced and analysed to compile a reference list of monogenic disorders associated with ID. Multiple literature searches were used to quantify the health and social costs for the care of people with ID. Health and social expenditures and the current cost of whole-exome sequencing and whole-genome sequencing were quantified in relation to the more common causes of ID and their impact on lifespan. RESULTS: On average, individuals with ID incur annual costs in terms of health costs, disability support, lost income and other social costs of US$172 000, accumulating to many millions of dollars over a lifetime. CONCLUSION: The diagnosis of monogenic disorders through genomic testing provides the opportunity to improve the diagnosis and management, and to reduce the costs of ID through informed reproductive decisions, reductions in unproductive diagnostic tests and increasingly targeted therapies.

Whole-exome sequencing reanalysis at 12 months boosts diagnosis and is cost-effective when applied early in Mendelian disorders.

PURPOSE: Whole-exome sequencing (WES) has revolutionized Mendelian diagnostics, however, there is no consensus on the timing of data review in undiagnosed individuals and only preliminary data on the cost-effectiveness of this technology. We aimed to assess the utility of WES data reanalysis for diagnosis in Mendelian disorders and to analyze the cost-effectiveness of this technology compared with a traditional diagnostic pathway. METHODS: WES was applied to a cohort of 54 patients from 37 families with a variety of Mendelian disorders to identify the genetic etiology. Reanalysis was performed after 12 months with an improved WES diagnostic pipeline. A comparison was made between costs of a modeled WES pathway and a traditional diagnostic pathway in a cohort with intellectual disability (ID). RESULTS: Reanalysis of WES data at 12 months improved diagnostic success from 30 to 41% due to interim publication of disease genes, expanded phenotype data from referrer, and an improved bioinformatics pipeline. Cost analysis on the ID cohort showed average cost savings of US$586 (AU$782) for each additional diagnosis. CONCLUSION: Early application of WES in Mendelian disorders is cost-effective and reanalysis of an undiagnosed individual at a 12-month time point increases total diagnoses by 11%.

Integrating exome sequencing into a diagnostic pathway for epileptic encephalopathy: Evidence of clinical utility and cost effectiveness.

BACKGROUND: Epileptic encephalopathies are a devastating group of neurological conditions in which etiological diagnosis can alter management and clinical outcome. Exome sequencing and gene panel testing can improve diagnostic yield but there is no cost-effectiveness analysis of their use or consensus on how to best integrate these tests into clinical diagnostic pathways. METHODS: We conducted a retrospective cost-effectiveness study comparing trio exome sequencing with a standard diagnostic approach, for a well-phenotyped cohort of 32 patients with epileptic encephalopathy, who remained undiagnosed after "first-tier" testing. Sensitivity analysis was included with a range of commercial exome and multigene panels. RESULTS: The diagnostic yield was higher for the exome sequencing (16/32; 50%) than the standard arm (2/32; 6.2%). The trio exome sequencing pathway was cost-effective compared to the standard diagnostic pathway with a cost saving of AU$5,236 (95% confidence intervals $2,482; $9,784) per additional diagnosis; the standard pathway cost approximately 10 times more per diagnosis. Sensitivity analysis demonstrated that the majority of commercial exome sequencing and multigene panels studied were also cost-effective. The clinical utility of all diagnoses was reported. CONCLUSION: Our study supports the integration of exome sequencing and gene panel testing into the diagnostic pathway for epileptic encephalopathy, both in terms of cost effectiveness and clinical utility. We propose a diagnostic pathway that integrates initial rapid screening for treatable causes and comprehensive genomic screening. This study has important implications for health policy and public funding for epileptic encephalopathy and other neurological conditions.

Improved Diagnosis and Care for Rare Diseases through Implementation of Precision Public Health Framework.

Public health relies on technologies to produce and analyse data, as well as effectively develop and implement policies and practices. An example is the public health practice of epidemiology, which relies on computational technology to monitor the health status of populations, identify disadvantaged or at risk population groups and thereby inform health policy and priority setting. Critical to achieving health improvements for the underserved population of people living with rare diseases is early diagnosis and best care. In the rare diseases field, the vast majority of diseases are caused by destructive but previously difficult to identify protein-coding gene mutations. The reduction in cost of genetic testing and advances in the clinical use of genome sequencing, data science and imaging are converging to provide more precise understandings of the 'person-time-place' triad. That is: who is affected (people); when the disease is occurring (time); and where the disease is occurring (place). Consequently we are witnessing a paradigm shift in public health policy and practice towards 'precision public health'.Patient and stakeholder engagement has informed the need for a national public health policy framework for rare diseases. The engagement approach in different countries has produced highly comparable outcomes and objectives. Knowledge and experience sharing across the international rare diseases networks and partnerships has informed the development of the Western Australian Rare Diseases Strategic Framework 2015-2018 (RD Framework) and Australian government health briefings on the need for a National plan.The RD Framework is guiding the translation of genomic and other technologies into the Western Australian health system, leading to greater precision in diagnostic pathways and care, and is an example of how a precision public health framework can improve health outcomes for the rare diseases population.Five vignettes are used to illustrate how policy decisions provide the scaffolding for translation of new genomics knowledge, and catalyze transformative change in delivery of clinical services. The vignettes presented here are from an Australian perspective and are not intended to be comprehensive, but rather to provide insights into how a new and emerging 'precision public health' paradigm can improve the experiences of patients living with rare diseases, their caregivers and families.The conclusion is that genomic public health is informed by the individual and family needs, and the population health imperatives of an early and accurate diagnosis; which is the portal to best practice care. Knowledge sharing is critical for public health policy development and improving the lives of people living with rare diseases.