Cost-effectiveness of genome sequencing for diagnosing patients with undiagnosed rare genetic diseases.

PURPOSE: To estimate the cost-effectiveness of genome sequencing (GS) for diagnosing critically ill infants and noncritically ill pediatric patients (children) with suspected rare genetic diseases from a United States health sector perspective. METHODS: A decision-analytic model was developed to simulate the diagnostic trajectory of patients. Parameter estimates were derived from a targeted literature review and meta-analysis. The model simulated clinical and economic outcomes associated with 3 diagnostic pathways: (1) standard diagnostic care, (2) GS, and (3) standard diagnostic care followed by GS. RESULTS: For children, costs of GS ($7284) were similar to that of standard care ($7355) and lower than that of standard care followed by GS pathways ($12,030). In critically ill infants, when cost estimates were based on the length of stay in the neonatal intensive care unit, the lowest cost pathway was GS ($209,472). When only diagnostic test costs were included, the cost per diagnosis was $17,940 for standard, $17,019 for GS, and $20,255 for standard care followed by GS. CONCLUSION: The results of this economic model suggest that GS may be cost neutral or possibly cost saving as a first line diagnostic tool for children and critically ill infants.

PARC report: a health-systems focus on reimbursement and patient access to pharmacogenomics testing.

Pharmacogenomics test coverage and reimbursement are major obstacles to clinical uptake. Several early adopter programs have been successfully initiated through dedicated investments by federal and institutional research funding. As a result of research endeavors, evidence has grown sufficiently to support development of pharmacogenomics guidelines. However, clinical uptake is still limited. Third-party payer support plays an important role in increasing adoption, which to date has been limited to reactive single-gene testing. Access to and interest in direct-to-consumer genetic testing are driving demand for increasing healthcare providers and third-party awareness of this burgeoning field. Pharmacogenomics implementation models developed by early adopters promise to expand patient access and options, as testing continues to increase due to growing consumer interest and falling test prices.

Correction: Estimating the burden and economic impact of pediatric genetic disease.

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Estimating the burden and economic impact of pediatric genetic disease.

PURPOSE: To identify the economic impact of pediatric patients with clinical indications of genetic disease (GD) on the US health-care system. METHODS: Using the 2012 Kids' Inpatient Database, we identified pediatric inpatient discharges with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes linked to genetic disease, including well-established genetic disorders, neurological diseases, birth defects, and other physiological or functional abnormalities with a genetic basis. Cohort characteristics and health-care utilization measures were analyzed. Discharges with a GD-associated primary diagnosis were used to estimate the minimum burden; discharges with GD-associated primary or secondary codes established the maximum burden. RESULTS: Of 5.85 million weighted discharges, 2.6-14% included GD-associated ICD-9-CM codes. For these discharges, mean total costs were $16,000-77,000 higher (P < 0.0001) in neonates and $12,000-17,000 higher (P < 0.0001) in pediatric patients compared with background, corresponding to significantly higher total charges and lengths of stay. Aggregate total charges for suspected GD accounted for $14 to $57 billion (11-46%) of the "national bill" for pediatric patients in 2012. CONCLUSION: Pediatric inpatients with diagnostic codes linked to genetic disease have a significant and disproportionate impact on resources and costs in the US health-care system.