Original Research Article

Meeting the challenges of implementing rapid genomic testing in acute pediatric care




The purpose of the study was to implement and prospectively evaluate the outcomes of a rapid genomic diagnosis program at two pediatric tertiary centers.


Rapid singleton whole-exome sequencing (rWES) was performed in acutely unwell pediatric patients with suspected monogenic disorders. Laboratory and clinical barriers to implementation were addressed through continuous multidisciplinary review of process parameters. Diagnostic and clinical utility and cost-effectiveness of rWES were assessed.


Of 40 enrolled patients, 21 (52.5%) received a diagnosis, with median time to report of 16 days (range 9–109 days). A result was provided during the first hospital admission in 28 of 36 inpatients (78%). Clinical management changed in 12 of the 21 diagnosed patients (57%), including the provision of lifesaving treatment, avoidance of invasive biopsies, and palliative care guidance. The cost per diagnosis was AU$13,388 (US$10,453). Additional cost savings from avoidance of planned tests and procedures and reduced length of stay are estimated to be around AU$543,178 (US$424,101). The clear relative advantage of rWES, joint clinical and laboratory leadership, and the creation of a multidisciplinary “rapid team” were key to successful implementation.


Rapid genomic testing in acute pediatrics is not only feasible but also cost-effective, and has high diagnostic and clinical utility. It requires a whole-of-system approach for successful implementation.

  • Subscribe to Genetics in Medicine for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


  1. 1.

    , , et al. A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med 2016;18:1090–1096.

  2. 2.

    , , et al. Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit. CMAJ 2016;188:E254–260.

  3. 3.

    , , et al. Use of exome sequencing for infants in intensive care units: ascertainment of severe single-gene disorders and effect on medical management. JAMA Pediatr 2017: e173438.

  4. 4.

    , , et al. Effectiveness of exome and genome sequencing guided by acuity of illness for diagnosis of neurodevelopmental disorders. Sci Transl Med 2014;6:265ra168.

  5. 5.

    , , et al. Rapid targeted genomics in critically ill newborns. Pediatrics 2017;140:e20162854.

  6. 6.

    , , et al. Whole-genome sequencing for identification of Mendelian disorders in critically ill infants: a retrospective analysis of diagnostic and clinical findings. Lancet Resp Med 2015;3:377–387.

  7. 7.

    , , , . Emergency medical genomes: a breakthrough application of precision medicine. Genome Med 2015;7:82.

  8. 8.

    , , , . Rapid whole genome sequencing and precision neonatology. Semin Perinatol 2015;39:623–631.

  9. 9.

    , , et al. Global implementation of genomic medicine: we are not alone. Sci Transl Med 2015;7:290ps13.

  10. 10.

    , , et al. Preparing for genomic medicine: a real world demonstration of health system change. NPJ Genom Med 2017;2:31.

  11. 11.

    , , et al. Implementing genomic medicine in the clinic: the future is here. Genet Med 2013;15:258–267.

  12. 12.

    , , , . The current state of implementation science in genomic medicine: opportunities for improvement. Genet Med 2017;19:858–863.

  13. 13.

    , , et al. A 26-hour system of highly sensitive whole genome sequencing for emergency management of genetic diseases. Genome Med 2015;7:100.

  14. 14.

    , , et al. Effectiveness of whole-exome sequencing and costs of the traditional diagnostic trajectory in children with intellectual disability. Genet Med 2016;18:949–56.

  15. 15.

    , , et al. Prospective comparison of the cost-effectiveness of clinical whole-exome sequencing with that of usual care overwhelmingly supports early use and reimbursement. Genet Med 2017;19:867–874.

  16. 16.

    , , et al. Diagnostic and cost utility of whole exome sequencing in peripheral neuropathy. Ann Clin Transl Neurol 2017;4:318–325.

  17. 17.

    , , et al. A clinical utility study of exome sequencing versus conventional genetic testing in pediatric neurology. Genet Med 2017;19:1055–1063.

  18. 18.

    , , et al. Diagnostic impact and cost-effectiveness of whole-exome sequencing for ambulant children with suspected monogenic conditions. JAMA Pediatr 2017;171:855–862.

  19. 19.

    , , et al. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat 2013;34:1057–1065.

  20. 20.

    , , et al. A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data. Eur J Hum Genet 2017;25:1268–1272.

  21. 21.

    , , et al. Cpipe: a shared variant detection pipeline designed for diagnostic settings. Genome Med 2015;7:68.

  22. 22.

    , , et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015;17:405–424.

  23. 23.

    , , , , , . Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 2009;4:50.

  24. 24.

    , , et al. Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group. Genet Med; e-pub ahead of print 14 September 2017.

  25. 25.

    , , . Discussing withholding and withdrawing of life-sustaining medical treatment in paediatric inpatients: audit of current practice. J Paediatr Child Health 2008;44:399–403.

  26. 26.

    , . Absorptive-capacity—a new perspective on learning and innovation. Admin Sci Quart 1990;35:128–152.

  27. 27.

    , , . Convergence of implementation science, precision medicine, and the learning health care system: a new model for biomedical research. JAMA 2016;315:1941–1942.

  28. 28.

    , , et al. Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions. Genet Med 2015;17:578–586.

  29. 29.

    , , . Potential psychosocial risks of sequencing newborns. Pediatrics 2016;137(suppl 1):S24–29.

Download references


The study was funded by the founding organizations of the Melbourne Genomics Health Alliance and the State Government of Victoria (Department of Health and Human Services). The involvement of the Australian Genome Research Facility was supported by sponsorship from Bioplatforms Australia and the NCRIS program. We thank the patients and families for participating in this study. We are grateful to Ravi Savarirayan, David Amor, Martin Delatycki, Lilian Downie, Emma Krzesinski, Amanda Moody, David Tingay, Kevin Wheeler, Anastasia Pellicano, Leah Hickey, Ruth Armstrong, Trisha Prentice, and Julia Gunn for referring patients to the study; Amber Boys for cytogenetics support; Michael Tamayo and Audrey Chong for sample processing support; Chris Ieng for bioinformatics support; and Hamidul Huque for statistical support.

Author information


  1. Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Melbourne, Australia

    • Zornitza Stark
    • , Sebastian Lunke
    • , Gemma R Brett
    • , Natalie B Tan
    • , Rachel Stapleton
    • , Smitha Kumble
    • , Alison Yeung
    • , Dean G Phelan
    • , Belinda Chong
    • , Miriam Fanjul-Fernandez
    • , Justine E Marum
    • , Anna Jarmolowicz
    • , Jessica R Riseley
    • , Justine Elliott
    • , Tiong Y Tan
    •  & Susan M White
  2. Melbourne Genomics Health Alliance, Melbourne, Australia

    • Zornitza Stark
    • , Gemma R Brett
    • , Alison Yeung
    • , Anna Jarmolowicz
    • , Yael Prawer
    • , Melissa Martyn
    • , Tiong Y Tan
    • , Clara L Gaff
    •  & Susan M White
  3. Department of Paediatrics, University of Melbourne, Melbourne, Australia

    • Zornitza Stark
    • , Miriam Fanjul-Fernandez
    • , Melissa Martyn
    • , Tiong Y Tan
    • , Clara L Gaff
    •  & Susan M White
  4. Monash Genetics, Monash Children’s Hospital, Melbourne, Australia

    • Matthew Hunter
    • , Yael Prawer
    •  & Matthew Regan
  5. Department of Paediatrics, Monash University, Melbourne, Australia

    • Matthew Hunter
  6. Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, Melbourne, Australia

    • Stephanie Best
  7. Department of Medicine, University of Melbourne, Melbourne, Australia

    • Clara L Gaff


  1. Search for Zornitza Stark in:

  2. Search for Sebastian Lunke in:

  3. Search for Gemma R Brett in:

  4. Search for Natalie B Tan in:

  5. Search for Rachel Stapleton in:

  6. Search for Smitha Kumble in:

  7. Search for Alison Yeung in:

  8. Search for Dean G Phelan in:

  9. Search for Belinda Chong in:

  10. Search for Miriam Fanjul-Fernandez in:

  11. Search for Justine E Marum in:

  12. Search for Matthew Hunter in:

  13. Search for Anna Jarmolowicz in:

  14. Search for Yael Prawer in:

  15. Search for Jessica R Riseley in:

  16. Search for Matthew Regan in:

  17. Search for Justine Elliott in:

  18. Search for Melissa Martyn in:

  19. Search for Stephanie Best in:

  20. Search for Tiong Y Tan in:

  21. Search for Clara L Gaff in:

  22. Search for Susan M White in:

Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to Zornitza Stark.

Supplementary information

Supplementary material is linked to the online version of the paper at http://www.nature.com/gim