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Workload measurement for molecular genetics laboratory: A survey study

Author

Listed:
  • Enrico Tagliafico
  • Isabella Bernardis
  • Marina Grasso
  • Maria Rosaria D’Apice
  • Cristina Lapucci
  • Annalisa Botta
  • Daniela Francesca Giachino
  • Maria Marinelli
  • Paola Primignani
  • Silvia Russo
  • Ilaria Sani
  • Manuela Seia
  • Sergio Fini
  • Paola Rimessi
  • Elena Tenedini
  • Anna Ravani
  • Maurizio Genuardi
  • Alessandra Ferlini
  • on behalf of the Molecular Genetics Working Group of the Italian Society of Human Genetics, SIGU

Abstract

Genetic testing availability in the health care system is rapidly increasing, along with the diffusion of next-generation sequencing (NGS) into diagnostics. These issues make imperative the knowledge-drive optimization of testing in the clinical setting. Time estimations of wet laboratory procedure in Italian molecular laboratories offering genetic diagnosis were evaluated to provide data suitable to adjust efficiency and optimize health policies and costs. A survey was undertaken by the Italian Society of Human Genetics (SIGU). Forty-two laboratories participated. For most molecular techniques, the most time-consuming steps are those requiring an intensive manual intervention or in which the human bias can affect the global process time-performances. For NGS, for which the study surveyed also the interpretation time, the latter represented the step that requiring longer times. We report the first survey describing the hands-on times requested for different molecular diagnostics procedures, including NGS. The analysis of this survey suggests the need of some improvements to optimize some analytical processes, such as the implementation of laboratory information management systems to minimize manual procedures in pre-analytical steps which may affect accuracy that represents the major challenge to be faced in the future setting of molecular genetics laboratory.

Suggested Citation

  • Enrico Tagliafico & Isabella Bernardis & Marina Grasso & Maria Rosaria D’Apice & Cristina Lapucci & Annalisa Botta & Daniela Francesca Giachino & Maria Marinelli & Paola Primignani & Silvia Russo & Il, 2018. "Workload measurement for molecular genetics laboratory: A survey study," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-13, November.
  • Handle: RePEc:plo:pone00:0206855
    DOI: 10.1371/journal.pone.0206855
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