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.
Highlights
New technologies in genomics are changing clinical practice, increasing the volume of genetic testing and, healthcare spending
We report the first survey describing the hands-on times requested for different molecular diagnostics procedures, including next-generation sequencing (NGS)
Molecular genetic diagnostic testing has become increasingly sophisticated during the last few years, mainly due to the breakthrough of genome and exome sequencing technologies
Summary
New technologies in genomics are changing clinical practice, increasing the volume of genetic testing and, healthcare spending. The evolution of knowledge in genomics and in medical genetics has elicited the need for accurate estimation of the cost impact of genetic testing on healthcare system in relation to clinical utility. With the rapid diffusion of next-generation DNA sequencing technologies into diagnostics, and the dramatic drop down of the cost of sequencing, genomics has started to pervade health care in the area of traditional genetic diseases as well as across the entire medical field, from preconception to aging. Estimates of laboratory workload have been reported for some laboratory specialties, including microbiology [1], pathology and laboratory medicine [2] Several documents on both clinical and laboratory workloads are present on the web (https://www.cap-acp.org/ wkload.php)
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