Back to Search
Start Over
Workload measurement for molecular genetics laboratory: A survey study.
- Source :
-
PloS one [PLoS One] 2018 Nov 27; Vol. 13 (11), pp. e0206855. Date of Electronic Publication: 2018 Nov 27 (Print Publication: 2018). - Publication Year :
- 2018
-
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.<br />Competing Interests: We have the following interests. Cristina Lapucci is employed by Synlab Italy. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.
- Subjects :
- Genetic Testing economics
Genetic Testing trends
High-Throughput Nucleotide Sequencing economics
High-Throughput Nucleotide Sequencing statistics & numerical data
Italy
Laboratories economics
Laboratories trends
Management Information Systems
Time Factors
Workload economics
Genetic Testing statistics & numerical data
Laboratories statistics & numerical data
Surveys and Questionnaires statistics & numerical data
Workload statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 13
- Issue :
- 11
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 30481188
- Full Text :
- https://doi.org/10.1371/journal.pone.0206855