Digital competence in laboratory medicine

被引:5
作者
Adler, Jakob [1 ]
Lenski, Marie [2 ,3 ]
Tolios, Alexander [4 ,5 ]
Taie, Santiago Fares [6 ]
Sopic, Miron [7 ]
Rajdl, Daniel [8 ,9 ]
Rampul, Ashlin [10 ]
Sancesario, Giulia [11 ]
Biemann, Ronald [12 ]
机构
[1] Med Lab Clin Chem Microbiol Infect Dis & Genet Pr, Magdeburg, Germany
[2] CHU Lille, Unite Fonct Toxicol, Lille, France
[3] Univ Lille, ULR 4483, IMPECS IMPact Environm Chim Sante Humaine, Lille, France
[4] Med Univ Vienna, Dept Blood Grp Serol & Transfus Med, Vienna, Austria
[5] Med Univ Vienna, Inst Vasc Biol & Thrombosis Res, Vienna, Austria
[6] Fares Taie Biotecnol, Lab Bioquim Clin, Mar Del Plata, Argentina
[7] Univ Belgrade, Dept Med Biochem, Fac Pharm, Belgrade, Serbia
[8] Charles Univ Prague, Med Fac Pilsen, Dept Clin Biochem & Hematol, Plzen, Czech Republic
[9] Univ Hosp Plzen, Plzen, Czech Republic
[10] PathCare Labs, Umhlanga, South Africa
[11] Biobank IRCCS Santa Lucia Fdn, European Ctr Brain Res, Rome, Italy
[12] Univ Hosp Leipzig, Inst Lab Med, Clin Chem & Mol Diagnost, Leipzig, Germany
关键词
artificial intelligence; data science; digital competence; digitalization; skills;
D O I
10.1515/labmed-2023-0021
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Objectives: Even though most physicians and professionals in laboratory medicine have received basic training in statistics, experience shows that a general understanding of data analysis is not yet available on a broad scale. Therefore, data literacy, data-driven decision making, and computational thinking should be implemented in future educational training. To evaluate the state of digital competence among young scientists (YS) in laboratory medicine, we launched a worldwide online survey. Methods: A global online survey was conducted from 25/05/2022 to 26/06/2022 and was disseminated to YS who are listed in three large networks: YS of the DGKL, the EFLM Task Group-YS, and IFCC Task Force-YS and its corresponding members, covering a base of 53 countries. Results: A total of 119 young scientists from 40 countries participated in this survey. 80 % did not learn digital skills in their academic education but 96 % felt they needed to. Digital literacy was associated with terms such as programming, artificial intelligence and machine learning, statistics, communication, Big Data and data analytics. Conclusions: The results of our survey show that more knowledge and training in the area of digital skills is not just necessary, but also wanted by young scientists. A varied learning environment consisting of tutorial articles, videos, exercises, technical articles, collection of helpful links, online meetings and in person bootcamps is crucial to meet the challenges of an international project with different languages, health systems and time zones.
引用
收藏
页码:143 / 148
页数:6
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