BACKGROUND: As the healthcare sector evolves, Artificial Intelligence's (AI's) potential to enhance laboratory medicine is increasingly recognized. However, the adoption rates and attitudes towards AI across European laboratories have not been comprehensively analyzed. This study aims to fill this gap by surveying European laboratory professionals to assess their current use of AI, the digital infrastructure available, and their attitudes towards future implementations. METHODS: We conducted a methodical survey during October 2023, distributed via EFLM mailing lists. The survey explored six key areas: general characteristics, digital equipment, access to health data, data management, AI advancements, and personal perspectives. We analyzed responses to quantify AI integration and identify barriers to its adoption. RESULTS: From 426 initial responses, 195 were considered after excluding incomplete and non-European entries. The findings revealed limited AI engagement, with significant gaps in necessary digital infrastructure and training. Only 25.6 % of laboratories reported ongoing AI projects. Major barriers included inadequate digital tools, restricted access to comprehensive data, and a lack of AI-related skills among personnel. Notably, a substantial interest in AI training was expressed, indicating a demand for educational initiatives. CONCLUSIONS: Despite the recognized potential of AI to revolutionize laboratory medicine by enhancing diagnostic accuracy and efficiency, European laboratories face substantial challenges. This survey highlights a critical need for strategic investments in educational programs and infrastructure improvements to support AI integration in laboratory medicine across Europe. Future efforts should focus on enhancing data accessibility, upgrading technological tools, and expanding AI training and literacy among professionals. In response, our working group plans to develop and make available online training materials to meet this growing educational demand.
- Klíčová slova
- artificial intelligence, digital medicine, new technologies,
- MeSH
- klinické laboratoře MeSH
- lidé MeSH
- průzkumy a dotazníky MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
The ultimate goal of value-based laboratory medicine is maximizing the effectiveness of laboratory tests in improving patient outcomes, optimizing resources and minimizing unnecessary costs. This approach abandons the oversimplified notion of test volume and cost, in favor of emphasizing the clinical utility and quality of diagnostic tests in the clinical decision-making. Several key elements characterize value-based laboratory medicine, which can be summarized in some basic concepts, such as organization of in vitro diagnostics (including appropriateness, integrated diagnostics, networking, remote patient monitoring, disruptive innovations), translation of laboratory data into clinical information and measurable outcomes, sustainability, reimbursement, ethics (e.g., patient empowerment and safety, data protection, analysis of big data, scientific publishing). Education and training are also crucial, along with considerations for the future of the profession, which will be largely influenced by advances in automation, information technology, artificial intelligence, and regulations concerning in vitro diagnostics. This collective opinion paper, composed of summaries from presentations given at the two-day European Federation of Laboratory Medicine (EFLM) Strategic Conference "A vision to the future: value-based laboratory medicine" (Padova, Italy; September 23-24, 2024), aims to provide a comprehensive overview of value-based laboratory medicine, projecting the profession into a more clinically effective and sustainable future.
- Klíčová slova
- home testing, laboratory medicine, technology, value,
- MeSH
- klinické laboratoře * ekonomika trendy MeSH
- klinické laboratorní techniky ekonomika trendy MeSH
- kongresy jako téma MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
