Clinical Chemistry Laboratory Analysis Unit, M isericordia Hospital Grosseto, South East Tuscany USL, Grosseto, Italy.
Department of Medicine-DIMED, University of Padova, Padova, Italy.
Clin Chem Lab Med. 2022 Sep 6;60(12):2017-2026. doi: 10.1515/cclm-2022-0680. Print 2022 Nov 25.
The Italian Society of Clinical Biochemistry and Clinical Molecular Biology (SIBioC) Big Data and Artificial Intelligence (BAI) Working Group promoted a survey to frame the knowledge, skills and technological predisposition in clinical laboratories.
A questionnaire, focussing on digitization, information technology (IT) infrastructures, data accessibility, and BAI projects underway was sent to 1,351 SIBioC participants. The responses were evaluated using SurveyMonkey software and Google Sheets.
The 227 respondents (17%) from all over Italy (47% of 484 labs), mainly biologists, laboratory physicians and managers, mostly from laboratories of public hospitals, revealed lack of hardware, software and corporate Wi-Fi, and dearth of PCs. Only 25% work daily on clouds, while 65%-including Laboratory Directors-cannot acquire health data from sources other than laboratories. Only 50% of those with access can review a clinical patient's health record, while the other access only to laboratory information. The integration of laboratory data with other health data is mostly incomplete, which limits BAI-type analysis. Many are unaware of integration platforms. Over 90% report pulling data from the Laboratory Information System, with varying degrees of autonomy. Very few have already undertaken BAI projects, frequently relying on IT partnerships. The majority consider BAI as crucial in helping professional judgements, indicating a growing interest.
The questionnaire received relevant feedback from SIBioC participants. It highlighted the level of expertise and interest in BAI applications. None of the obstacles stands out more than the others, emphasising the need to all-around work: IT infrastructures, data warehouses, BAI analysis software acquisition, data accessibility and training.
意大利临床生物化学和临床分子生物学学会（SIBioC）大数据和人工智能（BAI）工作组开展了一项调查，旨在了解临床实验室的知识、技能和技术倾向。
向 SIBioC 的 1351 名参与者发送了一份聚焦于数字化、信息技术（IT）基础设施、数据可及性和正在进行的 BAI 项目的问卷。使用 SurveyMonkey 软件和 Google Sheets 对回复进行评估。
来自意大利各地（484 个实验室中的 47%）的 227 名应答者（17%），主要是生物学家、实验室医师和管理人员，主要来自公立医院的实验室，他们报告缺乏硬件、软件和公司 Wi-Fi，个人电脑也不足。只有 25%的人每天在云端工作，而包括实验室主任在内的 65%的人无法从实验室以外的来源获取健康数据。只有 50%有访问权限的人可以查看临床患者的健康记录，而其他人只能访问实验室信息。实验室数据与其他健康数据的整合大多不完整，这限制了 BAI 类型的分析。许多人不知道整合平台。超过 90%的人从实验室信息系统中提取数据，具有不同程度的自主权。极少数人已经开展了 BAI 项目，经常依赖于 IT 合作伙伴。大多数人认为 BAI 在帮助专业判断方面至关重要，表明他们的兴趣日益浓厚。
问卷从 SIBioC 参与者那里获得了相关反馈。它突出了在 BAI 应用方面的专业知识和兴趣水平。没有一个障碍比其他障碍更突出，这强调了需要全面开展工作：IT 基础设施、数据仓库、BAI 分析软件的获取、数据可及性和培训。
