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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., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Objectives: There are many mobile health applications (apps) now available and some that use in some way laboratory medicine data. Among them, patient-oriented are of the lowest content quality. The aim of this study was to compare the opinions of non-laboratory medicine professionals (NLMP) with those of laboratory medicine specialists (LMS) and define the benchmarks for quality assessment of laboratory medicine apps., Methods: Twenty-five volunteers from six European countries evaluated 16 selected patient-oriented apps. Participants were 20-60 years old, 44% were females, with different educational degrees, and no professional involvement in laboratory medicine. Each participant completed a questionnaire based on the Mobile Application Rating Scale (MARS) and the System Usability Scale, as previously used for rating the app quality by LMS. The responses from the two groups were compared using the Mann-Whitney U test and Spearman correlation., Results: The median total score of NLMP app evaluation was 2.73 out of 5 (IQR 0.95) compared to 3.78 (IQR 1.05) by the LMS. All scores were statistically significantly lower in the NLMP group (p<0.05), except for the item Information quality (p=0.1631). The suggested benchmarks for a useful appear: increasing awareness of the importance and delivering an understanding of persons' own laboratory test results; understandable terminology; easy to use; appropriate graphic design, and trustworthy information., Conclusions: NLMP' evaluation confirmed the low utility of currently available laboratory medicine apps. A reliable app should contain trustworthy and understandable information. The appearance of an app should be fit for purpose and easy to use., (© 2020 Walter de Gruyter GmbH, Berlin/Boston.)

Background Many of the mobile applications (apps) used for delivering health interventions involve laboratory medicine data. This survey was conducted to search the online market for health apps that manage laboratory medicine data. The aim was to review them and perform a quality evaluation. Methods Apps search criteria were "Lab results blood work", "Lab results", and "Health apps". After the stepwise exclusion process, 52 selected apps were downloaded and analyzed. For review and content analysis of the apps, a multidimensional tool for classifying and rating the quality of mobile health apps - Mobile App Rating Scale (MARS), was used. Results Selected apps were classified into five categories according to their intended use by patients or physicians, and the type of data engaged. Spearman's correlation analysis found significant correlations between MARS individual scoring items, as with the subjective quality and number of technical aspects. Kruskal-Wallis analysis showed a significant difference in the number of technical aspects employed, MARS engagement and informational quality score items, total score, and subjective quality. The lowest values for all of these items were in the category of apps designed for patients, and the post hoc test showed that the difference was statistically significant between this and the values in all other categories. Conclusions Apps designed for patients, are of the poorest quality, considering the total quality of the content and information they provide, estimated using the MARS tool. This estimation needs to be validated for laboratory medicine apps, and eventually modified after consideration of specific quality benchmarks.