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European Nephrologists’ Attitudes toward the Application of Artificial Intelligence in Clinical Practice: A Comprehensive Survey
Open accessAbstract
Introduction: The rapid advancement of artificial intelligence and big data analytics, including descriptive, diagnostic, predictive, and prescriptive analytics, has the potential to revolutionize many areas of medicine, including nephrology and dialysis. Artificial intelligence and big data analytics can be used to analyze large amounts of patient medical records, including laboratory results and imaging studies, to improve the accuracy of diagnosis, enhance early detection, identify patterns and trends, and personalize treatment plans for patients with kidney disease. Additionally, artificial intelligence and big data analytics can be used to identify patients’ treatment who are not receiving adequate care, highlighting care inefficiencies in the dialysis provider, optimizing patient outcomes, reducing healthcare costs, and consequently creating values for all the involved stakeholders. Objectives: We present the results of a comprehensive survey aimed at exploring the attitudes of European physicians from eight countries working within a major hemodialysis network (Fresenius Medical Care NephroCare) toward the application of artificial intelligence in clinical practice. Methods: An electronic survey on the implementation of artificial intelligence in hemodialysis clinics was distributed to 1,067 physicians. Of the 1,067 individuals invited to participate in the study, 404 (37.9%) professionals agreed to participate in the survey. Results: The survey showed that a substantial proportion of respondents believe that artificial intelligence has the potential to support physicians in reducing medical malpractice or mistakes. Conclusion: While artificial intelligence’s potential benefits are recognized in reducing medical errors and improving decision-making, concerns about treatment plan consistency, personalization, privacy, and the human aspects of patient care persist. Addressing these concerns will be crucial for successfully integrating artificial intelligence solutions in nephrology practice.
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The main quality of care benefits from AI integration is seen as an overall improvement in clinical outcomes by increasing patient safety and enhancing medical standards.
“The main quality of care benefits from AI integration is seen as an overall improvement in clinical outcomes [33, 54, 55, 79, 80, 84] by increasing patient safety [32, 46, 49, 72] and enhancing medical standards [85].”
From Healthcare professionals’ perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels (2025) · cites this paper as [72]
The Results (page unavailable) report that 59.4% of surveyed nephrologists agreed AI could help physicians reduce medical mistakes, supporting a perceived patient-safety benefit. The Introduction describes the potential to optimize patient outcomes, but the paper does not establish an overall improvement in clinical outcomes or identify enhanced medical standards as the mechanism or a main benefit. (LLM, conf=0.82)
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References 14 · Cited by 6
Research works printed but not linked: 12
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Metadata
- Authors
- Savoia, M., Tripepi, G., Goethel-Paal, B., Baró Salvador, M. E., Ponce, P., Voiculescu, D., Pachmann, M., Jirka, T., Koc, S. K., Marcinkowski, W., Cioffi, M., Neri, L., Usvyat, L., Hymes, J. L., Maddux, F. W., Zoccali, C., & Stuard, S.
- Affiliations
- Fresenius Medical Care (Germany) (DE)
- Istituto di Fisiologia Clinica (IT)
- Fresenius Medical Care Portugal (Portugal) (PT)
- University of Warsaw (PL)
- Fresenius Medical Care (United States) (US)
- Biogem (IT)
- Corresponding author
- Stuard, Stefano
- ORCID
- Venue
- Blood Purification
- Publisher
- S. Karger AG
- Published
- 2023-11-24
- Volume
- 53
- Issue
- 2
- Pages
- 80-87
- ISSN
- 0253-5068 (ISSN-L)
- 1421-9735
- PMC
- PMC10836740
- OpenAlex
- W4388978362
- Cited by
- 6
- References
- 14
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2
- FWCI
- 0.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Blood Purification (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Fresenius Medical Care North America
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- artificial intelligence, nephrology, hemodialysis, physician attitudes, medical errors, medical malpractice, big data analytics, personalized treatment, patient privacy, clinical decision-making, kidney disease
- MeSH terms
- Nephrologists, Artificial Intelligence, Renal Dialysis, Humans, Nephrology, Surveys and Questionnaires
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