ArticleJournal of clinical and translational research2018
Legal challenges for the implementation of advanced clinical digital decision support systems in Europe.
Article in Journal of clinical and translational research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review.Paediatric drugs · 2024Pooled it
- E-Health & Innovation to Overcome Barriers in Neuromuscular Diseases. Report from the 3rd eNMD Congress: Pisa, Italy, 29-30 October 2021: Remote Monitoring: New Solutions for New Avenues in Neuromuscular Disorders.Journal of neuromuscular diseases · 2026Article
- Article
- The role of health-related quality of life in improving cancer outcomes.Journal of clinical and translational research · 2023Article
- Considerations for artificial intelligence clinical impact in oncologic imaging: an AI4HI position paper.Insights into imaging · 2022Article
- Artificial intelligence in clinical and translational science: Successes, challenges and opportunities.Clinical and translational science · 2022Review
- CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools.Frontiers in oncology · 2022Article
- Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies.The Journal of international medical research · 2021Article
- Diagnosing Diabetic Retinopathy With Artificial Intelligence: What Information Should Be Included to Ensure Ethical Informed Consent?Frontiers in medicine · 2021Article
- Staff perspectives on the usability of electronic patient records for planning and delivering dementia care in nursing homes: a multiple case study.BMC medical informatics and decision making · 2020Article
- Should we have a right to refuse diagnostics and treatment planning by artificial intelligence?Medicine, health care, and philosophy · 2020Article
- Artificial intelligence in modern clinical practice (Review).Medicine internationalReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systems based on artificial intelligence and machine learning that facilitate decision making in health care are promising new tools in the era of 'personalized' or 'precision' medicine. As the volume of patient data and scientific evidence grows, these computerised decision support systems (DSS) have great potential to help healthcare professionals improve diagnosis and care for individual patients. However, the implementation of these tools in clinical care raises some foreseeable legal challenges for healthcare providers and DSS-suppliers in Europe: How does the use of complex and novel DSS relate to professional standards to provide a reasonable standard of care? What should be done in terms of testing before DSS can be used in regular practice? What are the potential liabilities of health care providers and DSS companies if a DSS fails to function well? How do legal requirements for the protection of patient data and general privacy rights apply to likely DSS scenarios? In this article, we provide an overview of the current law and its general implications for the use of DSS, from a European perspective. We conclude that healthcare providers and DSS-suppliers will have the best chance of meeting legal challenges if: they are first tested in translational research with the patients' explicit, informed consent; DSS-suppliers and healthcare providers are able to clarify and agree on their individual legal responsibilities, and; patients are properly informed about privacy risks and able to decide themselves whether their data can be used for other purposes, or are stored and processed outside the EU. DSS developers and healthcare providers will need to work together closely to ensure compliance with national and European regulations and standards required for reasonable and safe patient care. RELEVANCE FOR PATIENTS: Advanced digital decision support systems have the potential to improve patient diagnosis and care. In this article we discuss key legal issues to support translational research using DSS and ensure that they meet the high standards for protection of patient safety and privacy in Europe.
Indexed as
Identifiers
30873491PMC6412598What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.