Department of Computer Science, Rutgers University, USA.
Yearb Med Inform. 2022 Aug;31(1):317-322. doi: 10.1055/s-0042-1742491. Epub 2022 Jun 2.
Inclusive digital health prioritizes public engagement through digital literacies and internet/web connectivity for advancing and scaling healthcare equitably by informatics technologies. This is badly needed, largely desirable and uncontroversial. However, historically, medical and healthcare practices and their informatics processes assume that individual clinical encounters between practitioners and patients are the indispensable foundation of clinical practice. This assumption has been dramatically challenged by expansion of digital technologies, their interconnectable mobility, virtuality, surveillance informatics, and the vastness of data repositories for individuals and populations that enable and support them. This article is a brief historical commentary emphasizing critical ethical issues about decisions in clinical interactions or encounters raised in the early days of the field. These questions, raised eloquently by François Grémy in 1985, have become urgently relevant to the equity/fairness, inclusivity and unbiasedness desired of today's pervasive digital health systems.
The main goal of this article is to highlight how the personal freedoms of choice, values, and responsibilities arising in relationships between physicians and healthcare practitioners and their patients in the clinical encounter can be distorted by digital health technologies which focus more on efficiency, productivity, and scalability of healthcare processes. Understanding the promise and limitations of early and current decision-support systems and the analytics of community or population data can help place into historical context the often exaggerated claims made today about Artificial Intelligence and Machine Learning "solving" clinical problems with algorithms and data, downplaying the role of the clinical judgments and responsibilities inherent in personal clinical encounters.
A review of selected early articles in medical informatics is related to current literature on the ethical issues and technological inadequacies involved in the design and implementation of clinical systems for decision-making. Early insights and cautions about the development of decision support technologies raised questions about the ethical responsibilities in clinical encounters where freedom of personal choice can be so easily limited through the constraints from information processing and reliance on prior expertise frequently driven more by administrative rather than clinical objectives. These anticipated many of the deeper ethical problems that have arisen since then in clinical informatics.
Early papers on ethics in clinical decision-making provide prescient commentary on the dangers of not taking into account the complexities of individual human decision making in clinical encounters. These include the excessive reliance on data and experts, and oversimplified models of human reasoning, all of which persist and have become amplified today as urgent questions about how inclusivity, equity, and bias are handled in practical systems where ethical responsibilities of individuals patients and practitioners intertwine with those of groups within professional or other communities, and are central to how clinical encounters evolve in our digital health future.
包容性数字健康通过数字素养和互联网/网络连接优先考虑公众参与，通过信息学技术推进和扩大公平的医疗保健。这是非常需要的，也是非常可取的，没有争议的。然而，从历史上看，医疗和医疗实践及其信息学过程假设，从业者和患者之间的个体临床接触是临床实践不可或缺的基础。这种假设受到数字技术的扩展、它们的互联移动性、虚拟性、监测信息学以及个人和人群的庞大数据存储库的极大挑战，这些存储库为它们提供了支持。本文是一篇简要的历史评论，强调了该领域早期提出的临床交互或接触中决策的关键伦理问题。这些问题由弗朗索瓦·格雷米（François Grémy）于 1985 年雄辩地提出，如今已成为当今普遍存在的数字健康系统所期望的公平/公平、包容性和无偏见的紧迫问题。
本文的主要目标是强调在临床相遇中，医生和医疗保健从业者及其患者之间的关系中出现的个人自由选择、价值观和责任如何因专注于医疗保健流程的效率、生产力和可扩展性的数字健康技术而扭曲。理解早期和当前决策支持系统的承诺和局限性以及社区或人群数据的分析，可以帮助将当前关于人工智能和机器学习通过算法和数据“解决”临床问题的夸张主张置于历史背景下，同时淡化个人临床接触中固有的临床判断和责任。
对医学信息学中选定的早期文章进行回顾，并与当前关于临床决策系统设计和实施中涉及的伦理问题和技术不足的文献相关联。早期关于决策支持技术发展的见解和警告提出了关于临床系统中伦理责任的问题，在这些系统中，个人选择的自由可以通过信息处理的限制和对预先存在的专业知识的依赖而轻易受到限制，而预先存在的专业知识往往更多地受到行政而不是临床目标的驱动。这些问题预先考虑了此后在临床信息学中出现的更深层次的伦理问题。
关于临床决策中的伦理问题的早期论文对不考虑临床接触中个体人类决策复杂性的危险提供了有先见之明的评论。这些危险包括过度依赖数据和专家，以及简化的人类推理模型，所有这些都一直存在，并且今天变得更加突出，因为人们迫切关注包容性、公平性和偏见在实际系统中是如何处理的，在这些系统中，个人患者和从业者的伦理责任与专业或其他社区内的群体的伦理责任交织在一起，并且是临床接触在我们的数字健康未来中演变的核心。
