Generative AI is knocking on hospital doors

Artificial intelligence has been transforming the healthcare sector for years. The emergence of generative AI is now giving this development an additional boost. It promises healthcare facilities further optimization of their processes and even more personalized patient care, for example through the automated analysis of patient records, the creation of medical documentation or virtual assistants.

Generative AI in healthcare: Five key aspects

Healthcare facilities have long recognized the enormous potential of generative AI and many of them have already experimented with initial applications. Now they want to use this technology on a large scale, but are often still considering how best to approach this project. Technology provider Dell Technologies explains five key aspects for developing a GenAI strategy.

1. Clear goals. Of course, the introduction of generative AI (GenAI) should not be an end in itself. It should solve problems that are closely related to strategic healthcare priorities such as improving patient care, streamlining processes or increasing operational efficiency. Healthcare organizations find these use cases by identifying weaknesses where traditional methods do not work and determining whether and how GenAI can close these gaps.
2. Robust data infrastructure. High data quality is a basic prerequisite for the successful use of generative AI. However, health data is often fragmented and scattered across many systems. A robust data processing infrastructure is therefore required to support GenAI applications. This includes data pipelines, secure storage systems and tools for integrating information from different sources such as patient records, imaging systems and clinical notes. Scalable solutions that can grow with the volume of data are best used.
3. Governance framework. Generative AI is subject to regulatory requirements such as the European Union's AI law and must meet ethical standards. To ensure that their GenAI applications meet these requirements, healthcare organizations can implement a governance framework. This should be developed jointly by IT, clinical managers and the legal department and provide employees with guidelines for the use of patient data, compliance with regulations and ethical decisions.
4. Culture of innovation. A culture of innovation and experimentation is required to make the most of the opportunities offered by generative AI. Overcoming the silos of IT and clinical teams is a crucial step in this direction. A simple but effective way to do this is to introduce a training program in which IT shows healthcare professionals how to use GenAI tools in their workflows. In addition, IT teams and clinical managers should be supported in developing practical solutions together.
5. Performance measurement. When implementing generative AI, it is best for healthcare organizations to start small, measure the impact and then expand the implementation based on demonstrable success. For example, if a GenAI solution reduces administrative errors in one department by a significant percentage, scaling this solution horizontally could have a positive impact across the organization. Important KPIs for measurement include efficiency gains, cost savings and patient satisfaction.

"Generative AI offers healthcare facilities the opportunity to sustainably optimize their processes and further improve patient care," explains Dr. Marten Neubauer, Field Director Healthcare at Dell Technologies in Germany. "They can best exploit this potential if they develop a strategy that creates a clear framework for anticipating and overcoming the challenges they will face when implementing this technology."

Source and further information: Dell Technologies