AI and Medical Technology

 There’s a lot going on

Here we begin a short series on the impact of AI on Medical Technology. First up – EHRs. Electronic Health Records.

Easily the most pervasive impact of technology on the medical community is how we document and share patient health information. Can you imagine 20 years ago when all they had was paper?

Electronic health records solve so many problems for us both as patients and as providers. In Southeast Asia, Singapore and Malaysia are leading the way in this field. Singapore, for example, has implemented a National Electronic Health Record (NEHR) system that allows for the sharing of patient information across public and private healthcare institutions. With the power of AI, the depth of functionality of these systems has the potential to shower us with new functionality, better interoperability and closer engagement between doctor and patient.

Pros of AI in EHRs

  There are many many pros, too many to list here. But by far and away the single largest boost that AI gives to medical technology is Enhanced Clinical Decision Support

• AI can analyse vast amounts of patient data within EHRs to provide real-time clinical decision support. This includes predictive analytics for identifying patients at risk of certain conditions, personalized treatment recommendations, and automated alerts for potential adverse drug interactions or deviations from care protocols.

Cons of AI in EHRs

The single biggest red flag in the AI / MedTech debate revolves around Privacy and Security Risk.

• The use of AI in EHRs raises some concerns about data privacy and security. AI systems require access to large amounts of patient data, which increases the risk of data breaches and unauthorized access. Ensuring the security of AI algorithms and the data they process is critical.

Conclusion

AI has the potential to significantly enhance EHR systems by improving clinical decision-making, personalizing care, and increasing efficiency. However, successful integration requires addressing challenges related to data quality, usability, security, and ethical considerations. Balancing these factors is crucial to realizing the full benefits of AI in EHRs while minimizing potential risks.