EHR Integration Provides Contextual Data Which Improves AI Decisions

The integration of Generative AI (Gen AI) into digital health applications into EHRs is changing the way healthcare providers make decisions. One of the most significant advancements in this space is the ability to pull contextual patient data to improve the accuracy and efficiency of medical decision-making processes. At Topology Health, we offer tools that empower software developers to integrate their applications with Electronic Health Records (EHRs). This integration facilitates the retrieval of comprehensive and up-to-date patient information, enhancing the capabilities of Gen AI models in digital health apps.

The Power of Contextual Data in Medical Decision-Making

Contextual patient data is crucial for making informed clinical decisions. This data includes a patient's medical history, current health status, ongoing treatments, and other relevant health metrics. By leveraging this data, Gen AI models can provide more accurate and personalized recommendations, leading to better patient outcomes.

A recent study published in NEJM AI, titled "GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelines" by Ferber et al., highlights the impact of contextual data on AI performance in the medical field. The study evaluated the use of GPT-4, a large language model, in interpreting oncology guidelines from the American Society of Clinical Oncology and the European Society for Medical Oncology. The findings reveal that GPT-4, when enhanced with retrieval-augmented generation (RAG) that pulls in additional clinical information, provided correct responses in 84% of cases. In contrast, GPT-4 without RAG provided correct responses in only 57% of cases.

Topology Health's Role in Advancing Digital Health Apps

At Topology Health, our tools are designed to help software developers integrate their digital health applications with EHRs. This integration is pivotal in providing Gen AI models with the necessary contextual data to make well-informed decisions. By pulling real-time patient data, our solutions ensure that digital health apps are not only accurate but also up-to-date with the latest patient information.

Key Benefits of Using Topology Health's Tools:

Improved Accuracy: By accessing comprehensive patient data, Gen AI models can provide more precise diagnostic and treatment recommendations.
Enhanced Efficiency: Automated data retrieval reduces the time healthcare providers spend on manual data entry and cross-referencing, allowing them to focus more on patient care.
Up-to-Date Information: Continuous integration with EHRs ensures that the latest patient information are always available, supporting treatment recommendations.
Personalized Care: Contextual data enables Gen AI models to offer personalized treatment plans tailored to individual patient needs, improving overall patient outcomes.

Conclusion

The integration of Gen AI with contextual patient data is a significant advancement for digital health apps. The findings from the study by Ferber et al. underscore the importance of contextual data in enhancing the performance of AI models in healthcare. At Topology Health, we are committed to providing the tools that make this integration easy for software developers, ultimately leading to more accurate, efficient, and personalized healthcare solutions.

By empowering digital health apps with the ability to pull and utilize contextual patient data, we are paving the way for a new era of informed decision-making in healthcare. Check out our YouTube Playlist on interoperability to learn more about how we can improve the accuracy of your next Gen AI health project.