Bringing Creativity, Agility, and Efficiency with Generative AI in Industries 24th Edition | Page 99

Driving Healthcare Transformation Through Generative AI
3.1 GENERATED PATIENT SUMMARY
GenAI is making inroads into healthcare by automating tasks and optimizing processes such as the generation of patient summaries . These summaries can be crucial for physicians and other healthcare professionals to quickly understand a patient ' s medical history , current conditions , and treatment plans before visits or procedures . Prior attempts with limited success , for similar use case without the use of GenAI is described here 22 . Let us look at how the use of GenAI enhances this scenario .
3.1.1 PROCESS OPTIMIZATION
The process optimization involves three steps :
• Data Aggregation : Medical LLMs can aggregate data from multiple sources such as EHRs ( Electronic Health Records ), lab results , and imaging studies .
• Natural Language Processing : Advanced natural language processing techniques are employed to interpret clinical notes , and other free-text fields , converting them into structured data or summarizing the essential points . The fine tuning of the Foundational LLM , with clinical data , helps to achieve this .
• Summarization : The model generates concise yet comprehensive patient summaries that encapsulate all the necessary clinical information . The process creates a draft for the medical professional such as physician assistance to review it and approve it for use by the physician before a patient visit . The human in the loop ensures patient safety and compliance .
3.1.2 BENEFITS
The use of GenAI in creating patient summaries offers several distinct advantages . First , automation significantly enhances efficiency , freeing up valuable time for healthcare professionals to devote more attention to direct patient care . Second , the generated summaries bring a level of consistency in both format and detail , which makes it easier for healthcare providers to quickly understand the patient ' s medical situation . Third , these models can be customized to cater to the specific informational needs of various medical specialties , thereby increasing the summaries ' relevance and utility . Lastly , these GenAI systems can be configured to provide real-time updates , ensuring that healthcare professionals have access to the most current patient information . Collectively , these benefits not only improve the quality of healthcare delivery but also contribute to more informed and timely decision-making .
While the advantages of using GenAI for patient summaries are clear , the technology faces several challenges that need to be addressed . First and foremost is the issue of data quality : the
22 https :// www . ncbi . nlm . nih . gov / pmc / articles / PMC7225507 / 94
March 2024