| | OCTOBER 20249UTLOOKHealthcare Tech capability is compelling in healthcare, where important details are often buried in narrative notes scattered throughout a patient's chart. Clinicians must manually trawl through that chart to create a complete picture of a patient's health.At the University of Rochester Medical Center (URMC), we are working to harness and apply the power of generative AI to improve access to and usability of data in the EHR. One of these projects focuses on helping primary care providers prepare for patients' visits. Providers need to quickly understand the patient's recent care journey, including any hospital visits, specialist consultations, or changes in medication since the last appointment. Traditionally, this would involve clicking around several areas in the EHR to discover and review the appropriate information, a time-consuming and often frustrating task. We are building chart summarization tools using generative AI that present a concise and customizable overview of what's changed for the patient since they were last seen, enabling the provider to catch up efficiently and focus more on the patient.Some information that is important to providers can be complicated to find. Some patients communicate frequently with their providers via the EHR's messaging tools and essential clinical information can be buried in these messages. In particular, medication changes and updates may occur in these exchanges, but those changes may not always be formally recorded in the patient's medication history. We have developed a tool to identify these message changes, compare them to the patient's medication list and surface any discrepancies with the provider so that the history can be updated without needing to track every interaction.Chart review and updates for direct patient care are not the only time-consuming tasks; they are manual work in which clinicians are engaged. At URMC, we are also tackling the issue of extracting data from the EHR for submission to clinical and research registries. In many cases, this process involves extensive manual review of patient charts and data entry into registry forms, which can take an hour or more for each case entered. To alleviate this burden, URMC is developing generative AI tools to augment and sometimes automate the process, allowing nurses to focus more on patient care and quality improvement rather than rote administrative tasks.The ability of generative AI to unlock and make sense of unstructured data is not just a technological advancement; it represents a paradigm shift in how we approach healthcare. We now have the tools to turn the wealth of data we've collected for centuries into actionable insights that can improve patient outcomes, enhance operational efficiency and ultimately transform healthcare delivery. In the face of a crisis of clinician burnout, generative AI can significantly reduce the burden of documentation and administrative tasks, providing much-needed relief to healthcare providers.The journey of data in healthcare reflects our ongoing quest to capture and utilize information better. With generative AI, we are finally able to harness the full potential of this data, unlocking critical insights that were previously hidden and bridging the gaps that have long plagued our healthcare system. As we continue to develop and refine these AI tools, the future of healthcare looks brighter, more connected, and more effective than ever before. HTGenerative AI is not just a technological advancement; it represents a paradigm shift in healthcare, turning centuries of collected data into actionable insights and significantly reducing the burden of documentation for clinicians
< Page 8 | Page 10 >