Every provider’s path to healthcare is unique. Some draw inspiration from loved ones with a legacy of service. Others are driven by a passion for advancing the science of medicine.

Virtually no providers would say they dedicated years of their lives to education and training so they could spend hours buried in the electronic health record (EHR). Yet EHR inefficiencies often stand between providers and their purpose.

With generative artificial intelligence (GenAI), that is poised to change. Let’s explore a few ways GenAI is already enabling providers to spend more time focused on patients.

Virtually no providers would say they dedicated years of their lives to education and training so they could spend hours buried in the electronic health record (EHR). Yet EHR inefficiencies often stand between providers and their purpose.

Enabling interactivity with the patient record

Keyword search for clinical documents has traditionally been ineffective because most systems rigidly require the user to know precise terms to query. And when you’re facing a mountain of notes, unstructured documents, progress reports and discharge summaries, how are you supposed to know what to search for in the first place?

With GenAI, streamlined search with contextual meaning is possible. Instead of reading a lengthy discharge summary, a user can simply ask the system to create a list of discharge orders.

Similarly, providers can interact with a patient’s record through a conversational AI interface, allowing them to ask questions about the patient rather than navigating multiple application windows. All clinicians may find this useful, but you can really see its value in a setting like the emergency department when minutes really matter.

Unlocking unstructured data

Leveraging unstructured data from documents like progress reports, discharge summaries and notes has been a laborious task for years. With GenAI and natural language processing (NLP), we can now extract discrete data elements and automatically add them to the patient’s structured chart. In addition to reducing the need for manual data entry and coding, this also significantly enriches the patient record with details like family history and social determinants of health (SDOH).

We’re already putting this functionality in the hands of our users. One of our clients is a national health research institution that works extensively with unstructured text. We partnered to use GenAI to extract conditions and problems into structured datasets for researchers, including rare diseases that are poorly represented in older model training datasets. Using AI, we can extract discrete data points and map them into standardized formats for analytics and research tools, reducing manual effort and accelerating potential medical breakthroughs.

Streamlining the provider experience

For healthcare leaders, generative AI represents more than technological advancement. It’s a major opportunity to enhance decision-making, improve outcomes and enable providers to do what they do best—support healthier patients and communities—without compromising their professional satisfaction.

Learn how CareInTelligence combines enterprise data platforms and GenAI to help healthcare organizations solve difficult problems and make more informed clinical and operational decisions here.