Generative AI in Clinical Workflows: A Boost to EHR Systems

Healthcare is undergoing a tectonic change that is redesigning the work, thinking and practice of clinicians. Innovations in language models and machine learning have opened the door to unexplored opportunities in generative AI in clinical workflows and will disrupt an industry that is overwhelmed by administrative burdens.

Imagine this: doctors spending their maximum time on paperwork rather than treating patients, nurses drowning in paper and wasteful processes in the healthcare systems. This is not sustainable and this is the very reason why generative AI healthcare solutions are bringing the industry the lifeline it badly requires.

The changes are already underway. Platforms such as ChatGPT are increasingly available to providers and they are learning how AI-enabled clinical workflow tools can help make operations more efficient, remove tedious tasks and bring back the human connection that attracted them to the medical field in the first place. The most exciting part is that the large EHR vendors are not just spectators on the sidelines; they are the drivers.

Some industry titans are already incorporating generative AI in healthcare workflows into their platforms, transforming the nature of how medical records are captured, processed, shared and distributed. This is not an upgrade, but a total redesign of clinical work that is already achieving quantifiable outcomes in real-life care environments.

In this guide, we will look at how 4 of the largest EHR vendors are leading the way in the adoption of generative AI in clinical practice to drive efficiency, reduce burnout, and eventually boost patient outcomes in the clinical ecosystem.

Understanding Generative AI in EHR

Generative AI in clinical workflows is reshaping EHR systems by automating repetitive tasks and enabling sophisticated data analysis. EMR systems simplify patient medical records and have added a task to the plate of providers and healthcare staff.

By leveraging natural language processing and ML algorithms, generative AI in healthcare EHR can analyze vast amounts of patient data, identify patterns, and generate accurate summaries, notes, and even recommendations. This technology supports clinical decision support systems by providing real-time insights during patient encounters.

The impact goes beyond simple automation. These AI-powered systems can automate data entry, generate clinical notes and summarize complex patient information, effectively reducing the cognitive load on healthcare professionals. This clinical workflow automation with generative AI allows clinicians to spend more time on direct patient care while maintaining documentation standards.

Epic’s Implementation of Gen AI

Epic, one of the leading EHR vendors, is at the forefront of this generative AI in clinical workflows revolution. They are using AI to automate responses to patient portal messages. Gen AI can draft responses that clinicians can review and send, speeding up communication and freeing up time for patient care.

Epic is also developing tools to summarize patient information since the last visit, providing physicians with concise, actionable updates that enhance patient engagement and care continuity. 

But that’s not all. Epic’s ambitions go beyond streamlining clinician workflows. They envision generative AI for clinical documentation as a “universal translator,” capable of explaining complex medical jargon in simple terms, enhancing patient understanding of their health records.

Oracle Health’s Gen AI Solutions

Oracle Health is taking a similar approach with its Clinical Digital Assistant, demonstrating how generative AI in healthcare EHR can transform daily operations. They’re beta-testing a generative AI-based chatbot designed to automate administrative workflows and support clinical decision-making processes.

This virtual assistant can summarize patient information, generate clinical notes by listening to patient-provider conversations, and even suggest next steps based on the discussion. The integration represents a huge advancement in AI in clinical decision support, providing real-time assistance during patient encounters.

Its standout feature is the ability to provide clinicians with information about patients, including recent lab results, during consultations. The ability to provide this type of service enhances the experience of patients, creating a feeling of being heard and cared for.

Additionally, the tool leverages AI in clinical process improvement by suggesting next steps, such as prescribing medication or scheduling tests, which clinicians can review and approve, based on the information acquired in the conversation.

eClinicalWorks and Ambient Listening Technology 

eClinicalWorks, another major EHR vendor, has also joined the generative AI for healthcare workflows movement by partnering with Sunoh.ai to integrate ambient listening into their platform.

No more typing furiously during appointments or spending hours documenting the encounter afterward. With ambient listening powered by generative AI in medical record systems, providers can capture the essence of the entire conversation without touching a keyboard.

How does this AI-generated clinical notes workflow function? Well, this technology listens to patient-provider conversations and generates draft clinical documentation, which clinicians can review and edit. This approach aims to save time and reduce the cognitive load on healthcare providers while maintaining accuracy and compliance with HIPAA compliant software standards.

MEDITECH’s Collaboration with Google

MEDITECH is working with Google to streamline clinical documentation through generative AI in hospital workflows, focusing initially on hospital discharge summaries. There is no doubt that these critical documents, which are essential to care coordination and hospital management system efficiency, can be incredibly time-consuming to complete for clinicians, especially for patients with longer hospital stays.

However, with generative AI in clinical trials and established healthcare applications, MEDITECH aims to auto-populate these summaries in real-time by taking relevant patient information directly from the patient’s records, saving clinicians time and effort. This ensures accuracy and builds trust in the technology and supports generative AI for health data management.

Also, this technology can actually help lessen burnout cases among care staff while at the same time responding to the shortage of different clinical professionals in healthcare facilities by speeding up the discharge process.  The integration shows a step forward in integrating generative AI in clinical operations across hospital systems.

Wrapping Up 

Generative AI clinical workflows is the pen writing the future of healthcare today. It is not only about technological evolution but a healthcare revolution that is now already producing life-changing outcomes in the industry.

Generative AI in clinical practice is now a reality and is actually helping to reduce administrative burden, alleviating clinician burnout and enhancing communication and care coordination. Such AI-driven technologies are showing that technology is not a substitute for the human touch in healthcare, but can be used to supplement it.

The facts speak for themselves: with generative AI in clinical trials and real-world applications, efficiency, accuracy, and job satisfaction show a measurable increase. Nonetheless, effective adoption will only be achieved through a considerate implementation that emphasizes the trust of clinicians and the maintenance of the most rigorous standards of precision and reliability of AI-generated material.

Going forward, organizations that adopt generative AI for healthcare workflows today will be the ones that will define the future of healthcare, providing remarkable patient experiences and establishing sustainable, rewarding workplaces for their clinical staff.