Break the EHR bottleneck with GenAI innovation

Electronic health records (EHRs) are the lifeblood of any healthcare system. They manage and streamline patient care by improving clinical workflows. But as EHRs have become more essential, they’ve also become fraught with challenges ranging from usability to interoperability.

It’s common for EHR systems to require excessive clicks, navigation steps, and data entry that takes time away from patient care. And EHRs often don’t communicate well across different healthcare systems, making it difficult to share patient records between hospitals, specialists, clinics, or even departments in the same hospital. 

But these challenges create opportunities for GenAI to make EHR systems smarter, more intuitive, and more useful. GenAI can empower providers to focus less on data entry and more on delivering exceptional care. But as powerful as GenAI can be, it requires careful management to achieve accuracy, security, and equitable outcomes.

GenAI can lighten the workload and improve decision-making

Any doctor or nurse will tell you that they would rather spend less time buried in paperwork and more time focusing on patients. The free flow of data across systems is the key to helping them do that. This’s the potential of GenAI. Here are five ways it can transform electronic health records (EHRs).

Automate administrative tasks

EHR systems often slow clinicians down with manual data entry and paperwork. GenAI can streamline these processes, allowing providers to focus on what truly matters: patient care.

• Real-time transcription captures doctor-patient conversations, potentially eliminating the need for manual note-taking and helping to ensure nothing gets lost.

• AI-driven scheduling optimizes appointments, reducing wait times, avoiding conflicts, and improving resource allocation.

• Smart coding suggestions enhance billing accuracy, reducing errors and minimizing reimbursement delays.

By streamlining manual tasks like these, GenAI frees up valuable time, reducing administrative burdens and improving the patient experience.

Make EHRs more intuitive

Many EHR systems are clunky and frustrating to use. GenAI can enhance usability by making interfaces more adaptive and intuitive.

• Conversational AI allows clinicians to interact with EHRs using natural language, much like speaking with a colleague.

• Personalized interfaces adjust to individual workflows, reducing cognitive load and making data retrieval and input seamless.

With a more user-friendly system, providers can work faster and more efficiently—without fighting with their software.

Solve interoperability issues

Patient data is often scattered across disconnected systems, creating inefficiencies and increasing the risk of critical details being overlooked. GenAI can bridge these gaps by standardizing data formats and integrating information from multiple sources.

• A unified patient record helps ensure that lab results, medication lists, and imaging reports are consolidated, reducing the need to toggle between systems. 

• Seamless data exchange between platforms improves coordination, eliminates duplicate testing, and minimizes errors in treatment plans.

GenAI helps clinicians make informed, timely decisions by improving better communication and data accessibility.

Reduce clinician burnout

The sheer volume of documentation required in healthcare can lead to burnout. While GenAI won’t eliminate it entirely, it can significantly lighten the load.

• Automated note generation captures key details of patient encounters, eliminating hours of manual documentation.

• Specialty-specific workflow enhancements reduce disruptions and allow clinicians to focus on patient care.

Providers can regain a sense of balance by spending less time on paperwork, leading to better job satisfaction and improved care quality.

Improve clinical decision-making

GenAI’s ability to analyze vast amounts of medical data can give clinicians deeper insights, supporting more informed decisions.

• Predictive analytics can flag risk factors, enabling earlier interventions and personalized treatment plans.

• Automated safety checks can detect potential drug interactions in real-time, reducing adverse events.

By augmenting clinical expertise with AI-driven insights, healthcare providers can deliver safer, more precise, and proactive care.

Healthcare systems are using GenAI to improve EHR already

GenAI is already delivering real-world benefits, too, for many providers. We’ve analyzed a few to provide real-world examples of GenAI for EHR in action.

MEDITECH

MEDITECH has partnered with Google to use GenAI for hospital discharge summaries. The system auto-populates discharge notes by synthesizing relevant information from the EHR. This application has reduced documentation time while improving patient engagement.

University of Missouri Health Care (MU Health Care)

In collaboration with Cerner Corporation, MU Health Care integrates GenAI into its EHR systems to automate routine tasks like documentation and billing. This project has not only reduced administrative workloads but also enhanced clinical decision-making through advanced analytics.

Johns Hopkins Hospital

Partnering with Microsoft Azure AI, Johns Hopkins employs GenAI for predictive analytics within its EHR system. The technology analyzes patient data to predict disease progression and readmission risks, enabling early interventions and personalized care plans.

Manage GenAI closely to Improve EHR

GenAI is an evolving technology. As such, GenAI needs close supervision and careful training to do its job well. Knowing what others have done to find success is the first step toward adopting your own EHR GenAI solution.

Train GenAI with high-quality data

The effectiveness of GenAI models in healthcare hinges on the quality of the data they are trained on. To help ensure accuracy, reliability, and fairness, these models must be trained on diverse and inclusive datasets that represent the full spectrum of patient demographics, medical conditions, and treatment outcomes.

This is crucial to minimize bias and enable AI-powered solutions to work effectively for all populations, regardless of race, ethnicity, gender, age, or socioeconomic status. For instance, training data should include a wide range of medical images, clinical notes, lab results, and genomic information from diverse patient groups.

Keep humans in the loop

While GenAI can automate many tasks in healthcare, clinical oversight remains essential to verify outputs, address errors, and protect patient safety. This is particularly important in avoiding hallucinations, where the AI generates incorrect or misleading information that could lead to misdiagnosis or inappropriate treatment.

Clinicians should be trained to critically evaluate AI-generated outputs, identify potential errors, and make informed decisions based on their professional judgment and expertise. This human-in-the-loop approach ultimately benefits patients and improves outcomes. 

Strong privacy protections

Robust privacy measures, such as advanced encryption, access controls, and de-identification techniques, should be implemented to safeguard patient information from unauthorized access, use, or disclosure. Compliance with regulations like HIPAA, which sets strict standards for the protection of health information, is necessary.

Healthcare organizations must also be transparent with patients about how their data is being used and give them control over their health information. By prioritizing privacy and security, healthcare organizations can build trust with patients.

A frontier AI data foundry platform can help you solve complex EHR challenges

A frontier AI data foundry platform empowers you to tackle procurement complexities head-on. Such a platform is a centralized system designed to manage, process, and analyze data from various sources, enabling AI-driven insights and facilitating collaboration across departments.

Discover how Centific’s frontier AI foundry platform can help you revolutionize EHR processes.