The Benefits of Integrating a Modern Data Platform Into the EHR

What Is a Modern Data Platform and How Does It Benefit the EHR?

Integrating a modern data platform into an EHR can offer numerous benefits, Turk says. Healthcare organizations can realize improved interoperability across systems and facilities, reduced infrastructure and maintenance costs, faster innovation cycles with access to cutting-edge tools, and enhanced patient outcomes through predictive analytics and personalized care.

Moreover, with their EHRs on a modern data platform, healthcare systems can unleash the vast potential of artificial intelligence. “We unlock advanced analytics, real-time data access and AI-driven insights that can dramatically improve clinical decision-making and operational efficiency,” Turk says.

Today, many healthcare organizations bolt AI-enabled, single-purpose tools onto legacy EHR infrastructures and workflows, according to Seema Verma, executive vice president and general manager at Oracle Health and Life Sciences. But this approach leaves AI unable to access different types of real-time data, so that AI can repeat past mistakes, present inaccuracies and biases as truth, and become prone to hallucinations and costly errors, Verma notes.

“AI works best when it has access to comprehensive data,” Verma says.

Oracle embeds AI agents directly into the EHR system, she explains. Rather than training on historical data that’s frozen in time, the AI in Oracle’s modern data platform constantly learns, staying current with medical evidence, clinical best practices and coverage rules. With continuously updated and contextualized data, AI can spot emerging trends, optimize resources and update care in real time.

In addition, the Oracle platform’s knowledge graph maps relationships across the healthcare industry’s data domains. As a result, the platform’s AI knows, for instance, that “heart attack” and “myocardial infarction” are the same thing, or that a hemoglobin A1C lab result can indicate diabetes.

READ MORE: AI is the next stop on healthcare’s EHR optimization journey.

The Role of Data Governance in Cloud-EHR Integration

The success of an integration rests on the quality of the data. “AI is only as good as the data it learns from,” Verma says.

With high-quality data, healthcare organizations can leverage a modern data platform to achieve reliable analytics and reporting, reduced clinical errors, and better resource allocation.

Data governance — establishing clear policies for data stewardship, access controls and lifecycle management — is paramount.

“Data governance and quality are the backbone of any successful cloud-EHR integration. It’s not just about technology, it’s about culture and accountability,” Turk says. “Governance ensures that data is accurate, secure and used responsibly.” That’s especially critical in healthcare, where patient trust and regulatory compliance are nonnegotiable.

Overcoming Modern Data Platform Integration Challenges

Integrating a modern data platform into an EHR isn’t easy. According to Turk, the challenges include legacy systems that weren’t designed for cloud interoperability; security and compliance concerns, especially involving HIPAA and protected health information; and data migration complexity, including mapping and cleansing.

Legacy systems represent a significant stumbling block. “Legacy EHRs were built decades ago, with fragmented data buried across hundreds of tables and accessed through slow APIs, making it nearly impossible for real-time reasoning or intelligent automation,” Verma says.

These obstacles aren’t insurmountable, however. To overcome them, healthcare systems must take a phased approach to cloud-EHR integration, Turk explains:

1. Start with a workload assessment to identify the cloud-ready systems.
2. Engage stakeholders early to align goals and build trust.
3. Invest in training and support.
4. Partner with vendors who understand healthcare regulations.

Integration must involve robust change management to build trust and gain buy-in among clinicians and staff.

To help gain trust, the AI in Oracle Health’s EHR cites sources for all of its analyses and recommendations. “Clinicians need to understand how an AI-enabled system reaches its conclusions and be confident it’s drawing from the right information,” Verma says.

EXPLORE: How does EHR optimization improve the patient experience?

The Benefits of Data Automation and RPA in Healthcare

Healthcare systems that successfully integrate a modern data platform into their EHRs can gain the many advantages of data automation and robotic process automation — capabilities that can “revolutionize how we interact with EHR data,” Turk says.

Data automation and RPA tools can automate repetitive tasks such as data entry, billing and scheduling. In addition to streamlining workflows across departments, they can use natural language processing to extract insights from unstructured data. These tools can enable real-time alerts to support clinical decision-making.

For example, Turk notes, RPA can automatically pull lab results into patient charts, reducing manual errors and freeing up staff for higher-value tasks. Automation also can surface trends such as readmissions risks or medication adherence, so that healthcare systems can make proactive interventions.

Once a human approves the recommendations of Oracle’s AI agents, the platform can send in prescription refills, order labs or do billing. “AI has the potential to help transform healthcare from a reactive system to an intelligent, connected and proactive system,” Verma says.