Transforming care management with AI and interoperability

Editor’s note: This is the second in a series of articles, powered by CHIME’s Digital Health Insights and sponsored by Oracle Health.

Healthcare organizations are facing increasing challenges in care management, from scaling services to support growing patient populations to addressing administrative burdens that lead to care team burnout.

“Care managers spend too much of their time on administrative tasks—documentation, coordination, logistics—rather than directly engaging with patients,” said Kate D’Orazio, Senior Principal Product Manager at Oracle Health, in a recent CHIME DHI webinar, “Intersection of Technology and Care Management: Strategies for Success,” sponsored by Oracle.

In this webinar, she discussed how AI and interoperability are transforming care management, providing key insights for healthcare IT leaders looking to leverage technology to enhance patient care, improve efficiency, and reduce provider fatigue.

The burden of care management: Challenges and pressures

Care managers today are overwhelmed with administrative tasks, reducing the time available for direct patient interactions. Heavy caseloads and fragmented data spread across multiple healthcare systems add to the challenge. “Care managers spend too much of their time on administrative tasks—documentation, coordination, logistics—rather than directly engaging with patients,” said D’Orazio.

The implications of these inefficiencies are significant. They contribute to burnout, impact job satisfaction, and can lead to poorer patient outcomes, such as increased hospital readmissions. Addressing these issues requires a dual approach: streamlining workflows through AI and improving data interoperability to enable a more connected care experience.

AI in care management: Driving efficiency and reducing burnout

AI has the potential to help relieve many of the administrative burdens that weigh down care teams.

D’Orazio noted AI, especially generative AI, is very good at tasks such as surfacing insights, drafting documentation and outreach, and reducing manual steps. These help save time, scale patient impact, and reduce burnout, making them “sweet spots” for AI use cases.

She outlined key areas where AI is making an impact:

• Automating manual tasks such as documentation and patient onboarding.
• Summarizing unstructured data to surface key insights for clinicians.
• Prioritizing patient lists using AI-driven risk stratification.

One standout example is Oracle Health’s Check-in Prep feature, designed to cut down on the time care managers spend preparing for patient interactions. “Care managers were spending 15 to 30 minutes reviewing information before a check-in,” D’Orazio explained. “With AI-driven summarization, that time has been reduced to a few minutes.”

The feature not only accelerates workflow efficiency but also enables human oversight with built-in validation tools, such as supporting facts and care manager feedback mechanisms. This approach highlights transparent and safe methods of introducing AI into existing healthcare systems.

Interoperability: Breaking down data silos for a unified care approach

Fragmented data systems pose another major hurdle in care management. Disparate platforms create inefficiencies, increase the likelihood of errors, and make it difficult for providers to track a patient’s full care journey. “An AI system is only as helpful as the data it receives,” D’Orazio noted. “If information is siloed, AI’s ability to generate meaningful insights is limited.”

To address interoperability challenges, healthcare organizations should consider:

• Leveraging AI for intelligent data extraction from multiple sources.
• Implementing multi-source, agnostic data platforms to reduce data silos and have opportunities for AI to rationalize over a holistic set of data about a patient or population.
• Prioritizing vendor solutions that support seamless data exchange across different healthcare systems.

By integrating AI and interoperability solutions, organizations can create a more holistic view of the patient, helping improve care coordination for patients and support of the broader population.

Strategic recommendations for healthcare IT leaders

For IT leaders looking to integrate AI and interoperability into their care management strategies, D’Orazio offered the following best practices:

• Align AI Initiatives with Success Metrics: Measure success based on improvements in patient outcomes, total patients impacted, care gap closures, and ROI. Examples include reducing emergency department visits, increasing care capacity, and lowering operational costs.
• Start with AI Pilots: Get started with onboarding AI features that support backend processes like documentation drafting and care team workflow optimization before expanding to more complex applications.
• Ensure Proper Training and Adoption: Provide comprehensive training for care teams and establish feedback loops to refine AI applications over time.
• Assess In-House vs. Vendor AI Solutions: Weigh the cost-effectiveness of developing AI solutions internally versus leveraging scalable vendor offerings.

The future of AI and interoperability in care management

Looking ahead, AI and interoperability will continue to reshape care management by shifting care managers’ focus from administrative tasks to direct patient engagement. “If AI systems are successful in care management workflows, you’d see the pie chart of a care manager’s time spent directly engaging with patients being 90% of their day versus 10% or 15%,” D’Orazio predicted.

AI and interoperability offer a powerful combination to address the challenges of modern care management. As D’Orazio put it, “The future of care management isn’t just about technology—it’s about freeing care managers to do what they do best: spend more time with more patients and less time on administrative tasks.” By reducing administrative burdens, improving data access, and aligning AI with measurable outcomes, healthcare organizations can enhance both efficiency and patient care.

For IT leaders, the next step is clear: evaluate current pain points, experiment with AI-driven efficiencies, and invest in interoperability initiatives to build a more connected and resilient healthcare system.

About Oracle

Organizations and care management teams are challenged with providing patients the personalized care they deserve while keeping up the daily demands of maintaining optimal performance. Oracle Health is helping to connect care teams, enhance patient care and engagement, and foster optimal patient experiences. Learn more today by visiting the Oracle Health website.