Healthcare organizations face constant pressure to improve financial performance and operational efficiency. Whether you're part of an MSO, an ACO, or running a digital health company, efficiently using your data is key to staying competitive. One innovative approach making waves today is Retrieval-Augmented Generation (RAG), an AI method blending structured and unstructured data to quickly deliver precise, traceable insights. Despite growing LLM context windows, RAG remains a robust and effective architecture.

Here are four practical areas where healthcare organizations can leverage RAG:

Revenue Cycle Management

& Practice FinOps

• Claim Denials Management: Quickly pull data from claims, payor policies, and clinical notes to build stronger appeals, reduce denials, and accelerate reimbursement.

• Prior Authorization Automation: Instantly access the latest insurer requirements to simplify prior auth processes, cutting paperwork and rejected claims.

• Contract Management: Navigate complex payor agreements and reimbursement terms efficiently, ensuring compliance and maximizing revenue. While many companies offer solutions for assisted or fully automated coding, RAG takes back-office billing efficiency a step further.

Value-Based Care

• Risk Stratification: Quickly summarize and query claims, EHR data, and social determinants of health to spot care gaps and identify high-risk patients. These approaches have shown promising results in recent research, highlighting risks that traditional methods might miss.

• Predictive Analytics: Proactively identify patients at risk of chronic conditions using RAG-driven insights, offering richer predictions compared to time-series data alone.

Regulatory Compliance & Quality Reporting

• Automated Compliance Checks: Retrieve essential documentation swiftly for compliance audits (Medicare, Medicaid, payor contracts), significantly reducing risk.

• Quality Reporting Automation: Streamline gathering evidence for quality measures like HEDIS, MACRA/MIPS, and Medicare Shared Savings, reducing administrative effort and improving reporting accuracy.

Care Coordination & Patient Engagement

• Transitions of Care: Quickly identify valid in-network referrals by leveraging clinical notes, plan details, and provider directories.

• Care Plans: Equip care coordinators with comprehensive EHR data, discharge summaries, and clinical notes to suggest talking points and reduce documentation time. Use the same data to boost patient communications, lower outreach costs, and improve care plan adherence.

Build with Us!

At Toboggan Labs, we've spent years mastering complex healthcare claims data, interoperability standards like FHIR and HL7, and optimizing clinical workflows. We've also delivered diverse AI solutions, from digital biomarkers to patient-facing chatbots. While RAG isn't a one-size-fits-all solution, it's incredibly effective at tackling common healthcare information challenges.

We recently shared insights on RAGnarök, our internal toolkit designed specifically to simplify the development, deployment, and evaluation of RAG applications, especially in cases where vendor solutions fall short. With RAGnarök, our developers and data scientists rapidly build customized RAG solutions tailored to your organization's needs, ensuring quick deployment, compliance, and measurable impact.

Ready to improve how your healthcare organization leverages data? Contact us today to discuss integrating RAG into your workflows.