The winning formula: 7 benefits of AI-powered prospective risk
Learn how AI helps health plans boost HCC accuracy, streamline workflows, and maximize revenue through smarter prospective risk adjustment.
1. Precision you can act on and defend
AI enables health plans to gain a more complete view of patient risk by analyzing structured and unstructured clinical data together. With up to 50% less noise than traditional NLP1, higher confident risk insights can be surfaced at the point of care.
The result is fewer unnecessary provider interactions, stronger RAF accuracy, and audit-ready outcomes with full traceability as programs scale.
2. New levels of productivity
AI-driven automation enables health plans to accelerate data integration, eliminate manual chart reviews, and reduce administrative burden.
In what previously took a year, one large regional health plan was able to code 1.2 million charts in 4 months using AI-powered technology, resulting in 3x its coding speed2.
3. Smarter, simpler workflows
Health plan coding teams achieve a 30% increase in efficiency using AI-powered technology that scans the full scope of data for clinical evidence of diagnoses. 3
Coders can spend less time on paperwork and data entry and focus their efforts on validating whether the evidence surfaced by AI supports the diagnosis suggestion.
4. Stronger provider relationships
3 in 4 physicians think AI will improve their diagnostic ability, and seamless AI-powered integrations are making that a reality.4
Sophisticated integrations that can connect AI-powered technology with both health plan systems and provider EHRs facilitate new levels of collaboration with providers. With HCC insights pushed directly into provider workflows – and minimal clicks required to access those insights – AI-powered technology transforms the patient encounter for more informed, efficient decision-making.
5. Cost efficiency to do more with less
AI empowers risk adjustment teams to do more with less, coding medical records in far less time and allowing more time to focus on closing care gaps year-round.
With AI-powered technology, health plans can lower overall administrative costs by 25%, allowing them to produce a greater value and achieve higher Star Ratings.5
6. Healthier patients, stronger outcomes
AI-driven prospective risk enables proactive care and enhances care coordination by surfacing previously undetected HCCs when they matter most – at the point of care.
Early intervention and timely disease management prevents unnecessary hospitalizations by identifying high-risk patients earlier in their care journey.
7. Optimal revenue capture
By surfacing risk-adjustable HCCs, using AI for prospective risk helps ensure cost of care projections align with patient complexity.
For one large health system, AI-driven improvements in HCC coding and risk adjustment led to $18.5 million in enhanced revenue capture – resulting in a 6x return on investment.7
Learn more about AI and prospective risk
Interested in how AI can transform prospective risk at your health plan? Schedule a demo of Reveleer’s Prospective Risk Adjustment Solution to get started.
Sources:
1Results vary depending on configuration settings, team mix, and chart density. Reveleer expert guidance on program set up recommended.
2“Case study: AI-powered clinical intelligence for improved patient care.” Reveleer. Available at: https://www.reveleer.com/case-studies/aco-ai-platform-prospective-risk.
3“Case study: AI to Accelerate Clinical Coding.” Reveleer. Available at: https://www.reveleer.com/resource/bcbs-ai-clinical-coding.
4“Big majority of doctors see upsides to using health care AI”. (Jan 2024). American Medical Association. Available at:
https://www.ama-assn.org/practice-management/digital/big-majority-doctors-see-upsides-using-health-care-ai.
5“The AI opportunity: How payers can capture it now.” McKinsey & Company. (June 2024). https://www.mckinsey.com/industries/healthcare/our-insights/the-ai-opportunity-how-payers-can-capture-it-now.
6Romero-Brufau et al. Applied Clinical Informatics. (Sept 2020). “Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital”. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC7467834/
7“Case study: Enhancing revenue capture and outcomes with advanced patient targeting.” Reveleer. Available at: https://www.reveleer.com/case-studies/provider-suspecting-enhancing-revenue-capture.
For health plans looking to gain visibility into patient risk, artificial intelligence (AI) is a powerful tool. With AI-powered technology, payers can achieve new levels of productivity as they identify patient care gaps with precision. Here are seven ways AI-powered insights for prospective risk deliver transformative results for value-based health plans.
About the Author
Related Resources
Heading
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.
Heading
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.
Heading
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.
