AI & Technology in Value-Based Care
What is the market saying about the role of technology and AI in value-based care?
By Stephanie Dodgen, Business Analyst, Client Services and Corporate Development, Apex Health Solutions
March 13, 2025
Apex Health Solutions focuses on five key Value-Based Care (VBC) capabilities to drive revenue, cost management, and health outcomes for its clients. AI has the potential to transform each of these areas.
Article Main Highlights
1. Disease Burden Capture: AI is revolutionizing risk adjustment by analyzing vast datasets and enhancing predictive analytics, enabling more accurate risk profiling and reimbursement.
2. Quality Improvement: AI-driven technologies improve quality by enabling early disease detection and supporting preventative care, reducing disease progression and improving patient outcomes.
3. Medical Cost & Trend Management: AI streamlines operations by automating time-intensive tasks and improving accuracy, helping to lower costs through claims error detection, automated processing, and fraud prevention.
4. Provider Alignment: AI enhances provider capabilities in imaging/radiology, clinical trials, electronic health records (EHRs), diagnosis, decision-making support, and even surgical procedures and personalized medicine.
5. Growth & Patient Experience: AI-driven patient engagement solutions enhance participation in health management. On the operational side, AI improves efficiency in utilization management and claims adjudication, while also reducing wait times through AI-powered virtual assistants.
AI’s Role in Risk Adjustment & Proactive Care
In a VBC setting, risk adjustment primarily ensures accurate health plan reimbursements based on member profiles. AI enhances this process by aggregating data from pharmacies, out-of-network specialists, health exchanges, and EHRs to create a more comprehensive view of a patient’s health. This allows providers to predict potential health risks and proactively implement preventive measures and interventions (1).
VBC success depends on closing care gaps, identifying non-compliant patients, and understanding key utilization and cost drivers. AI-powered predictive modeling enables health plans and providers to be proactive in-patient care, ultimately reducing future disease burden (2). AI also plays a growing role in hospital diagnostics and treatment, analyzing 2D and 3D imaging, ECGs, EEGs, vital signs, and demographic data to improve clinical decision-making (6). With the rising Medicare population and prevalence of cardiovascular disease, AI is increasingly being leveraged to enhance patient outcomes.
AI for Operational Efficiency & Cost Reduction
With healthcare costs continuing to rise, AI-powered solutions increase efficiency by automating labor-intensive tasks like clinical documentation, coding, data entry, appointment scheduling, claims processing, and compliance checks (4). These AI-driven improvements reduce human error, which can lead to misdiagnoses, incorrect treatment plans, and billing issues. By identifying patterns, predicting risks, and flagging inconsistencies, AI helps mitigate errors, saving time and reducing administrative costs (8). AI also optimizes resource utilization by detecting unnecessary healthcare usage, leading to overall cost reductions.
Additionally, AI improves transparency in claims processing by analyzing often-overlooked criteria that impact claim denials, enabling providers and patients to better understand payment decisions (8).
AI’s Impact on Providers & Clinical Decision-Making
AI alleviates administrative burdens by enhancing EHR management, automating information capture, analyzing data, and leveraging natural language processing. AI also aids in disease diagnosis by extracting insights from patient records (7). In clinical research, AI streamlines patient selection, monitoring, and data collection, improving trial efficiency. By analyzing real-time and historical data, AI enhances risk assessment and prognostics, identifying high-risk patients and predicting disease progression (7). Virtual health assistants powered by AI also offer telemedicine support, provide preliminary healthcare recommendations, and monitor symptoms in real time (7).
AI further supports financial and operational decision-making by enabling revenue forecasting, financial planning, and resource allocation strategies (10).
AI’s Role in Enhancing the Patient Experience
AI-driven solutions are transforming patient engagement through mobile apps that support medication adherence, chronic disease management, and preventative health programs (5). Conversational AI extends patient support beyond traditional healthcare hours, offering instant, reliable responses to inquiries about symptoms, prescriptions, and medical procedures (9). Additionally, AI streamlines insurance processes by guiding patients through claims submissions, billing breakdowns, and payment navigation (9).
The Future of AI in Value-Based Care
As AI continues to evolve, its impact on VBC will only grow, helping healthcare organizations improve quality, reduce costs, and enhance patient outcomes. By leveraging AI across these critical areas, health plans and providers can navigate the complexities of VBC with greater efficiency and effectiveness.
Sources:
1. AI Can Help Providers Get Better Outcomes in Value-Based Care Models
2. A New World of Healthcare: VBC and the Promise of AI
3. AI’s Ability to Transform Value-Based Care
4. The Future of Accountable Care: How AI is Redefining Value-Based Health Care
8. Leveraging GenAI for Utilization Management
9. Top 10 Use Cases of Conversational AI in Healthcare
10. 3 Ways AI Can Improve Revenue-Cycle Management