Raise Quality, Reduce Costs, and Protect Value-Based Care Savings
Value-based care requires predictive intelligence to drive preventive, proactive care. HealthVision™ turns your beneficiary data into predictive insights, stratifying risks, surfacing the highest-yield HCC gaps, benchmarking your network against national peers, and identifying advanced illness patients, so your team can optimize outcomes and secure appropriate revenue.
Proven Results from ACO Implementations
Built to Manage Risk Across Your Entire Population
ACOs face constant pressure to improve outcomes and control costs, but missed HCCs, preventable care and quality gaps, and late identification of advanced illness patients make it difficult to act before risk compounds. Built on the nation's largest longitudinal database, HDAI's AI-powered intelligence engine helps organizations predict which patients need intervention next, rank HCC gaps by recapture probability, benchmark network performance against risk-matched peers, and flag anomalous billing directly in the EHR.
Need
Prevent rising risk patients from becoming high risk
Care management teams are stretched thin, relying on lagging claims data, generic risk scores relying on historical utilization, and physical assessment to identify patients at risk of hospitalization, readmission, or escalating utilization. For many patients in the community, the opportunity for early intervention has passed.
Solution
Risk models provide precise stratification to drive proactive, targeted outreach
Your attributed population is segmented into actionable cohorts—hospice, advanced illness, complex care, rising risk, and low risk—with forward-looking predictions and prioritized by intervention potential. Updated weekly from CMS claims data and in real-time with additional EHR integration.
Solution
Risk models provide precise stratification to drive proactive, targeted outreach
Your attributed population is segmented into actionable cohorts—hospice, advanced illness, complex care, rising risk, and low risk—with forward-looking predictions and prioritized by intervention potential. Updated weekly from CMS claims data and in real-time with additional EHR integration.
Need
Prioritize HCC documentation gaps
Chronic conditions go undocumented each year, lowering RAF scores and reducing the benchmark against which shared savings are calculated. Most recapture tools surface raw gaps without context, overwhelming providers with low-yield alerts.
Solution
Unique approach that pairs predicted likelihood to recapture with HCC weight
HDAI's proprietary methodology combines raw RAF opportunity with national expected recapture rates from digital twinned Medicare populations. The result: physicians see the clinically relevant, highest-yield HCCs for each patient, not the longest list.
Solution
Unique approach that pairs predicted likelihood to recapture with HCC weight
HDAI's proprietary methodology combines raw RAF opportunity with national expected recapture rates from digital twinned Medicare populations. The result: physicians see the clinically relevant, highest-yield HCCs for each patient, not the longest list.
Need
Network decisions are based on relationships, not risk-matched data
ACOs rely on provider networks they cannot fully evaluate. Referral patterns drive cost and quality outcomes, but without risk-matched benchmarking, identifying underperforming SNFs, home health agencies, or specialists is largely guesswork.
Solution
Digital twin-powered network analytics
Every SNF, home health agency, and provider group in your network is scored against risk-matched national peers using HDAI's digital twinning methodology. Metrics include cost, readmissions, length of stay, and adverse events, giving ACO leadership the evidence to redirect referrals toward higher-performing providers, renegotiate contracts with underperformers, and reduce avoidable post-acute spending.
Solution
Digital twin-powered network analytics
Every SNF, home health agency, and provider group in your network is scored against risk-matched national peers using HDAI's digital twinning methodology. Metrics include cost, readmissions, length of stay, and adverse events, giving ACO leadership the evidence to redirect referrals toward higher-performing providers, renegotiate contracts with underperformers, and reduce avoidable post-acute spending.
Need
Identify and proactively reach out to patients with advanced illness
Patients approaching end-of-life milestones are often identified only during a crisis admission, when treatment options have narrowed and families are overwhelmed. Without earlier identification, goals-of-care conversations default to the hospital instead of the home.
Solution
Predictive identification and palliative care patient summaries
Mortality and hospice risk models identify patients approaching advanced illness before a crisis, giving care teams the time to have meaningful goals-of-care conversations when patients and families can still shape their own care. Automated summaries surface information buried in the record but useful for palliative teams, hospitalists, and others.
Solution
Predictive identification and palliative care patient summaries
Mortality and hospice risk models identify patients approaching advanced illness before a crisis, giving care teams the time to have meaningful goals-of-care conversations when patients and families can still shape their own care. Automated summaries surface information buried in the record but useful for palliative teams, hospitalists, and others.
Areas of Impact
Risk Stratification & Care Management
Segment your entire attributed population by predicted risk and intervention potential. Condition-specific models across cardiac, respiratory, renal, and behavioral health populations surface the patients most likely to benefit from proactive outreach, enabling care management teams to focus where the impact is greatest.
- Full population segmented into hospice, advanced illness, complex care, rising risk, and low risk cohorts
- Condition-specific predictive models across dozens of clinical endpoints
- Weekly roster updates from CMS claims data via BCDA
- Contributing risk factors surfaced for each patient
- Prioritization by intervention potential, not severity alone
- Works across 10+ EHR environments
Protect Your Margins with Proactive Detection of Anomalous Billing Practices
Anomalous billing patterns can silently erode shared savings. HDAI monitors your claims data to identify spend irregularities, such as unusual provider billing spikes, product cost escalations, and utilization outliers, and flags them before they impact your settlement. This capability has already helped partner ACOs uncover millions in anomalous charges across categories including wound care, DME, and specialty pharmacy.
Who We Help
MSSP Accountable Care Organizations
REACH ACOs
New LEAD ACOs (2027)
CMS TEAM Model Designated Hospitals
Value-Based Care Organizations (Medicare Advantage & VBO)
Medicaid Managed Care Organizations
Self-Insured Employer Groups
Other Value-Based Care Organizations
Take Control of Your Population Performance
See how predictive population health analytics can transform your value-based care strategy.