Healthcare payer proof of concept: Enabling value-based care analytics & AI applications
A seamless integration of type 2 diabetes member data HULFT
A Proof of Concept Pilot Engagement for Payers
POC Scenario & Goals
Meaningful integration of member data for a population that is clinically diagnosed with diabetes to control costs and improve quality of care.
- Deploy a platform that can handle complexity of health data, seamlessly collect, move, aggregate and meaningfully integrate data.
- 800+ discrete fields for patient level clinical data set; 20-30 fields for financial transactions.
POC Overview Leverage
HULFT to build a limited purpose integrated environment from disparate data sources and disconnected systems.
- Claims Processing System
- PBM system/ Prescription Data
- Claims payment
- Provider directory
- Provider contract system
- Eligibility Verification System
- Medical case management
- Referral management system
- EHR systems in provider networks
- Call center management
- EMPI
POC Outcome
Identify care gaps and generate select reports:
- Who did not have a retinal or dilated eye exam
- Who did not have a nephropathy test
- Who did not have an HbA1c test
- With no blood pressure record
Identify member leakage due to out-of-network referrals, generate select reports:
- Percentage of out-of-network claims by zip codes
- Percentage of distribution of cause of the leakage (ie, seeking second opinion, lack of cost transparency, appointment scheduling frustrations, communication breakdowns)
Go-Forward Engagement
HULFT offers a low-code/no-code integration platform that enables payers to:
- Engage members
- Optimize risk adjustment and quality
- Accelerate speed to market
- Prevent fraud
- Establish environment for analytics and AI applications
- Uniquely suitable to feed PHM applications
- Can build layers of bucket, payers can apply ML and AI tools to develop models for multiple analysis: More precise phenotyping of member populations; predictive models to identify patients at various levels of risk; models for unsupervised learning to generate hypotheses
HULFT helps healthcare payers automate, orchestrate, and accelerate their data at scale.