TietAI has raised €2.5M in seed funding to bring AI into the operational heart of hospitals
Use case

Population Health Analytics & Quality Reporting

Hydra connect unifies clinical, claims, lab, and SDOH data into trusted population insights. Identify high-risk patients, automate quality reporting, and drive proactive care decisions with harmonized, analytics-ready data that powers value-based performance and better outcomes.

Population Health Analytics & Quality Reporting
The Impact
Improve quality measure tracking
The Challenge

The Challenge

Data fragmentation usually drives healthcare bodies to the inability to aggregate and analyze patient data for population health insights and quality measures. When clinical, claims, lab, and SDOH data live in silos—each with different identifiers and vocabularies—there's no reliable longitudinal view of patients or populations.

Late, inconsistent and untrusted indicators have huge consequences on regulators and hospital managers alike. Without proper harmonized, analytics-ready data and consistent measure logic, teams can't confidently compute HEDIS/CMS metrics, surface care gaps in time, or direct resources where they'll have the greatest impact.

The Solution

The Solution

TietAI generate trustworthy population statistics end-to-end: Multi-Source Data Aggregation consolidates clinical, claims, lab, and SDOH data into unified patient profiles and a consistent population table. The platform's AI-powered Risk Stratification Engine identifies high-risk patients and predicts potential health outcomes, enabling proactive care management.

The Risk Stratification Engine produces explainable risk scores and cohort flags that roll up cleanly by payer, service line, and geography; and Automated Quality Reporting continuously computes denominators/numerators for HEDIS, CMS Star Ratings, and custom indicators with real-time refresh and drill-downs to member lists. The outcome is accurate, current population metrics, trends, and gap-closure dashboards you can rely on for planning, contracting, and targeted interventions.

Multi-Source Data Aggregation

Combine clinical, claims, lab, and social determinants of health (SDOH) data from multiple sources into unified patient profiles.

Risk Stratification Engine

AI-powered risk scoring to identify high-risk patients and predict potential health outcomes.

Automated Quality Reporting

Generate HEDIS, CMS Star Ratings, and other quality-measure reports with real-time data updates.

The Impact

The Impact

A unified and reliable view in hands of health planners, turns a biases partial outlook into a full picture of their populations. Clinical and operational teams can track quality measures in real time, identify care gaps before they escalate, and target interventions where they matter most. The result: faster, more accurate reporting, stronger performance in value-based programs, and measurable improvements in population health outcomes.

1

Improve quality measure tracking

2

Enable preventive care interventions

3

Optimize value-based care performance

4

Accelerate quality reporting

Ready to modernize this workflow?

Book a 30-minute working session. We will map your current process, identify integration bottlenecks, and show where TietAI can reduce manual work.

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