PatientIQ – Analytics for Real-World Data Powered by Agentic AI

Author Name:- Webinar Series: AI Without Limits

Analyzing real-world patient data is often complex, time-consuming, and dependent on technical expertise, making it difficult to generate timely insights.

In this session, we demonstrate how Agentic AI transforms patient analytics. Using our ciATHENA platform, complex analyses, traditionally dependent on SQL and manual effort, can now be performed through simple, conversational queries. From patient trends to switching behavior and persistence analysis, see how insights can be generated in seconds, directly within your data environment.

Read The Full Case Study Here

Key Takeaways

Understand the key challenges in analyzing large-scale claims and real-world patient data

Analyze patient data using simple, natural language, without SQL or manual effort

Eliminate reliance on static dashboards and accelerate insight generation with Agentic AI

Uncover deeper insights into patient trends, switching behavior, persistence, and line of therapy

Automate complex analytics workflows using domain-trained AI Agents

Speakers

Aneesh Gupta
Senior Principal,
CustomerInsights.AI

Ian Nevitt
Vice President
CustomerInsights.AI

Client Benefits

Solves Critical Business Headaches

The app promptly identified new affiliations, keeping the sales pipeline fresh and accurate. This ensured that their teams were always up to date with affiliations and details across the patient population (known and unknown). This results in a deeper understanding of the prescriptions in areas where disease identification and prescription locations differ.

Empowers Field Force

The on-field teams can contribute their on-ground knowledge, making strategies more aligned with real-world dynamics. Their insights ensure accurate IC calculations and better-informed decision-making.

Accurate and Integrated Data

Streamlined data reconciliation ensured accurate sales tracking, reducing risks of data conflicts. The app ensures a single source of truth is followed while managing the data, enhancing its reliability.

Regular Audits for Transparency

Routine audits and cross-referencing ensure data accuracy and build trust in the IC process, as the application can easily showcase which HCPs are the ones driving revenue from which relevant dialysis center.