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Case Study
AI-Powered Modeling Finds Potentially Non-Adherent Patients for Outreach
Precise linkage of over 900 potentially non-adherent patients to HCPs streamlined outreach efforts
Apr 25, 2023
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IQVIA's leading Real World Data (RWD) assets, along with our artificial intelligence (AI) and machine learning (ML) algorithms help drive new insights and accelerate commercial success in ways that were never possible before.

This client case study shows how we leveraged our ML and AI capabilities to help IQVIA’s healthcare clients find the right patients and HCPs, while developing new patient journey insights – both with accuracy and speed.

Important Outcomes in this AI Case Study:

Our AI-powered modelling helped achieved results like these:

  • Identification and precise linkage of over 900 potentially non-adherent patients to the relevant network of HCPs
  • Optimization of outreach efforts to focus on HCPs managing patients at risk of early discontinuation of therapy
  • Timely predictive alerts allowing for the counsel of at-risk patients in “real-time”
Our AI Drives Commercial Success

AI and ML can dramatically accelerate time to insight: our advanced healthcare analytics platforms can process patient data in massive volumes and with a precision beyond any other method. In other cases, AI/ML methods can provide entirely new methods of advancing healthcare, such as efficiently spotting patients who are at risk for certain conditions before those conditions are clinically evident.

AI Experts, More Case Studies

Want to see how IQVIA AI-powered modeling can dramatically accelerate your results? Ask to speak with an AI expert. You can also see other AI case studies highlighting improvements in patient segmentation and HCP identification.

Have questions? Want a demonstration ?

We'd love to show you how AI and Machine Learning can help you find the right patients, the right HCPs, and develop patient journey insights with precision and speed.
Speak to an expert

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HCP Targeting and Segmentation

Use predictive analytics and machine learning to identify providers most likely to prescribe your brand, and see ways to cut through the noise.

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