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Case Study
Patient & HCP Targeting with Dynamic HCP Profiling and Targeting
Leveraging Machine Learning to Optimize Care for Patients with Type 2 Diabetes and Obesity
Nov 02, 2022
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  • Patient & HCP Targeting with Dynamic HCP Profiling and Targeting
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Read this case study to learn how a large pharmaceutical company interested in identifying HCPs treating diabetic patients with comorbid obesity leveraged IQVIA’s Dynamic HCP Profiling and Targeting solution to draw market insights and optimize care quickly and easily. 

Many patients diagnosed with type 2 diabetes have comorbid diagnoses of obesity. This case study shows how machine learning helped a large client more accurately identify patients and target their HCPs, thereby facilitating optimal care. This project relied on use of IQVIA’s rich, claims-based US healthcare data assets.

Key business questions answered:
  • Which healthcare providers had high volumes of patients with both obesity and type 2 diabetes?
  • Which patient populations with type 2 diabetes and obesity were not being treated appropriately for their comorbid obesity?

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.

Just send us a message and we'll connect you to a dedicated expert who you can give you a demonstration, customized to your goals and needs.

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