NEW YORK – Pharmaceutical firms and other healthcare organizations will now be able to conduct evidence-based research on data that enables them to better quantify the effectiveness of medical treatments on discrete patient populations, thanks to a new data and analytics solution developed and delivered by GE Healthcare and Thomson Reuters.

When needed to answer appropriate population-based health economics and outcomes research questions, healthcare analytics teams at General Electric and Thomson Reuters now have the ability to combine commonly used outcomes research data from the Thomson Reuters MarketScan Research Databases with de-identified electronic medical records data, while maintaining patient privacy and full compliance with HIPAA standards.. As a result, researchers and physicians can now gain new evidence-based insights into treatment protocols. These insights can help drive improved health outcomes.
 
The addition of de-identified clinical data provided by healthcare providers using EMR means a research study can evaluate medical treatments — commonly called “outcomes research” or “comparative effectiveness research.” The addition of the de-identified clinical data from the EMR means a research study can link de-identified claims data from a population of patients diagnosed with a particular condition such as hypertension, with de-identified clinical data on everything from a patient’s body mass index, blood pressure, symptoms and more. This research would provide more specific evidence to enable clinicians and patients to make better informed decisions.
 
“We’ve tackled what was once considered an insurmountable barrier to outcomes-based research,” said  Brandon Savage, MD, chief medical officer at GE Healthcare IT. “We’re extremely enthusiastic about the opportunities this discovery creates for the field and the improvements it may someday bring to patient care, across the world.”
 
Researchers from GE Healthcare and Thomson Reuters first demonstrated this approach to linking de-identified data in a presentation at the annual meeting of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) held in Atlanta in May 2010.
 
The ISPOR presentation, which used hypertension as a sample set, combined de-identified clinical data collected from more than 9,000 electronic medical records with MarketScan claims and prescription data from more than 30 million individuals. Each dataset has since grown considerably, resulting in an increasingly powerful data source.
 
Teams from both organizations have developed algorithms which enable the de-identification of patient data without loss of utility.
 
The companies subsequently proved the ability to use these proprietary methodologies to link additional therapeutic areas. They have now entered into a partnership to provide research and analytical services based on this proven capability.
 
“We can now conduct studies that assess the effectiveness of medical treatments, prescription adherence, and disease management initiatives based on both a deep set of clinical data and extensive data on the complete healthcare experience of a de-identified patient. This includes all hospitalizations and ambulatory visits as well as all filled prescriptions, costs, and reimbursements,” said Bill Marder, senior vice president at Thomson Reuters.
 
The companies are now engaging customers and planning studies that will demonstrate the value of these unique and comprehensive capabilities.