Use big data and predictive analytics to improve human health.
Real-world data (RWD) has for some time been a goldmine for medical research. Now, by integrating RWD with clinical and biological information, and taking advantage of data infrastructure and advanced analytics, it is possible to gain new insights into the safety, efficacy and quality of care. These data aren't just valuable to the pharmaceutical industry; academic and public policy experts are increasingly using Real World Evidence (RWE) to address public health issues, and to directly inform public policies and treatment guidelines with far-reaching impact.
Last month, the IQVIA Institute and IQVIA Real World Insights held the second annual IQVIA Research Forum to showcase some of the groundbreaking studies that have been undertaken using extensive healthcare databases, data expertise and data analytic capabilities to provide policy-setters and decision-makers with new information on healthcare dynamics.
The day-long forum featured presentations from leading academics, industry professionals and government experts speaking on a range of topics, including the impact of RWE on drug pricing and solving public health challenges, and how RWD is used in health economics, and to improve the safety and effectiveness of drugs in the market. Many of the presentations included examples of studies that are changing medical care and treatment guidelines.
A compelling presentation came from Dr. Megan Noe at the University of Pennsylvania, who conducted research into the links between psoriasis severity and risk of mortality. Physicians know psoriasis is associated with higher rates of other comorbidities, including hypertension, diabetes obesity, and cardiovascular disease. Dr. Noe’s study set-out to determine whether mortality rate is stratified by disease severity.
Through a prospective, population-based cohort study of psoriasis patients using data gleaned from 11 million electronic medical records, she found patients with severe psoriasis had much higher mortality rates than those with mild or moderate conditions—comparable to mortality rates for smokers and diabetics. These insights will be used to help educate physicians and patients about the risks these patients face.
Dr. Daniel Budnitz, from the Center for Disease Control (CDC), shared results of his study to quantify the frequency of adverse drug events for different medication types. Using data from the National Electronic Injury Surveillance Systems (NEISS), Budnitz was able to estimate the rate of adverse drug events resulting in an emergency room visit across a variety of medication types, and then use the data to make recommendations for change. In one example, data showing an unusual level of unsupervised ingestion among children for a specific drug led to a simple packaging change, which ultimately reduced the frequency of emergency room visits for child ingestions of this drug by 65 percent.
Kimberley Woodcroft, associate scientist at Henry Ford Health System, shared details of her research project exploring how to fill knowledge gaps in medication safety during pregnancy. In the study, Woodcroft’s team developed a claims-based pregnancy algorithm that included exposure to medications and outcomes of pregnancy, which they are subsequently working to validate with QuintilesIMS data assets. Because pregnant women are typically excluded from clinical trials, many questions as to medication safety could potentially be gleaned from administrative claims databases. This research could be an important step in determining medication safety for pregnant women going forward.
Dima Qato from the University of Illinois at Chicago College of Pharmacy shared her research into the impact of pharmacy closures and medication adherence among older adults. There have been thousands of pharmacy closures in the U.S. in recent years, which affects access to medication. To prove the impact of these closures on adherence, Qato reviewed IMS LifeLink (LRx) patient-level data regarding statin-use among patients 50 years and older pre and post-pharmacy closure in 12-month time periods. The results show that pharmacy closures have an immediate and persistent effect on statin adherence, and that patients who filled their prescriptions at independent pharmacies experience a greater decline than those filling at chains.
She concluded that efforts to improve adherence should consider the role of pharmacy closures, and suggested that regulations to prevent closures, and/or ensure patients have adequate access to new pharmacies post-closure could mitigate this adherence risk. She is now considering a study into the impact of pharmacy closures on ER visits and hospitalizations.
These are just a few of the many innovative uses of IQVIA data to inform public healthcare and policy making. This forum underscores how important these studies are to enhancing our understanding of disease management, and to accelerate access to safer and more effective treatment paths.
We hope events like the Research Forum will encourage exploratory research using RWD, and we look forward to working with researchers across industry, academia and government to facilitate and promote this exciting work.
Use big data and predictive analytics to improve human health.
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