Research Support

Shaping the future of healthcare

The IQVIA Institute conducts empirically rigorous, policy-relevant studies to improve the quality and cost-effectiveness of healthcare. The Institute and its academic advisory board include members from a variety of disciplines including pharmacy, medicine, law, economics, business, and public policy.

Recent projects include an examination of trends in prescription opioid use, global and U.S. pricing dynamics, antibiotic utilization and trends in the use of technology and innovation in healthcare.

Research priorities

The IQVIA Institute welcomes proposals examining most aspects of healthcare, projects that are directly relevant to ongoing healthcare reform are of greatest interest. High-priority areas include

  • Comparative effectiveness
  • Drug utilization trends and expenditure
  • Real world practice
  • Geographic variations in care

Comparative Effectiveness Research

  • Evaluations of which interventions work best, for whom, and under what circumstances
  • Analyses of how comparative effectiveness research is reflected in clinical practice

Drug Utilization Trends and Expenditures

  • Analysis of national trends in prescription drug utilization and office-based care
  • Examination of adoption of new therapies among patient and physician subpopulations
  • Evaluation of prescription use and expenditures and factors that influence these trends

Real-World Practice

  • Analysis of association between patient, physician, and health system characteristics and practice patterns
  • Establishment of best practices and quality metrics for specific conditions or populations, including for preventive care and screening
  • Utilization trends and costs in specific medical areas, such as oncology, cardiovascular disease or rare diseases where orphan drugs or specialty drugs are used
  • Investigations of socioeconomic, racial, or ethnic disparities in processes or outcomes of care

Geographic Variations in Care

  • Examination of geographic variations in treatments, costs and outcomes
  • Ecologic studies examining how geographic variation in prescription use (e.g., antibiotics) is associated with specific outcomes (e.g., antimicrobial resistance)
  • Studies using geographic variation in use to infer information regarding disease or treatment prevalence

Access to data and analysis

Through collaboration with the IQVIA Institute, researchers and students have access to a broad range of proprietary databases and tools to support independent research, discovery work and requirement development for future funded studies.

IQVIA Real World Data

  • De-identified patient activity across healthcare channels including Prescription Claims (retail and mail), Medical Claims, Hospital EMR, Health Plan, Consumer Behavior
  • 300+ million anonymous patients
  • Data available starting with the early 2000’s
  • Data can be linked (for example Prescription Claims and Medical claims) via the unique non-identified patient I.D

IQVIA Prescription Drug Data

  • Over 90% coverage for dispensed prescriptions
  • National views and sub-national views to state, county, zip code or prescriber granularity
  • Retail, mail and long-term care channels
  • Age, gender, co-pay, method of payment and payer details

IQVIA OneKey Reference Assets

  • Organization and professional reference data
  • Includes NPI, AMA, SLN, DEA, and AOA
  • Over 600,000 organizations and >8.9Mil professionals (~2.1mil prescriber eligible)
  • Includes physicians, nurse practioners and physician assistants
  • Includes ACOs, IDNs and affiliations
Learn More
Contact Us
Contact Us

Email Us

Interested in learning more about how IQVIA can create solutions to help you drive healthcare forward?

Call Us

We're available during standard business hours.

U.S. Toll-Free only
+1 866 267 4479

For international call please find a number in our toll-free list.

IQVIA Institute Inquiries

The IQVIA Institute for Human Data Science contributes to the advancement of human health globally through timely research, insightful analysis and scientific expertise applied to granular non-identified patient-level data.