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IQVIA AI
AI engineered for life sciences & healthcare
IQVIA Healthcare-grade AI® is engineered to meet the level of precision, speed, and trust required for life sciences and healthcare.
AI designed and guided by experts. Results you can trust.
Everything we do in our industry ultimately has an impact on patients, so it’s imperative that we deliver AI that’s built on a foundation of unparalleled data, expertise, and trust.
With IQVIA Healthcare-grade AI®, we’re building on our rich history of deploying AI to connect the right data, technology, and expertise to address the unique needs of each challenge we help our customers solve.
With IQVIA Healthcare-grade AI®, we’re building on our rich history of deploying AI to connect the right data, technology, and expertise to address the unique needs of each challenge we help our customers solve.
IQVIA AI enables revolutionary patient impact
From diagnosing diseases earlier to finding better ways to treat those diseases, IQVIA Healthcare-grade AI® is helping customers and patients get better results and outcomes.
At IQVIA, we’re committed to advancing patient health all over the world, and we’re excited by the new possibilities AI is creating for the life sciences industry.
At IQVIA, we’re committed to advancing patient health all over the world, and we’re excited by the new possibilities AI is creating for the life sciences industry.
Trust in AI is built on transparency, explainability, auditability, and strong governance. Our solutions meet rigorous scientific and regulatory standards, with experts-in-the-loop to guide development to enable technical soundness and real-world relevance.
IQVIA Healthcare-grade AI® is grounded in quality data, guided by expertise, and connected throughout every IQVIA AI capability. For customers, this enhances time to value, quality of insights, confidence in decision-making, and delivers results at the highest standards.
IQVIA HEALTHCARE-GRADE AI® IN ACTION
Improving patient outcomes
IQVIA is deploying AI for life sciences companies, governments, and non-profit organizations to power smarter healthcare and get better results, faster.
Closing care gaps with Social Determinants of Health (SDoH)
Challenge: Social factors such as employment status, financial situation, or stress are useful predictors of health outcomes but are often only captured in unstructured physician notes. For example, NorthShore University HealthSystem found only 0.1% of patient records had these fields completed.
Solution: IQVIA assisted NorthShore with the use of Natural Language Processing (NLP) to assess that unstructured data across multiple sources.
Results: NorthShore is now able to help close care gaps by identifying and screening 56% more at-risk patients. In one example, they were able to identify at least one SDoH risk factor in 30% of their patient population (up from only 0.1%).
Solution: IQVIA assisted NorthShore with the use of Natural Language Processing (NLP) to assess that unstructured data across multiple sources.
Results: NorthShore is now able to help close care gaps by identifying and screening 56% more at-risk patients. In one example, they were able to identify at least one SDoH risk factor in 30% of their patient population (up from only 0.1%).
Reducing risk of stroke for AFib patients
Challenge: Atrial Fibrillation (AFib) patients are 5x more likely to have a stroke. IQVIA partnered with the UK National Health Service to reduce AFib related strokes through identifying at-risk patients.
Solution: The risk of stroke for AFib patients was predicted using EMR data including age, gender, and clinical risk factors (e.g. Congestive Heart Failure, Hypertension, Stroke/Transient Ischemic Attack, Diabetes, Vascular Disease).
Results: Annul strokes reduced by approximately 22% during the implementation phase compared to the prior period. This also led to an estimated reduction in healthcare costs amounting to an annual savings of approximately $2m.
Solution: The risk of stroke for AFib patients was predicted using EMR data including age, gender, and clinical risk factors (e.g. Congestive Heart Failure, Hypertension, Stroke/Transient Ischemic Attack, Diabetes, Vascular Disease).
Results: Annul strokes reduced by approximately 22% during the implementation phase compared to the prior period. This also led to an estimated reduction in healthcare costs amounting to an annual savings of approximately $2m.
Improving care for patients with Type 1 Diabetes
Challenge: Nearly 40% of adults with Type 1 Diabetes are initially misdiagnosed with Type 2. IQVIA worked with the Juvenile Diabetes Research Foundation (JDRF) to identify Type 1 patients most likely to be misdiagnosed.
Solution: IQVIA developed an AI algorithm on EMR data, to identify misdiagnosed Type 1 among patients with Type 2 at different points in the patient’s treatment journey.
Results: Inputs into the AI algorithm are routinely collected in EMR data – thus available within any Healthcare Organization (HCO) providing opportunity to deploy the program at scale. The algorithm is currently being prospectively validated at 4 US HCOs testing 2 different scaling paths.
Solution: IQVIA developed an AI algorithm on EMR data, to identify misdiagnosed Type 1 among patients with Type 2 at different points in the patient’s treatment journey.
Results: Inputs into the AI algorithm are routinely collected in EMR data – thus available within any Healthcare Organization (HCO) providing opportunity to deploy the program at scale. The algorithm is currently being prospectively validated at 4 US HCOs testing 2 different scaling paths.
Enhancing routine care for diabetes and CVD
Challenge: The government of one Middle East country is investing in AI to make better healthcare decisions in the diagnosis and treatment of both diabetes and cardiovascular disease.
Solution: IQVIA developed 14 decision support tools that can be used by physicians to help guide screening, improve preventative care and optimise disease management.
Results: The program is being delivered by a cross-functional team of local and global IQVIA experts over a three year period.
Solution: IQVIA developed 14 decision support tools that can be used by physicians to help guide screening, improve preventative care and optimise disease management.
Results: The program is being delivered by a cross-functional team of local and global IQVIA experts over a three year period.
Identifying patients at risk for respiratory disease
Challenge: A client launched a new product to treat respiratory disease. They needed help identifying patient cohorts with this specific unmet need to then reach physicians most likely to have these patients.
Solution: IQVIA deployed the AI/ML Platform capability to identify and profile eligible patient populations with unmet needs. The patients were profiled based on sub-national concentration, demographics and other clinical drivers, with focus on physicians treating them.
Results: Patients predicted for high likelihood to have respiratory disease with 86% precision, while removing approximately 30% of non-target patients from the target population data. Furthermore, a 6-month analysis of patients on this new treatment showed a 17% reduction in uncontrolled disease status.
Solution: IQVIA deployed the AI/ML Platform capability to identify and profile eligible patient populations with unmet needs. The patients were profiled based on sub-national concentration, demographics and other clinical drivers, with focus on physicians treating them.
Results: Patients predicted for high likelihood to have respiratory disease with 86% precision, while removing approximately 30% of non-target patients from the target population data. Furthermore, a 6-month analysis of patients on this new treatment showed a 17% reduction in uncontrolled disease status.
AI GOVERNANCE
Committed to the responsible use of AI
Delivering on the promise of IQVIA Healthcare-grade AI® means applying robust AI governance principles every step of the way, guided by experts-in-the-loop, no matter what kind of AI we’re using.