IQVIA AI

‏AI you can trust. Introducing IQVIA Healthcare-grade AI™.‏‏

IQVIA AI is intelligence engineered to meet the level of accuracy, speed, and trust required for life sciences and across healthcare.
IQVIA AI

Powered by IQVIA Connected Intelligence™

From unparalleled data to deep healthcare expertise, critical connections enable AI with new levels of speed, precision, reliability, and scale. 

AI designed for healthcare & life sciences

Delivering AI that truly meets the demands of healthcare requires globally diverse, trusted data, AI & healthcare experts working side-by-side to design optimized foundations for healthcare, and benchmarking to ensure quality outputs.

We’ve built on our rich history of using AI for healthcare to develop a different class of AI that’s powered by IQVIA Connected Intelligence™. 

IQVIA AI connects the right data, right technology, and right expertise to address the unique needs of healthcare. We call it Healthcare-grade AI.

Generative AI

Resourced and ready for the future of AI

The emergence of generative AI is creating exciting opportunities for our industry and IQVIA is ready to help you make the most of this, and other new AI technologies. 

With an extensive history of applying AI to solutions for healthcare, we continue to build on our expertise to leverage new technologies to the fullest extent of their capabilities. To ensure we’re getting the best results for you, all while improving patient outcomes. Backed by the security, privacy, and efficiency that healthcare demands. 
Publication
Boosting healthcare capacity with AI
Hear from IQVIA experts Aurelio Arias and Sarah Rickwood on how AI in healthcare could bridge a significant capacity gap.

CASE STUDIES

Improving patient outcomes and closing care gaps

IQVIA is working with life sciences companies, governments, and non-profit organizations to power smarter healthcare with advanced AI capabilities.

Iqvia Human data science

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%). 
Elderly man with cane chatting with female nurse

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. 
Father and children having breakfast in kitchen

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.

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.

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.

Responsible AI

We work with partners globally to responsibly advance AI

Dedicated to privacy, security, trust

Protecting patients and organizations is our priority. We have internal teams advising on and dedicated to ensuring the highest standards of privacy.

Commitment to regulatory alignment

We work with organizations like the World Economic Forum to help shape global AI policy and regulations and regularly publish materials on best practices.

Driving & adhering to global data standards

Driving data standards across the industry and adhering to standards like FAIR Principles is critical to reliable and responsible use of data.

Contributing to the development of AI

IQVIA is committed to advancing the latest thinking on AI. With an intellectually rigorous approach, we have published more than 200 AI scientific publications to date.

Related solutions

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