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, no matter what kind of AI we’re using, to ensure optimal and responsible impact.

Setting the standard for AI governance

Ensuring responsible AI practices in healthcare is critical to the impact AI can have on patient well-being, treatment outcomes, and the overall integrity of healthcare systems. A consistent and dedicated approach to AI governance is essential.

IQVIA is committed to effectively addressing concerns around bias, transparency, accountability, and ethics to deliver a uniform approach to AI, backed by a standardized, ethical framework that guides development and deployment of AI across our portfolio.

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.

Our guiding principles

Fairness reduces bias

Fairness is essential to ensuring that AI systems are developed and used without discrimination and bias. This requires constant evaluation and mitigation of any biases identified in the data and algorithms. This ensures that they are suitable for their intended use cases while improving protections for individuals and groups from the negative impacts of bias.

Transparency enhances trust

Transparency in algorithms and data sources facilitates better oversight, scrutiny, and auditability. Our teams make their AI technologies and supporting data sources available to other IQVIA experts for review and follow the four key considerations outlined to the right.

Respect enables privacy

Respect is essential to protecting the rights and values of the individuals or data subjects involved in any assessment. This includes obtaining consent for any analysis of personally identifiable data, confirming the non-identifiability of all de-identified data, and regularly reassessing to ensure ongoing protection of data. Respect for privacy at IQVIA is not limited to AI and extends to all areas of our business.

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Auditability improves performance

Auditability aims to enforce the appropriate structure and processes to allow for rigorous and periodic audits of applications and performance. This facilitates efficient and timely compliance with organizational and regulatory requirements. Lack of auditability may expose AI systems and solutions to additional regulatory scrutiny. Some safeguards employed include:

  • Documentation maintained for algorithms, model and code
  • Algorithm code is source-controlled in a uniform repository
  • Models and visualizations are deployed through approved systems
  • Datasets are versioned
  • All activity on environments is logged and auditable

Healthcare-grade AI™ for a healthier world

Ensuring the responsible use of AI enables us to help improve results, and ultimately make a bigger impact for patients. 

Pragmatic Application of Healthcare AI Governance
This document explores regulatory frameworks and guidelines for Artificial Intelligence (AI), highlights common foundational principles of best practice, and provides tangible examples of data and analytics management approaches to meet some of these best practice guidelines.
U.S. Healthcare and AI: Why Data Governance Matters More Than Ever
With the rapid pace at which new AI tools are being used in the workplace, it’s clear that now is the time to institutionalize a new approach that proactively makes data governance a business imperative.
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