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Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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The need for a new a discipline
Human Data Science
Feb 25, 2020
The promise of a new era in healthcare is exciting. The availability of ever-expanding healthcare data coupled with advances in human science and digital technology are fueling an opportunity for new approaches to bring innovative, life-saving treatments to patients faster.
Today, we have access to more information than ever before—information that is improving our understanding of human biology and helping healthcare stakeholders maker better, more informed decisions. But making sense of all of this data can still be difficult. Harnessing the myriad of data to create breakthroughs will require us to think differently using a multi-disciplinary approach known as Human Data Science.
Human Data Science will augment our ability to take advantage of important trends in healthcare and science:
Scientific advances are accelerating. A record number of new active substances (NAS) were launched in the United States in 2018, bringing 59 new treatment options to patients. Almost half of these therapies carried an orphan drug designation and more than a third of NAS launches were identified by the FDA as first-in-class, having mechanisms of action different from those of existing therapies. Despite this increased output, gaps in our understanding of underlying disease causes and molecular processes across therapy areas are slowing the overall development of life-saving treatments.
Technologies such as artificial intelligence (AI) and machine learning (ML) are becoming more prevalent in healthcare, though 85 percent of life sciences executives explain that AI is advancing faster than their organization’s ability to adopt the technologies. At the same time, information technology is being progressively incorporated into clinical practice to improve care and manage costs. Patients are getting more involved in their own health by engaging with wellness technologies and are participating in their own healthcare decision-making. Despite all of this, we are faced with disparities in healthcare access and delivery related to an individual’s environment and social factors.
Big data in healthcare presents new opportunities. Applying data science to raw, unstructured, disparate sources of data is allowing us to answer increasingly complex questions. It’s essential to understand the nuances of healthcare data to avoid the common pitfalls associated with collecting, connecting and preparing big data for advanced analysis. While data science is advancing with a plethora of new data sources, challenges remain with data collection, bias in data, and the disparate and siloed nature of data sources.
Enter, Human Data Science
The emerging discipline of Human Data Science can be applied to address some of the biggest challenges that exist in healthcare today. It leverages technology and data science built for healthcare to enable new levels of access, security and analysis that were previously out of reach. In addition, the deep domain expertise of human science is a critical element to link disparate data sources that are siloed into a more complete picture of human health. It is now possible to get more out of healthcare data by combining the analytic rigor and clarity of data science with the ever-expanding scope of human science.
The powerful forces of human ingenuity, breakthrough science and disruptive technology that Human Data Science has unleashed promise to power future healthcare advances and improve health outcomes for individuals and populations globally.
For a deeper dive into Human Data Science, explore our new video series. The series features in-depth insights into the current state of healthcare, the principles of Human Data Science, stakeholder engagement, and Human Data Science case studies.
Learn more about our vision for healthcare with Human Data Science.