Guest column

To access the rewards of big data in health care, potential risks must be managed

(Image: Getty/Crisfotolux)
(Image: Getty/Crisfotolux)

Related tags Big data Wearables Ethics Clinical trials

Increased access to real-world data sources opens up new possibilities, but it also raises new ethical questions, which cannot be tackled by one organization, government agency, or company alone.

In the last decade, an unprecedented amount of health care data has been collected, generated, and analyzed from beyond the traditional clinical trial setting.

Read: How the industry is addressing the ethical concerns of incorporating big data into health care

Today, millions of people wear devices that track their movements and measure their heart rates. They map their genetic lineages from the comfort of their homes. And their web searches and insurance forms reveal new details about their behaviors and health risks.

Increased access to these real-world “big data” sources opens up new possibilities to improve our health, better understand disease, and advance treatments. But it also raises new ethical questions and concerns around how to responsibly use this information for good.

Big data will continue to proliferate as technology advances and the definition of what constitutes medical data will continue to expand.

At a recent symposium​ hosted by the New York Academy of Sciences and New York University School of Medicine and sponsored by Johnson & Johnson, leading health care, science and technology experts from 23andMe, Duke Clinical Research Institute, FDA, Merck, US Department of Health & Human Services, Verily (a Google company), and Vanderbilt University, among others, debated the ethical risks and rewards of health care big data.

Five key points emerged:

  1. Evidence generation is evolving.​ Traditional clinical trials have long been the gold standard to assess the safety and effectiveness of therapeutics, but big data is increasingly integrated into trial processes. It is therefore important to consider the standards that the use of big data should be held to, especially if such data is used to inform policy changes, drug approvals, and other health care decisions.
  2. We must balance privacy and impact. ​Health data are some of our most sensitive information. That is why it is vital to carefully balance the potential rewards of leveraging big data to improve public health with the risks of sharing information that could jeopardize individual privacy and even safety. While anonymization offers some protection, there is growing evidence that sometimes individuals still can be identified through a few seemingly innocuous data points. Some experts believe stronger penalties could help deter data breaches. Others feel that true privacy may no longer be possible, and we should instead focus on punishing data misuse.
  3. Data ownership is a complex issue.​ After consumers and patients agree to share their data from clinical trials, medical devices, and other sources, who owns it? Legally, once the data are collected and de-identified, they may no longer belong to the individual. Yet these data are sometimes used beyond their express purpose, including for commercial gain. If companies profit from the data, some patients and consumers think they should have a piece of the revenue.
  4. Be aware of potential bias and discrimination.​ There is the potential for bias across every stage of the big data process—from collection to analysis to decision making. Results are skewed if specific groups are underrepresented in datasets, or if algorithms are impacted by researchers’ beliefs or viewpoints (whether implicit or explicit). Big data can also reveal pre-existing conditions or other health factors that potentially could be used by insurance companies to justify coverage discrimination. Recognizing and addressing bias is critical to ensure that everybody can reap the benefits of big data in health care.
  5. Big data only gets us so far. ​We already have tremendous amounts of medical data. As a next step, we must determine how to implement it effectively, integrate it into existing health care systems and capitalize upon innovative new uses. Incentivizing groups to use big data for the common good and to responsibly share data will help pave the way toward more equitable rewards for all.

No one organization, government agency, or company can tackle these questions around big data management and protection alone. Solutions come from a collaborative effort and dialogue guided by transparency and ethics.

In this exciting new era of health care management, we must work together to establish policies and principles that protect the public while fostering innovation. 

Related news

Show more

Related products

show more

Saama accelerates data review processes

Saama accelerates data review processes

Content provided by Saama | 25-Mar-2024 | Infographic

In this new infographic, learn how Saama accelerates data review processes. Only Saama has AI/ML models trained for life sciences on over 300 million data...

More Data, More Insights, More Progress

More Data, More Insights, More Progress

Content provided by Saama | 04-Mar-2024 | Case Study

The sponsor’s clinical development team needed a flexible solution to quickly visualize patient and site data in a single location

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us


View more