The complexity and differences in privacy laws make it difficult for researchers to use huge amounts of individual data, called big data, to improve public health and clinical outcomes, said Cason Schmit, JD, assistant professor at Texas A&M University School of Public Health in College Station, Texas, where he leads the Health Law and Policy Program. If the US public health service, and the health sector in general, is to get the most from big data, the country must abandon its current approach to data protection.
“A comprehensive data protection law that allows the use of data for public health and research is needed to truly understand the impact of social determinants of health, as this data is scattered and protected by different laws with different standards,” said Schmit.
Without a comprehensive data protection law, the application of big data in medical research and in public health will encounter significant obstacles, said Schmit. “HIPAA is often wrongly viewed as an obstacle to science and public health. In fact, HIPAA is one of the few federal data protection laws with robust provisions that allow disclosure of identifiable information for both public health and research purposes, ”Schmit said.
Excessive protection guidelines
Obstacles to the use of big data include the adoption of very conservative guidelines that limit otherwise perfectly legal data usage. Organizations may adopt such guidelines because they do not fully understand HIPAA regulations or want to make it easier to comply with a complex law with overly broad restrictions. Another reason could be the overprotection of commercially valuable and personally sensitive information. “While some organizations publicly justify these safeguards by serving their patients, our research shows that the public agrees that their data is used to promote social well-being such as research and public health,” Schmit said.
Schmit recently led a study in which 504 nationally representative participants were asked how they felt comfortable with different big data usage scenarios. The results of the study, published in the Journal of Medical Internet Research, suggest that the public strongly prefers the use of big data for public health and research purposes over for-profit, marketing, or crime-solving activities.
What the public prefers
The existing patchwork of US privacy laws does not reflect public preference for individual data usage. The survey results suggest that the public is more concerned about who is using the data for what purposes, and that individuals have a strong preference for data uses that are for the common good as opposed to commercial interests, Schmit said.
HIPAA has been widely criticized for its incredibly broad and vague definition of “identifiable” information, according to Schmit. As a result, many organizations rely heavily on the HIPAA Safe Harbor rule for legal anonymization, which lists 18 types of identifiers. Some organizations insist on removing all of these identifiers before releasing information for research or public health, which is not required by law and can drastically reduce the usefulness of the information.
Michael Greenberger, JD, founder and director of the Center for Health and Homeland Security at the University of Maryland at Baltimore, said that big data should flow freely, but policies to make it happen must be carefully developed with all interested parties in mind. “In my opinion, all interests can be taken into account,” said Greenberger. “You can delete the person’s identity. I think big data is needed for research. I think it’s a helpful part of our advances in science and for medical researchers, “said Greenberger.
The promise of big data
Stefano Piotto, PhD, associate professor in the Faculty of Pharmacy at the University of Salerno in Italy, said big data could revolutionize health policy by improving the health and safety of citizens and reducing the cost of national health systems. “There is a lot of research that has shown this, and we have also been able to examine how behavioral data, the frequency and nature of human contact, can be used to anticipate outbreaks of a virus,” said Dr. Piotto. “If properly collected and used under the control of international health organizations, big data could become the first in silico medicine of our time. It could become the first line of intervention for future pandemics, ”said Dr. Piotto. In silico refers to methods or predictions that use computational approaches.
Shelley Tworoger, PhD, Associate Center Director of Population Science at Moffitt Cancer Center, Tampa, Florida, said big data has changed cancer care, especially during the pandemic. The ability to better understand how cancer occurs and how it is treated has grown exponentially with the advent of big data. For example, using machine learning and artificial intelligence methods to predict which people will have cancer recurrence or poor response to treatment has great potential for improving targeted treatment and earlier interventions when treatment has failed. “We also have a unique opportunity to use new electronic tools such as cell phone apps to provide information and interventions to patients to improve their outcomes and manage potential treatment side effects,” said Dr. Tworoger.
The appearance of the delta variant of SARS-CoV-2 initiated an urgent need for a quick response. By helping track infection rates, hospital stays and deaths, public health surveillance could be one of the most important ways big data can help fight the COVID-19 pandemic. “This can provide public health recommendations for prevention,” said Dr. Tworoger. “There is a great chance that more research will be done on the impact of the pandemic on cancer patients. For example, we are currently conducting a study asking cancer patients about their experience of COVID-19 exposure and infections and how they are trying to prevent exposure. ”
This article originally appeared on the Kidney and Urology News