The general public became aware of the deep connection between big data analytics and public health during the COVID-19 pandemic. Even the most casually interested person eagerly shared metrics and dashboards focusing on hospitalization rates, new infections and deaths, and all manner of data that gave people some tangible connection to a wide-reaching pandemic. However, public health and medical practitioners would say that analytics and data-driven decision making have been core to the health industry since even before the dawn of the computing age.
On a recent GovFuture podcast, Dr. Susan Gregurick, Associate Director for Data Science and Director of the Office of Data Science Strategy at the National Institutes of Health (NIH) shared insights and details on how the NIH is using advanced analytics to drive data-driven decision-making, as well as some of the unique challenges the NIH faces in leveraging advanced analytics in areas related to data privacy and security.
A far reaching plan for data
Dr. Gregurick shares that as part of her role, her office leads the implementation of the NIH strategic plan for data science which works to harness emerging opportunities and advance cutting-edge data science across the NIH’s 27 institutes and centers, focusing on activities such as data interoperability, platform interoperability, data accessibility, data standards and standardization and the reuse of data. They also support the establishment of policies and related privacy and ethics and data sovereignty policies as well as promoting the principles of diversity, equity, inclusivity and accessibility.
“This is such an exciting time to be in data science with the real significant advances in artificial intelligence and generative AI that we’ve just seen recently,” Dr. Susan Gregurick shared on the podcast. “AI and advanced analytics really does speed the discovery of science and for us, bringing treatment and cures to keep people healthy. So one of our policies and one of our priorities is the ethical use of advanced analytic technology like artificial intelligence.”
She further shared insights into a new program called the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program. “AIM-AHEAD is working with researchers and institutions across the entire country, to enhance the participation and the representation of researchers and communities in the development of AI models and also to improve their ability to take advantage of this emerging technology… AIM-AHEAD is focused on recruiting new students and new scholars, funding new cutting-edge programs and priorities and really making an impact in AI models and the AI community.”
Augmenting capabilities with the help of AI
Dr. Gregurick also shares that through the use of AI, the NIH is seeing “the analytic speedup of diagnostic and treatment capabilities. So just for example, not long ago, an infant that was born with a rare genetic disease, it would take a really long time to test, get their sequence sequence, annotate it and then try to figure out what their rare genetic disease might be. But recently with the advent of AI, we can now very quickly sequenced the entire genome of the infant compared against a number of variants that we have for over 13,000 genetic disorders. And in five minutes, actually pinpoint what that disorder might be and then increase the capacity to develop the therapeutics that that infant might need. And that’s a big time saving when you’re looking at small children and babies who are born with rare genetic disorders. So those are just some of the cutting-edge technologies that we’re working on both to enhance our capacity to use AI and also to really speed the care delivered to patients using AI.”
The increasing concerns of privacy and ethics related to health data
The use of private medical data always comes paired with concerns of data security, privacy, and ethics. In response to a question on what unique challenges the NIH faces in leveraging advanced analytics and dealing with those complex data sets, while also ensuring data privacy and security, Dr. Gregurick responds:
“For agencies such as mine, which deal with health data, we do have significant challenges with data privacy, as well as access to data. In order to take advantage of AI, researchers do need a significant amount of very good data. And that means that they need to access data across a number of repositories. Right now, NIH supports roughly 80 controlled access data repositories. These are data repositories that hold human data. They protect participant data privacy and security.
Previously, there’s a fairly complicated process for researchers to get access from these repositories. And they need to do this multiple times. It was quite duplicative and really quite onerous. So recently, we’ve standardized the way that researchers can gain access to controlled access data repositories. This is called Research Health Services, or RHS. RHS provides a single sign-on capability. Right now, we’re working with nine of our largest data systems, with many, many more in the process of adoption. And in this way by sharing credentialing systems across our data repositories, we’re standardized in the way that researchers log in and the way that we can track and log basically potential data breaches and data security issues.”
In addition to the GovFuture podcast interview, Dr. Susan Gregurick was a featured panelist at the GovFuture Forum DC event at George Mason University (GMU) where she shared additional insights into the use and adoption of AI as well as advanced analytics.
Disclosure: Ronald Schmelzer is an Executive Director at GovFuture.
Read the full article here
