This article highlights a recent conference held here at Stanford, Big Data in Precision Medicine. We highlight some key concepts gained from the conference, and the need to be aware of how big data is changing the healthcare field.
Big Data in Precision Health Conference
Since the advent of electronic health records (EHR), the health care industry has been drowning in patient data. There is an acronym that describes health care data well: “DRIP: Data Rich, Information Poor”. We have all this data for a patient, but it is near impossible to put all of it together with a detailed history to understand the underlying cause of the problem or even predict the length of stay. Additionally, with the advances in science and the understanding that every person is different, medical treatment can now be targeted to a specific person.
Recently, Stanford University hosted a 2-day annual conference entitled, The Big Data in Precision Health Conference. It brought together members of the tech industry, scientists, and health care providers to talk about the advances being made through partnerships between health care and tech. There were panels of doctors, pharmacists, data scientists, and computer scientists discussing how using machine learning is helping better identify, diagnose, and even predict clinical outcomes.
Jeff Dean, a Senior Fellow at Google, was a keynote speaker who shared some projects he and his team (Google Brain) are working on by partnering with different health systems. One of the projects discussed was a method of machine learning, called Deep Learning, being able to better predict length of stay, mortality, and readmissions vs the traditional clinical model with all the EHR data1. He also highlighted the variability with reading patient images due to the expertise and background of the physician reading them.
Nurses need to be aware of all the up and coming changes in the digital world as this will influence our practice. Also, we need to be mindful on how we can help influence the development of new technologies. Patricia Brennan who is a nurse and the Director of the National Library of Medicine was the lead author on a paper entitled, “Nursing Needs Big Data and Big Data Needs Nursing.” In that paper, she highlights why nurses need to participate in understanding big data and the roles nurses can play2.
Consider attending next year’s conference. You can go to their web page (http://bigdata.stanford.edu/) to stay up to date on next year’s conference. Additionally, on their website they have videos of previous presentations, and this year’s presentations will be up soon. If you want to learn more about machine learning, Stanford University has a free online course available on Coursera (https://www.coursera.org/).
- Rajkomar, A., Oren, E., Chen, K., Dai, A. M., Hajaj, N., Hardt, M., … & Sundberg, P. (2018). Scalable and accurate deep learning with electronic health records. NPJ Digital Medicine, 1(1), 18.
- Brennan, P. F., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship, 47(5), 477-484
Article By: Monique Bouvier