At Stanford’s Big Data conference, healthcare and information technology professionals, executives and leaders discussed the advantages of big data to medicine and how expectations are tempered by privacy and security concerns.
Big data, that ever-growing trove of information gleaned from patient records, imaging tests, lab samples, clinical studies, insurance claims, wearable sensors and social media collected and analyzed by today’s advanced computers, has been hailed as the next big thing to revolutionize healthcare and medicine.
This was again the overall theme in Stanford’s second annual Big Data on Biomedicine conference held recently.
The event was attended by hundreds of doctors, data scientists, computer specialists, executives and leaders, and by thousands more online.
They engaged in panel sessions and listened to speeches of representatives from companies like Google, Intel and Genentech, institutions such as Stanford School of Medicine, Harvard Medical School and Oxford, and from government offices such as the White House and the National Institutes of Health.
“We're all here because we believe in the vast potential of technology, data and biomedicine to transform human health for the 21st century,”
Lloyd Minor, MD, dean of Stanford School of Medicine, said in a report.
Keynote speakers cited their experiences in harnessing big data and how it can uncover knowledge that impact healthcare today and in the future in many aspects.
Stanford assistant professor of biochemistry Julia Salzman, PhD talked about how her team used a computational pattern-recognition software that discovered circular RNA which can provide diagnostic clues to diseases such as cancer using a blood test.
“It's important to scrutinize the data that is traditionally thrown away in massive data analyses,”
Salzman was quoted in a San Francisco Chronicle report as saying.
“It presents huge new opportunities to make fundamental discoveries in biology and potentially inroads into understanding and monitoring diseases, but in order to do this, we need better quantitative and statistical methods.”
A representative from the U.S. Food and Drug Administration shared how the agency built a publicly accessible database holding the genomic sequences of more than 5,000 food-poisoning microbes such as Salmonella, and how the FDA is now using social media for surveillance of outbreaks.
The U.S. National Institutes of Health meanwhile announced that it is developing an online network where geneticists can share and discuss research studies.
Event host Stanford has allocated a third of the computing space in its own Stanford Research Computing Center for its School of Medicine, a sign of confidence that powerful computing technology can eventually lead to medical discoveries.
Many other event speakers also talked about how apps and sensors in wearable devices and smartphones now collect our personal data regarding diet, exercise, sleeping patterns, stress levels, and vital signs, and store information in the cloud.
While the possibilities to improve health seem apparent, big data may not be easily harnessed because of a number of concerns, a major one being the privacy concerns associated with sharing and storing personal health information.
According to a Stanford Daily article, David Glazer, director of engineering at Google, sounded optimistic that this may be overcome eventually, and claimed that
“when the information is valuable to the population at large, he expects people to opt into volunteering their personal data.”
The same report said that another speaker, Jim Davies, computer science professor from Oxford University, sees the initial step would be “to win patient trust by creating a suitable environment and encouraging education.”
Patients may be convinced further from their own personal experiences with the healthcare system, whether their electronic medical records, for instance, can help their doctors devise a better treatment plan for them.
Other than through increased willingness from patients, big data’s potential could be realized faster if interoperability can be achieved to allow for seamless sharing of health data that lead to better clinical outcomes.