I really enjoyed this piece, by Barb Darrow, about the development of healthcare-related data management at the University Pittsburgh Medical Center (UPMC) for a number of reasons. First of all, as the article explains, UPMC is a leader in the area and is doing some really interesting things! Secondly, I always enjoy a good story about the economy of Pittsburgh, since it represents one of the best cases (the best case?) of transforming a US rust belt city into a 21st century City (Health care and robotics are among the key fields relevant to that success.). Finally, and most significantly, the issues raised in the article demonstrate that mastering new levels of data management do not lead to ease and simplicity but rather, to even greater opportunities and challenges.
In the case, of UPMC, getting a head start on developing Electronic Medical Records has led, first of all, to the challenge of coordinating independent systems across specialties. Being able to manage enormous amounts of granular data, and to understand how to deploy that data, is one of the frontiers beyond the systems coordination step:
Doctors now try to take a more holistic view of their patients, and that requires the ability to pull together data from different sources. Imaging data is separate from surgery notes, which is separate from pharmacy data.
“If we look at big data, the idea is how to interconnect multiple points of data across the broad, biological continuum,” Shrestha said. “If the patient is diabetic, you don’t just see an endocrinologist looking at the liver in terms of liver function tests or any scans but across the biological spectrum of organs and then down to a cellular level. We look at pathology slides, reports on molecular imaging and down to the genomic levels.”
Darrow explains that data can be broken down into three buckets: imaging data, which accounts for close to 50% of UPMC’s digital information; databases, which account for about 10%; and unstructured information, such as “postoperative notes, radiology reports, discharge summaries,” which accounts for the remaining 40%. The piece goes on to describe some of the specific technologies that are being used to address these various categories and concludes by pointing to another, even further frontier: the integrated management of pathology reports.
Big data, as the article in which I found the above reference would argue, is here to stay. The more we know, the more we that will become knowable. Personally, I find the challenge daunting