The source of the common hospital-acquired infection known as C. diff can be hard to pin down in a busy, sprawling hospital, where patients might pick up the bug in countless locations.
Hospitals nationwide are eager to reduce C. diff infections. A few years ago, when the UCSF Medical Center set a priority to cut rates of the infection, the UCSF Health Informatics team pitched an unusual strategy: Digitally reconstructing each patient’s footsteps in the hospital.
The team realized that within each patient’s electronic health record (EHR) was detailed information about every room each patient had stepped into for every test. Using these digital breadcrumbs mined from the records, the team was able to trace a significant source of infection back to one CT scan machine.
EHRs—in many ways still in their adolescence since coming into widespread use just in the last decade—alternately have been viewed as a time-consuming burden to doctors and as a gateway to smarter, safer, and more accessible healthcare.
More and more, the promise of EHRs turning data into knowledge is beginning to bear fruit. Work like the C. diff case, recently published by assistant professor of medicine Sara Murray, MD, and collaborators in JAMA Internal Medicine, “is a brilliant example of how we can learn from data in the electronic health records,” said Robert Wachter, MD, professor and chair of UC San Francisco’s Department of Medicine.
The true power of EHRs may lie in places that haven’t been fully explored yet—in the vast troves of patient data that could be mined for precision medicine and the shifting workflow of the hospital as information travels faster and more freely.
So far, the most salient changes brought by EHRs are improving the storage and speeding the flow of information through the healthcare system. Gone are the shelves of paper medical records that used to line doctor’s offices, stuffed with documents that had to be sent by courier, mailed or faxed when needed.
Now EHRs allow for notes to be shared digitally between clinicians treating the same patient, and test results can be retrieved from the lab and prescriptions sent to the pharmacy instantaneously. EHRs have essentially eliminated the problems of misread handwriting and lost paper prescriptions.
Ideally, records would flow seamlessly from provider to provider, but one notable area of weakness for today’s EHRs is communication between systems, known as interoperability. The problem stems from different EHR companies—a handful dominate the market—building their own systems that don’t talk to one another.
A study by Julia Adler-Milstein, Ph.D., associate professor of medicine and director of the Center for Clinical Informatics and Improvement Research at UCSF, found that in 2015, more than half of hospitals nationwide did not have access to outside patient information. That leaves open the possibility that doctors could be treating patients without access to their full medical history—just the opposite of what EHRs were meant to do.
Streamlined access to a patient’s medical records only scratches the surface of EHRs’ potential. In years to come, doctors will base their decisions on not only a single patient’s comprehensive medical history, but the lessons learned from populations with similar problems.
When a surgeon recommends a procedure to a patient today, she or he may rely on personal experience, that of colleagues, and relatively small-scale studies published in academic journals. A surgeon of the future could ask an intelligent algorithm to analyze the outcomes of hundreds of similar surgeries that had been documented with EHRs.
As a step in that direction, UCSF is one of five UC Health systems that have joined an effort to integrate their EHRs, which comprise more than 15 million patient records, creating the largest collection among academic health centers to date. Led by UCSF’s Institute for Computational Health Sciences and headed by Atul Butte, MD, Ph.D., the project will not only smooth the exchange of information, but lay the groundwork for data-driven experiments that could lead to new drugs and more precise medical care.