“We have EHRs in place. There are tremendous amounts of data available now. It’s time to innovate the data and make it meaningful,” says Natalie Pageler, M.D., a critical care physician and Stanford Children’s chief medical information officer.

The hospital has custom-built several web-integrated clinical decision support tools that use data from the EHR to drive analytics that produce and display suggested courses of action given the patient's situation.

For instance, the hospital has developed a tool that seeks to prevent high bilirubin levels in premature infants. The clinician clicks on the tool, sends the patient’s age in hours and bilirubin levels to the website, and the tool recommends which clinical move to take for that particular baby. Moreover, unlike bilirubin treatment for full-term babies, bilirubin treatment for premature infants is still being studied; the clinical decision support tool also collects the data input and provides feedback so that Stanford can create treatment protocols.

“It’s the concept of a learning health system,” says Pageler.

Stanford also has created a clinical decision support tool for the dosing of vancomycin, an antibiotic with toxicity and a narrow therapeutic window. “In children, dosing can often be a challenge. So the tool takes the patient’s specific information, like, age, weight and drug history, uses analytics and comes up with a recommended dosage strategy. We continually update the model and learn from that so we can fine tune the protocol,” she says.

The hospital is working on an app that would help to determine the timing of surgery for a form of complex heart disease by uploading patient data from the patient’s home, reducing the need for hospital visits.

Pageler says that Stanford Children’s is well-situated to be on the forefront of these innovations, because it has several clinical informatics experts on staff who bridge the gap between medicine and technology. The hospital also operates a fellowship program in clinical informatics and is located in Silicon Valley, which enables it to work with area technology companies.  

The approach is "cutting edge, using analytics to be more personalized," Pageler says. "This is where [clinical decision support] is going.”