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Real-Time Data Visualization of Clinical Workflows to Improve Patient Care

Real-Time Data Visualization of Clinical Workflows to Improve Patient Care

May/June 2018

Clinicians delve into electronic medical records hundreds of times a day to know whether a patient in the hospital has had certain tests, seen a particular specialist or received other care. To transform this practice, a team participating in the Technology Innovation Center’s Hexcite fellowship is developing a system that combines data from various sources to create a visual representation of a patient’s care in a single snapshot.

“We want a simple way for everyone to know what’s going on with a patient,” says Simon Mathews, clinical lead on the project, who is assistant professor of medicine and assistant director of the Armstrong Institute for Patient Safety and Quality at Johns Hopkins Bayview Medical Center. “This includes things like a patient’s labs, imaging, consults, medication, evaluations and procedures.”

Mathews is working with Vanessa Alphonse, who leads a team of experts at the Johns Hopkins University Applied Physics Lab (APL), to use existing APL technology to integrate data sources from across the hospital. So far, they have identified the individual data elements that comprise common clinical workflows and are working to integrate them in novel ways.

“With so much information during a hospital stay, there’s a huge potential for things to get lost along the way,” says Mathews. “By using this technology to communicate information automatically, it could prevent harm to patients, enable better care, increase patient satisfaction, avoid redundant testing and increase efficiencies overall.”

Once the technology is validated, the team will focus on the best way to display the data from numerous sources. Ultimately, Mathews envisions three versions to communicate patients’ status to three different groups: clinicians, patients and administrators.

A future application involves using the data elements collected to create a discharge summary automatically. Currently, this is a painstaking manual process.

“A clinician must scour the entire medical chart to see what happened longitudinally over the patient’s hospitalization to compile the discharge summary,” says Mathews. “We hope to tell the digital story of a patient’s hospitalization using the orders and other electronic data inputs.”

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