Ask the EHR: Using data for real-time treatment decisions

November 23, 2011

Here’s a novel use of electronic health records: Using the technology to provide an “electronic cohort” that allows you to evaluate a course of treatment on a real-time basis. Usually, physicians rely on randomized, controlled trials, when possible, and turn to expert opinion when necessary. But what if experts aren't available or testing is inconclusive? Find out how a medical team used a quick analysis of an EHR database to determine treatment of a pediatric patient with systemic lupus erythematosus complicated by nephritic-range proteinuria, antiphospholipid antibodies, and pancreatitis.

Here’s a novel use of electronic medical records (EHRs): Using the technology to provide an “electronic cohort” that allows you to evaluate a course of treatment on a real-time basis.

Usually, physicians rely on randomized, controlled trials, when possible, and turn to expert opinion when necessary. But what if that experts aren’t available or testing is inconclusive?

An article in the New England Journal of Medicine demonstrates how a quick analysis of an EHR database can guide clinical decision-making in the absence of published studies or even anecdotal evidence. The perspective piece by Jennifer Frankovich, MD, and colleagues provides a new answer to the question: “What should we do when there aren’t even meager data available and we don’t have a single anecdote on which to draw?”

A 13-year-old girl presented to pediatricians at Stanford University Medical Center with systemic lupus erythematosus (SLE) complicated by nephritic-range proteinuria, antiphospholipid antibodies, and pancreatitis. Concerned about risk factors for thrombosis, the medical team wondered whether it should start the patient on an anticoagulant, which is not standard treatment for children with SLE. “However, we were unable to find studies pertaining to anticoagulation in our patient’s situation and were therefore reluctant to pursue that course, give the risk of bleeding,” Frankovich wrote.

A survey of colleagues produced no consensus or relevant anecdotes, so the team turned to data captured in Stanford’s EHR and research data warehouse. Using a platform called the Stanford Translational Research Integrated Database Environment, or STRIDE, a clinician reviewed data on an “electronic cohort” of pediatric patients with SLE cared for by the division between October 2004 and July 2009. Finding that 10 of the 98 patients in the cohort developed thrombosis while acutely ill, and that patients with nephrotic-range proteinuria and pancreatitis had significantly higher risk of thrombosis, the team decided to initiate anticoagulant therapy within 24 hours of admission. The automated cohort review took less than 4 hours.

As the authors note, this case “illustrates a novel process that is likely to become much more standard with the widespread adoption of [EHRs] and more sophisticated informatics tools.” The ability to turn to data available in institutional EHRs to inform real-time clinical decisions on patient care can fill a critical gap in knowledge. “The rapid electronic chart review and analysis were not only feasible but also more helpful and accurate than physician recollection and pooled colleague opinion,” said the authors.

More widespread adoption of EHRs and development of more sophisticated tools for data analysis will make this data-driven approach to healthcare increasingly available to clinicians and “help physicians learn from every patient at every visit and close the feedback loop for clinical decision making in real time,” the authors said.

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