How to Use EHRs to Reduce Dangerous Drug-Drug Interactions

By Eric Wicklund

New research out of the Regenstrief Institute gives health system executives specific recommendations on how to use EHRs to reduce dangerous drug-drug interactions.

“Drug-drug interactions are very common, more common than a lot of people outside the healthcare system expect,” Michael Weiner, MD, MPH, a researcher with the US Department of Veterans Affairs, Regenstrief Institute, and Indiana University School of Medicine and senior author of the study, said in a press release. “In the US, these interactions lead to hundreds of thousands of hospitalizations in any given year at an enormous cost. Most of these drug interactions are preventable.”

With the advent of EHRs and digital health technology, health systems are looking to reduce those interactions by pinpointing when they can occur and giving clinicians on-demand access to information to prevent them. But that technology depends on understanding how clinicians prescribe drugs and how they look for dangerous interactions.

“This study was needed because we previously didn’t have a great understanding of how clinicians actually make decisions in assessing these interactions,” Weiner said. “No one had really taken apart the thinking process step-by-step to understand it from the beginning to the end. There’s a patient, there’s a drug and another drug. There is now a potential interaction. There’s been a decision about how to resolve it following an assessment and then a resolution process. Understanding all this is very important if we are hoping to design improvements to the medical system that enhance patient safety.”

The study, recently published in BMJ Open, identified 19 information cues used by clinicians to manage drug-drug interactions, including information on the potential severity of a drug reaction, side-effects, a patient’s expected duration of exposure to an interaction, patient-specific conditions, a patient’s need for those drugs, and the characteristics of safer medications. Using that list, Weiner and his colleagues developed recommendations for designing alerts through the EHR.

They are:

  • Provide information on the expected range of timing of potential drug-drug interaction effects (days, weeks, months, or years).
  • Give clinicians a platform to review multiple electronic drug-drug interaction reference sources directly from the alert, side-by-side.
  • Leverage data analytics to populate drug-drug interaction alerts with “smart” displays of alternative drugs that align with three criteria used by clinicians.
  • Provide recommendations on the alert along with associated patient characteristics (for example, “monitor, if patient indicates willingness and capability of measuring blood pressure daily”).

Alissa Russ-Jara, PhD, a researcher at the Purdue University College of Pharmacy and US Department of Veterans Affairs, Regenstrief Institute affiliated scientist, and the study’s lead author, said the research highlighted the fact that no two clinicians use the same protocols in assessing drug-drug interactions.

“We expect our findings can improve the design and usability of drug-drug interaction alerts for clinicians, and so they can more effectively aid patient safety,” she added. “Our study focused on clinical decision-making, regardless of whether the clinician was warned by an alert or not, so our findings have implications for clinicians, informatics leaders, and patients, and for any EHR system.”

Eric Wicklund is the associate content manager and senior editor for Innovation, Technology, Telehealth, Supply Chain and Pharma for HealthLeaders.