EHR medication lists are often inaccurate and incomplete, opening the door for adverse drug reactions, un-informed clinical decision-making, and poor medication monitoring, according to a new JAMA study.
Researchers from Vanderbilt University Medical Center, Cleveland Clinic, and Precera Bioscience assessed the difference between prescribed medications recorded in EHR medication lists compared to the drug concentrations for 263 frequently-prescribed medications found in patients’ blood.
The team performed a cross-sectional study of 1,346 patients in three different care settings. Patient cohorts included a group of 1,000 patients who had sent samples for routine clinical chemistry testing, 50 patients enrolled in a gastroenterology clinic, and 296 patients with hypertension who had sought care in an emergency department (ED).
Researchers tested a serum assay panel that detects 91% of small-molecule oral drug prescriptions for in a single blood sample.
Ultimately, researchers found 22 percent of medications used across all cohorts were not shown as prescribed in patients’ EHR medication lists.
“In addition, medications not included in electronic health record medication lists were detected and were more frequently associated with alerts for potential adverse drug reactions,” noted researchers in the report.
Among patients in the gastroenterology and ED cohorts, researchers found patients on average were using one medication not listed in their EHR. Furthermore, researchers found less than half of patients in the gastroenterology and ED cohorts were using the exact medications listed in their EHR medication lists after testing their blood.
“We evaluated prescription and detection data on an individual patient basis by determining the percentage of patients with any unexpected finding relative to the EHR medication list,” stated researchers.
“Electronic health record medication lists were classified as accurate if there were no prescribed but non-detected medications from the subset of 189 drugs used for assessing adherence and no DNP medications (excluding over-the-counter medications),” the team continued.
In the cohort of patients who had sent samples for routine testing, 43.5 percent had accurate EHR medication lists. Forty-four percent of patients in the gastroenterology cohort had accurate lists, and only 13.9 percent of patients in the ED cohort had accurate lists.
The top 10 percent of patients taking prescriptions not recorded in their EHR medication lists were using more than 3.5 unlisted medications per patient.
Researchers also assessed the frequency and severity of drug-drug interaction alerts among patients. About 32 percent of major or severe drug-drug interactions involved detected medications not listed in patient EHRs.
Overall, researchers suggested providers comprehensively test patients’ blood for medications to address patient medication adherence and reconcile inaccuracies in EHR medication lists.
“This novel approach of comprehensively comparing measured medication concentrations with patient medical records could be used to optimize medication efficacy and safety and tailor drug therapy,” researchers stated.
Accurately identifying and quantifying all medications a patient takes provides crucial information for treatment optimization.
“Collectively, we demonstrated that 63.0 percent of patients (848 of 1346) have a discrepancy between the medical record and detected medications, illustrating the extent to which adherence and medical record inaccuracies manifest at the patient level,” wrote researchers.
The high number of medications not listed in patient EHRs that have the potential to spur adverse drug reactions increases the likelihood providers may prescribe medications and make other clinical decisions with incomplete information. Ensuring providers are fully aware of all medications a patient may be taking is a matter of patient safety.
“Comprehensive medication monitoring has merit and will require further data comparing measured drug concentrations with outcomes to verify published reference ranges and future clinical decision support algorithms,” concluded researchers.