Assessment of the Frequency, Phenotypes, and Outcomes of Acute Liver Injury Associated with Amoxicillin/Clavulanate in 1.4 Million Patients in the Veterans Health Administration.

INTRODUCTION: Drug-induced liver injury is a significant health issue, yet the exposure-based incidence remains to be characterized. OBJECTIVE: We aimed to assess the frequency, phenotypes, and outcomes of acute liver injury associated with amoxicillin/clavulanate using a large electronic health record system. METHODS: Using the Veterans Health Administration electronic health record system, we developed the framework to identify unexplained acute liver injury, defined by alanine aminotransferase and/or alkaline phosphatase elevation temporally linked to prescription records of amoxicillin/clavulanate, a major culprit of clinically significant drug-induced liver injury, excluding other competing causes. The population was subcategorized by pre-existing liver conditions and inpatient status at the time of exposure for the analysis. RESULTS: Among 1,445,171 amoxicillin/clavulanate first exposures in unique individuals [92% men; mean age (standard deviation): 59 (15) years], 6476 (incidence: 0.448%) acute liver injuries were identified. Of these, 4427 (65%) had alternative causes, yielding 2249 (incidence: 0.156%) with unexplained acute liver injuries. The incidence of unexplained acute liver injury was lowest in outpatients without underlying liver disease (0.067%) and highest in inpatients with pre-existing liver conditions (0.719%). Older age, male sex, and American Indian or Alaska Native (vs White) were associated with a higher incidence of unexplained acute liver injury. Cholestatic injury affected 74%, exhibiting a higher frequency with advanced age, inpatient exposure, and pre-existing liver conditions. Hepatocellular injury with bilirubin elevation affected 0.003%, with a higher risk at age >45 years. During a 12-month follow-up, patients with unexplained acute liver injury had a higher adjusted overall mortality risk than those without evident acute liver injury. CONCLUSIONS: This framework identifies unexplained acute liver injury following drug exposure in large electronic health record datasets. After validating in other systems, this framework can aid in deducing drug-induced liver injury in the general patient population and regulatory decision making to promote drug safety and public health.

Near Real Time EHR Data Utilization in a Clinical Study.

Extraction and use of Electronic Health Record (EHR) data is common in retrospective observational studies. However, electronic extraction and use of EHR data is rare during longitudinal prospective studies. One of the reasons is the amount of processing needed to assess data quality and assure consistency in meaning and format across multiple investigational sites. We report a case study of and lessons learned from acquisition and processing of EHR data in an ongoing basis during a clinical study.

Use of RxNorm and NDF-RT to normalize and characterize participant-reported medications in an i2b2-based research repository.

The MURDOCK Study is longitudinal, large-scale epidemiological study for which participants' medication use is collected as free text. In order to maximize utility of drug data, while minimizing cost due to manual expert intervention, we have developed a generalizable approach to automatically coding medication data using RxNorm and NDF-RT and their associated application program interfaces (APIs). Of 130,273 entries, we were able to accurately map 122,523 (94%) to RxNorm concepts, and 106,135 (85%) of those drug concepts to nodes under the Drug by VA Class branch of NDF-RT. This approach has enabled use of drug data in combination with other complementary information for cohort identification within an i2b2-based participant registry. The method may be generalized to other projects requiring coding of medication data from free-text.