An adverse event capture and management system for cancer studies

Abstract

BackgroundComprehensive capture of Adverse Events (AEs) is crucial for monitoring for side effects of a therapy while assessing efficacy. For cancer studies, the National Cancer Institute has developed the Common Terminology Criteria for Adverse Events (CTCAE) as a required standard for recording attributes and grading AEs. The AE assessments should be part of the Electronic Health Record (EHR) system; yet, due to patient-centric EHR design and implementation, many EHR's don't provide straightforward functions to assess ongoing AEs to indicate a resolution or a grade change for clinical trials.MethodsAt UAMS, we have implemented a standards-based Adverse Event Reporting System (AERS) that is integrated with the Epic EHR and other research systems to track new and existing AEs, including automated lab result grading in a regulatory compliant manner. Within a patient's chart, providers can launch AERS, which opens the patient's ongoing AEs as default and allows providers to assess (resolution/ongoing) existing AEs. In another tab, it allows providers to create a new AE. Also, we have separated symptoms from diagnoses in the CTCAE to minimize inaccurate designation of the clinical observations. Upon completion of assessments, a physician would submit the AEs to the EHR via a Health Level 7 (HL7) message and then to other systems utilizing a Representational State Transfer Web Service.ConclusionsAERS currently supports CTCAE version 3 and 4 with more than 65 cancer studies and 350 patients on those studies. This type of standard integrated into the EHR aids in research and data sharing in a compliant, efficient, and safe manner.

Using electronic medical record data to report laboratory adverse events

“…This study demonstrates that EMR‐based AE ascertainment at a single institution using an automated data extraction, cleaning and grading process dramatically improves the accuracy of AE laboratory ascertainment. Notably, the automated processing steps to remove potential laboratory errors, which were not previously reported by Lencioni et al () are crucial to ensuring accurate laboratory AE identification.…”

“…Finally, automated EMR‐based laboratory AE reporting may substantially decrease the variation in clinical trial AE reports (Thomas et al , ; Huynh‐Le et al , ; Lencioni et al , ). Many CTCAE definitions use “life‐threatening consequences” and a numerical cut‐off.…”

“…We and others have sought to improve AE reporting with automated data extraction from the electronic medical record (EMR) (Mandelblatt et al , ; Lencioni et al , ). Mandelblatt et al () ascertained AEs in breast cancer patients with an overall sensitivity of 89% (range 0–100%), but did not report positive predictive value (PPV).…”

“…Mandelblatt et al () ascertained AEs in breast cancer patients with an overall sensitivity of 89% (range 0–100%), but did not report positive predictive value (PPV). Lencioni et al () incorporated EMR AE capture in one hospital system to streamline AE collection, but did not provide a methodology for improving AE reporting on multi‐centre trials.…”

Efficacy and Tolerability of Solifenacin 5 mg Fixed Dose in Korean Children with Newly Diagnosed Idiopathic Overactive Bladder: a Multicenter Prospective Study

“…It has been proposed that the Korean version of the OABSS might offer clinicians a valid and reliable tool for the assessment of OAB symptoms in the Korean population (9). AEs were assessed using Common Terminology Criteria for Adverse Events (CTCAE) version 4 (10). …”