An adverse event capture and management system for cancer studies
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Comprehensive 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.
At 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.
AERS 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.
KeywordsElectronic Health Record Adverse Event Reporting System Academic Health Center Biomedical Informatics Electronic Case Report Form
List of abbreviations used
Adverse Event Reporting System
Cancer Automated Lab-based Adverse Event Grading Service
CLinicAl Research Administrator
Comprehensive Research Informatics Suite
Common Terminology Criteria for Adverse Events
Electronic Health Record
Health Level 7
International Classification of Diseases
University of Arkansas for Medical Sciences
Apache + MySQL + PHP + Perl.
Data collection in cancer research studies is vital to understand the possible side effects of medication, the medication's efficacy, and overall safety in patients. Collecting AEs has become problematic with the use of both data management systems and EHR to record and monitor the adverse events in the study population. From the time the clinician documents the encounter with the study participant to the data entry into the database, there are several potential sites for AEs to be duplicated, incompletely documented, or transcribed incorrectly.
The Food and Drug Administration's Code of Federal Regulations Title 21 Section 312.64 requires investigators to immediately report any event to the sponsor regardless of the relationship to the drug . When Belknap et al compared several nationwide cancer institutes looking at the quality of methods of adverse event reporting, they found zero of the 49 institutes "use a valid method for assessing causality," and 38 of the 49 are implicitly prompting global introspection by the investigator . Only one-third of the forms provided the domain of terms recommended by the Food and Drug Administration for the assessment of quality. Belknap et al also noted that an integration of taxonomy system to CTCAE could help amend some of the issues within adverse event reporting. They recommended that because of the familiarity of the oncologist to use CTCAE . The findings of Belknap reiterate the finding from a report in the Institute of Medicine on the national cancer clinical trials system. The report states that "the lack of a standard required data set leads to inconsistency in the data collected for cancer trials that can affect the quality of the study and limit cross-study comparisons." 
The study titled "Does error and adverse event reporting by physicians and nurses differ?" found that of all the events reported physicians only accounted for 1.1%, while reporting by nurses accounted for 45.3%. The study also found that physicians and nurses reported different types of events. Showing physicians more often reported events that "caused permanent harm, near death, or death of the patient" and nurses more often reported "events that caused no or temporary harm" . Having a system where the adverse events are collected systematically and well-documented within the patient's chart can improve the recognition, evaluation, and monitoring of all adverse events by the entire patient care team [12, 13].
A recent report compiled by the United States Department of Health and Human Services' Inspector General identifed very common issues on AE reporting citing the incomplete collection and information system related issues . Although Epic has the highest EHR marketshare , our cancer clinics have determined that AE capture and reporting features of Epic are not as functional as AERS and are more difficult to track ongoing adverse events. Another alternative could be to use some other existing AE capture platforms; however, to our knowledge, there is no available AE capture system in the public domain. caBIG Adverse Event Reporting System (caAERS)  has been developed by the National Cancer Institute; however, it is a reporting system to generate necessary AE reports once an AE is captured and it is not a AE capturing platform. Due to those constraints, and since academic health centers have their own diverse IT infrastructructure, AERS was created to improve the efficacy of AE reporting at UAMS. The AERS system integrates with the EHR allowing the information to be documented within the patient encounter note in the legal medical records. AERS is interfaced to a research database as well and eliminates the need of the clinical coordinator to retype AEs, thus preventing transcription errors. Having the AE database and the EHR integrated, the AERS system prompts the clinician to address the ongoing AEs and note any changes. AERS will also allow clinicians to address new AEs. The clinician will be prompted to address all attributes regarding the ongoing or new AEs to ensure the AEs are documented completely. The AERS system has drastically improved AE reporting efficacy and has helped eliminate unnecessary data queries regarding data documentation by improving the data collection process. By decreasing the AE queries, the efficiency and accuracy of clinical trial management has improved.
AERS was implemented as part of the Comprehensive Research Informatics Suite (CRIS) at UAMS and interfaced with the Epic EHR to provide easy integration to clinic workflows and properly document AEs in a patient's chart. As majority of academic health centers use Epic EHR , we believe, integration schema defined in this paper is easily adoptable. For non-Epic centers, the approach is modeled after the way an external transcription service would work, so it is possible for non-Epic EHR customers to take advantage of the AERS.
All applications are integrated into a portal that allows a single point of access with a registered UAMS username and password. All CRIS applications reside on a cluster server with failover capability behind the UAMS firewall, and thus have the benefit of high security, fire protection, and routine backup. CRIS modules are widely adopted across UAMS, and currently enhancing the suite to support their vanguard work in translating genomics and proteomics research into clinical practice.
Symptoms and diagnosis
Current regulations require AEs to be captured and reported in a timely and as accurate as possible manner [1, 7]. In order to increase the compliance, a user-friendly system is required that demands a bidirectional communication with the Epic EHR since Epic is the starting point for a patient encounter (i.e. visit).
In order to pull complete and accurate patient demographics of those registered into a study, we developed an interface to the caBIG Central Clinical Participant Registry (C3PR), which serves as the UAMS' research participant registry. C3PR also houses study personnel who have been approved to have access to participants' records and AERS authorizes the authenticated users and provides access to study personnel listed in C3PR only. CLinicAl Research Administrator (CLARA) is the UAMS' Institutional Review Board protocol management system that keeps study metadata (e.g. name, ID etc.) as well as the investigational drugs and devices if it is an interventional study. AERS pulls drug(s) or device(s) information from CLARA so that a clinican may properly associate any AE to the correct agent if AE is related.
There are two ways to create AEs in AERS: 1) Lab AEs that are auto generated based on the study participants' lab results (see section d;toxicity grading) and 2) office visits that are created by authorized users who assess any new or worsening symptom a patient may have due to study treatment (or pre-exisiting). In our workflow, a study nurse assesses the ongoing AEs and enters the new symptoms to make the system ready for the provider to finalize the assessment. There are small human interface reminders such as displaying a red frame for ongoing AEs that are not assessed during the visit yet to ensure all the ongoing AEs are designated as either ongoing or resolved.
Upon login to AERS, a physician will be provided list of awaiting assessments in a sidebar for easy access. The system sends email reminders to the physicians if AEs have not been finalized within 24 hours. The email reminders are very useful in case of lab-based AEs since lab results becomes available after an office visit and associated documentation is completed.
Architecture of AERS
Medical record integration and Epic interfaces
Epic supports Integrating the Healthcare Enterprise's Retrieve Process for Execution standard to enable providers to access research protocol with incoming messages from clinical research systems. Retrieve Process for Execution is one of a set of profiles that create interoperability between EHRs and clinical research systems. The study definition and the registration information are being sent to Epic via Retrieve Process for Execution from CRIS for all of the clinical research studies that are being conducted at UAMS' clinical enterprise. In addition, Epic has the bridge interfaces to allow incoming HL7 messages such as transcriptions. We utilize the research interface for AE documents, including lab-based AEs that are being generated by AERS and sent to as HL7 via the MirthConnect.
While adding a new AE, selecting the appropriate customer serial number (i.e. encounter) from the dropdown list is crucial to properly import incoming documents into Epic. This allows the system to route the AERS note to the appropriate encounter within Epic. Then the "complete AERS button and submit" buttons are selected.
Lab-based AEs are filed as separate documents in Epic and automatically routed to providers' in basket for signature. They are then filed as Lab Based Adverse Event note types in Epic.
Results and discussion
Improvements resulted by the AERS implementation.
Area of improvement
Time spend for adverse event clarification between the clinical trial office staff and providers
Estimated 60% less inquiries to clinics for clarification
All ongoing AEs are being assessed every visit
The number of sponsor queries has decreased, which reduced the time needed to identify and complete missed and incomplete assessments.
Complete and accurate reporting of AEs
Staff spends less time to compile data from systems to complete needed attributes of an AE report. This allows more thorough and accurate reporting.
Timely reporting of AEs
As the complete and accurate AE report is easily available, the staff reports those in a timely manner as expected by the sponsors and regulatory bodies.
Complete reporting of the lab related AEs
Before AERS, the lab AE reporting was paper based with some potential missed lab-based AEs. Each lab AE had to be signed by the provider with proper association. After AERS, the research staff estimates that they are reporting 75% more lab-based AEs and providers just make the clinical significance determination and submit electronically.
Time saving and efficiency due to less number of queries.
We analyzed two studies and both of which have 10 subjects enrolled and the same investigational product, the time frame is from April 2008 to the present date. A) Study A that doesn't use AERS, had 106 queries out of which 73 were AE related (~69%). B) Study B that uses AERS, had 169 queries out of which 36 were AE related (27%)
The reorganization of symptoms versus diagnoses and the ability to see ongoing AEs at the time of entering a possible new AE in AERS system decreases the chances of documenting the same AE twice under different medical synonyms. With the ability to place the AERS documentation in the encounter note, clinicians have an option to use it as the documentation for the review of symptoms section of the office visit. This eliminates descrepancies and the use of medical synonyms for the same event, which requires clarification in the note and queries to clarify the correct information. The combination of AERS with our workflow has addressed the discrepancies noted between nursing and physician assessments since the AEs collected by all healthcare team members are assessed at the same time with the same criteria, providing consistency in reporting and reducing global introspection with regard to assessing AEs. The feature that grades lab results and imports that into AERS for final assessment and attribution has saved much time and effort on the part of the clinicians, research coordinators and monitors. The elimination of transcription has reduced errors as well.
The design of the AERS system allows multiple sites to use the system for investigator initiated trials, thus providing the same consistent reporting, accurate data collection and improved efficacy of AE. With more accurate AE reporting we will be able to improve accuracy and reduce time, thereby ultimately leading to improved patient safety.
The AERS system, which is integrated globally into cancer clinical trials, improves the efficacy and speed of AE reporting and promotes patient safety. The AERS system provides a platform to globally standardize AE reporting, ensuring consistent reporting, and will increase the efficiency of the clinical trial staff. This has been accomplished through the flexibility allowed by the software design with innovative integration of the open-source tools and the ability to import the data into the commercial EHR documentation. The flexible design may be enhanced in the future to allow patient-reported events, broadening the data collection further. We have used open-source tools and systems and the source code is available at https://github.com/vickiechen/AERS
We would like to thank UAMS' IT Clinical Systems and the Epic's interface team for their help and expertise during the implementation of the EHR integration. We also thank Susan Van Dusen for proof-reading and edits.
Publication of this work was partly supported by the Winthrop P. Rockefeller Cancer Institute and Award UL1TR000039 from the National Center for Advancing Translational Sciences.
This article has been published as part of BMC Bioinformatics Volume 16 Supplement 13, 2015: Proceedings of the 12th Annual MCBIOS Conference. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcbioinformatics/supplements/16/S13.
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