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An adverse event capture and management system for cancer studies

BACKGROUND: 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...

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Autores principales: Lencioni, Alex, Hutchins, Laura, Annis, Sandy, Chen, Wanchi, Ermisoglu, Emre, Feng, Zhidan, Mack, Karen, Simpson, Kacie, Lane, Cheryl, Topaloglu, Umit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4597098/
https://www.ncbi.nlm.nih.gov/pubmed/26424052
http://dx.doi.org/10.1186/1471-2105-16-S13-S6
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author Lencioni, Alex
Hutchins, Laura
Annis, Sandy
Chen, Wanchi
Ermisoglu, Emre
Feng, Zhidan
Mack, Karen
Simpson, Kacie
Lane, Cheryl
Topaloglu, Umit
author_facet Lencioni, Alex
Hutchins, Laura
Annis, Sandy
Chen, Wanchi
Ermisoglu, Emre
Feng, Zhidan
Mack, Karen
Simpson, Kacie
Lane, Cheryl
Topaloglu, Umit
author_sort Lencioni, Alex
collection PubMed
description BACKGROUND: 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. METHODS: 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. CONCLUSIONS: 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.
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spelling pubmed-45970982015-10-08 An adverse event capture and management system for cancer studies Lencioni, Alex Hutchins, Laura Annis, Sandy Chen, Wanchi Ermisoglu, Emre Feng, Zhidan Mack, Karen Simpson, Kacie Lane, Cheryl Topaloglu, Umit BMC Bioinformatics Proceedings BACKGROUND: 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. METHODS: 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. CONCLUSIONS: 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. BioMed Central 2015-09-25 /pmc/articles/PMC4597098/ /pubmed/26424052 http://dx.doi.org/10.1186/1471-2105-16-S13-S6 Text en Copyright © 2015 Lencioni et al. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Lencioni, Alex
Hutchins, Laura
Annis, Sandy
Chen, Wanchi
Ermisoglu, Emre
Feng, Zhidan
Mack, Karen
Simpson, Kacie
Lane, Cheryl
Topaloglu, Umit
An adverse event capture and management system for cancer studies
title An adverse event capture and management system for cancer studies
title_full An adverse event capture and management system for cancer studies
title_fullStr An adverse event capture and management system for cancer studies
title_full_unstemmed An adverse event capture and management system for cancer studies
title_short An adverse event capture and management system for cancer studies
title_sort adverse event capture and management system for cancer studies
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4597098/
https://www.ncbi.nlm.nih.gov/pubmed/26424052
http://dx.doi.org/10.1186/1471-2105-16-S13-S6
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