Proposal of a New Adverse Event Classification by the Society of Interventional Radiology Standards of Practice Committee

To develop a new adverse event (AE) classification for the interventional radiology (IR) procedures and evaluate its clinical, research, and educational value compared with the existing Society of Interventional Radiology (SIR) classification via an SIR member survey. A new AE classification was dev...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of vascular and interventional radiology 2017-10, Vol.28 (10), p.1432-1437.e3
Main Authors:	Khalilzadeh, Omid, Baerlocher, Mark O., Shyn, Paul B., Connolly, Bairbre L., Devane, A. Michael, Morris, Christopher S., Cohen, Alan M., Midia, Mehran, Thornton, Raymond H., Gross, Kathleen, Caplin, Drew M., Aeron, Gunjan, Misra, Sanjay, Patel, Nilesh H., Walker, T. Gregory, Martinez-Salazar, Gloria, Silberzweig, James E., Nikolic, Boris
Format:	Article
Language:	eng
Online Access:	Request full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	To develop a new adverse event (AE) classification for the interventional radiology (IR) procedures and evaluate its clinical, research, and educational value compared with the existing Society of Interventional Radiology (SIR) classification via an SIR member survey. A new AE classification was developed by members of the Standards of Practice Committee of the SIR. Subsequently, a survey was created by a group of 18 members from the SIR Standards of Practice Committee and Service Lines. Twelve clinical AE case scenarios were generated that encompassed a broad spectrum of IR procedures and potential AEs. Survey questions were designed to evaluate the following domains: educational and research values, accountability for intraprocedural challenges, consistency of AE reporting, unambiguity, and potential for incorporation into existing quality-assurance framework. For each AE scenario, the survey participants were instructed to answer questions about the proposed and existing SIR classifications. SIR members were invited via online survey links, and 68 members participated among 140 surveyed. Answers on new and existing classifications were evaluated and compared statistically. Overall comparison between the two surveys was performed by generalized linear modeling. The proposed AE classification received superior evaluations in terms of consistency of reporting (P < .05) and potential for incorporation into existing quality-assurance framework (P < .05). Respondents gave a higher overall rating to the educational and research value of the new compared with the existing classification (P < .05). This study proposed an AE classification system that outperformed the existing SIR classification in the studied domains.
ISSN:	1051-0443 1535-7732