Cargando…

How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology

In a real world search, it can be important to keep ‘an eye out’ for items of interest that are not the primary subject of the search. For instance, you might look for the exit sign on the freeway, but you should also respond to the armadillo crossing the road. In medicine, these items are known as...

Descripción completa

Detalles Bibliográficos
Autores principales: Wolfe, Jeremy M., Alaoui Soce, Abla, Schill, Hayden M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569644/
https://www.ncbi.nlm.nih.gov/pubmed/28890920
http://dx.doi.org/10.1186/s41235-017-0072-5
_version_ 1783259034280787968
author Wolfe, Jeremy M.
Alaoui Soce, Abla
Schill, Hayden M.
author_facet Wolfe, Jeremy M.
Alaoui Soce, Abla
Schill, Hayden M.
author_sort Wolfe, Jeremy M.
collection PubMed
description In a real world search, it can be important to keep ‘an eye out’ for items of interest that are not the primary subject of the search. For instance, you might look for the exit sign on the freeway, but you should also respond to the armadillo crossing the road. In medicine, these items are known as “incidental findings,” findings of possible clinical significance that were not the main object of search. These errors (e.g., missing a broken rib while looking for pneumonia) have medical consequences for the patient and potential legal consequences for the physician. Here we report three experiments intended to develop a ‘model system’ for incidental findings – a paradigm that could be used in the lab to develop strategies to reduce incidental finding errors in the clinic. All the experiments involve ‘hybrid’ visual search for any of several targets held in memory. In this ‘mixed hybrid search task,’ observers search for any of three specific targets (e.g., this rabbit, this truck, and this spoon) and three categorical targets (e.g., masks, furniture, and plants). The hypothesis is that the specific items are like the specific goals of a real world search and the categorical targets are like the less well-defined incidental findings that might be present and that should be reported. In all these experiments, varying target prevalence, number of targets, etc., the categorical targets are missed at a much higher rate than the specific targets. This paradigm shows promise as a model of the incidental finding problem.
format Online
Article
Text
id pubmed-5569644
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-55696442017-09-07 How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology Wolfe, Jeremy M. Alaoui Soce, Abla Schill, Hayden M. Cogn Res Princ Implic Original Article In a real world search, it can be important to keep ‘an eye out’ for items of interest that are not the primary subject of the search. For instance, you might look for the exit sign on the freeway, but you should also respond to the armadillo crossing the road. In medicine, these items are known as “incidental findings,” findings of possible clinical significance that were not the main object of search. These errors (e.g., missing a broken rib while looking for pneumonia) have medical consequences for the patient and potential legal consequences for the physician. Here we report three experiments intended to develop a ‘model system’ for incidental findings – a paradigm that could be used in the lab to develop strategies to reduce incidental finding errors in the clinic. All the experiments involve ‘hybrid’ visual search for any of several targets held in memory. In this ‘mixed hybrid search task,’ observers search for any of three specific targets (e.g., this rabbit, this truck, and this spoon) and three categorical targets (e.g., masks, furniture, and plants). The hypothesis is that the specific items are like the specific goals of a real world search and the categorical targets are like the less well-defined incidental findings that might be present and that should be reported. In all these experiments, varying target prevalence, number of targets, etc., the categorical targets are missed at a much higher rate than the specific targets. This paradigm shows promise as a model of the incidental finding problem. Springer International Publishing 2017-08-23 /pmc/articles/PMC5569644/ /pubmed/28890920 http://dx.doi.org/10.1186/s41235-017-0072-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Wolfe, Jeremy M.
Alaoui Soce, Abla
Schill, Hayden M.
How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title_full How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title_fullStr How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title_full_unstemmed How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title_short How did I miss that? Developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
title_sort how did i miss that? developing mixed hybrid visual search as a ‘model system’ for incidental finding errors in radiology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569644/
https://www.ncbi.nlm.nih.gov/pubmed/28890920
http://dx.doi.org/10.1186/s41235-017-0072-5
work_keys_str_mv AT wolfejeremym howdidimissthatdevelopingmixedhybridvisualsearchasamodelsystemforincidentalfindingerrorsinradiology
AT alaouisoceabla howdidimissthatdevelopingmixedhybridvisualsearchasamodelsystemforincidentalfindingerrorsinradiology
AT schillhaydenm howdidimissthatdevelopingmixedhybridvisualsearchasamodelsystemforincidentalfindingerrorsinradiology