Ontology type: schema:ScholarlyArticle
2017-10
AUTHORSMichael Morris, Babak Saboury, Niketh Bandla, Christopher Toland, Christopher Meenan, Eliot Siegel, Jean Jeudy
ABSTRACTIn the post-PACS era, mammography is unique in adopting specialized ergonomic interfaces to improve efficiency in a high volume setting. Chest radiography is also a high volume area of radiology. The authors hypothesize that applying a novel interface for chest radiography interpretation and reporting could create high productivity while maintaining quality. A custom version of the ClearCanvas open source software, EzRad, was created with a workflow re-designed specifically for tuberculosis screening chest radiographs, which utilized standardized computer generated reports. The preliminary reports from 881,792 studies evaluated by radiology residents over a nine-year period were analyzed for productivity as RVU/FTE and compared to the finalized reports from a subspecialty attending chest radiologist for accuracy. Radiology residents were able to produce 7480 RVU/FTE per year in screening chest radiography productivity when using a custom interface at a large academic medical center with a miss rate of 0.1%. Sensitivity was 77% and specificity was 99.9%. An ergonomic user interface allowed high productivity in interpretation of chest radiography for tuberculosis screening while maintaining quality. More... »
PAGES589-594
http://scigraph.springernature.com/pub.10.1007/s10278-017-9952-y
DOIhttp://dx.doi.org/10.1007/s10278-017-9952-y
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1083524391
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/28154988
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information Systems",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Efficiency, Organizational",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Ergonomics",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Image Interpretation, Computer-Assisted",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Image Processing, Computer-Assisted",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Radiography, Thoracic",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Reproducibility of Results",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Sensitivity and Specificity",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Software",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Tuberculosis",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Workflow",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Baltimore Veteran\u2019s Affairs Medical Center, Baltimore, MD, USA",
"Mercy Medical Center, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Morris",
"givenName": "Michael",
"id": "sg:person.01356370111.96",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01356370111.96"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Baltimore Veteran\u2019s Affairs Medical Center, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Saboury",
"givenName": "Babak",
"id": "sg:person.01042766404.29",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042766404.29"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical Center",
"id": "https://www.grid.ac/institutes/grid.413036.3",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Bandla",
"givenName": "Niketh",
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Analytical Informatics, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Toland",
"givenName": "Christopher",
"id": "sg:person.01023567731.64",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01023567731.64"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Analytical Informatics, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Meenan",
"givenName": "Christopher",
"id": "sg:person.01212550757.86",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01212550757.86"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Baltimore Veteran\u2019s Affairs Medical Center, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Siegel",
"givenName": "Eliot",
"id": "sg:person.0734606617.87",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734606617.87"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Maryland Medical System",
"id": "https://www.grid.ac/institutes/grid.413038.d",
"name": [
"Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, 21201, Baltimore, MD, USA",
"Baltimore Veteran\u2019s Affairs Medical Center, Baltimore, MD, USA",
"University of Maryland Medical System, Baltimore, MD, USA"
],
"type": "Organization"
},
"familyName": "Jeudy",
"givenName": "Jean",
"id": "sg:person.01335240375.41",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01335240375.41"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1001/jama.1996.03540010041028",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003172442"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jacr.2004.06.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005820197"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1148/radiol.2522081895",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011175514"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jacr.2012.06.022",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012875235"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jacr.2014.09.005",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014868837"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1148/radiol.2523081992",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029458130"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.acra.2013.07.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038754940"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.acra.2005.05.015",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042551488"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1067/j.cpradiol.2015.09.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050414814"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/jama.276.1.39",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1054160025"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2214/ajr.178.3.1780563",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1069324571"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1074317468",
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1148/radiol.14141227",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1079004486"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1079013904",
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1148/radiology.209.2.9807581",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083343559"
],
"type": "CreativeWork"
}
],
"datePublished": "2017-10",
"datePublishedReg": "2017-10-01",
"description": "In the post-PACS era, mammography is unique in adopting specialized ergonomic interfaces to improve efficiency in a high volume setting. Chest radiography is also a high volume area of radiology. The authors hypothesize that applying a novel interface for chest radiography interpretation and reporting could create high productivity while maintaining quality. A custom version of the ClearCanvas open source software, EzRad, was created with a workflow re-designed specifically for tuberculosis screening chest radiographs, which utilized standardized computer generated reports. The preliminary reports from 881,792 studies evaluated by radiology residents over a nine-year period were analyzed for productivity as RVU/FTE and compared to the finalized reports from a subspecialty attending chest radiologist for accuracy. Radiology residents were able to produce 7480 RVU/FTE per year in screening chest radiography productivity when using a custom interface at a large academic medical center with a miss rate of 0.1%. Sensitivity was 77% and specificity was 99.9%. An ergonomic user interface allowed high productivity in interpretation of chest radiography for tuberculosis screening while maintaining quality.",
"genre": "research_article",
"id": "sg:pub.10.1007/s10278-017-9952-y",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1100894",
"issn": [
"0897-1889",
"1618-727X"
],
"name": "Journal of Digital Imaging",
"type": "Periodical"
},
{
"issueNumber": "5",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "30"
}
],
"name": "Computer-Aided Reporting of Chest Radiographs: Efficient and Effective Screening in the Value-Based Imaging Era",
"pagination": "589-594",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"6ef75e1122a9b6a7479bd298e1967caf2660382c7b6529a808c6a25099db660c"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"28154988"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"9100529"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s10278-017-9952-y"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1083524391"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s10278-017-9952-y",
"https://app.dimensions.ai/details/publication/pub.1083524391"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T10:00",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000347_0000000347/records_89816_00000002.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs10278-017-9952-y"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10278-017-9952-y'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10278-017-9952-y'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10278-017-9952-y'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10278-017-9952-y'
This table displays all metadata directly associated to this object as RDF triples.
204 TRIPLES
21 PREDICATES
55 URIs
32 LITERALS
20 BLANK NODES