A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-10

AUTHORS

Monica Sapo, Shaozhi Wu, Shadnaz Asgari, Norma McNair, Farzad Buxey, Neil Martin, Xiao Hu

ABSTRACT

OBJECTIVE: (1) To investigate if there exist any discrepancies between the values of vital signs charted by nurses and those recorded by bedside monitors for a group of patients admitted for neurocritical care. (2) To investigate possible interpretations of discrepancies by exploring information in the alarm messages and the raw waveform data from monitors. METHODS: Each charted vital sign value was paired with a corresponding value from data collected by an archival program of bedside monitors such that the automatically archived data preceded the charted data and had minimal time lag to the charted value. Next, the absolute differences between the paired values were taken as the discrepancy between charted and automatically-collected data. Archived alarm messages were searched for technical alarms of sensor/lead failure types. Additionally, 7-min waveform data around the place of large discrepancy were analyzed using signal abnormality indices (SAI) for quantifying the quality of recorded signals. RESULTS: About 31,145 pairs of systolic blood pressure (BP-S) and 67,097 pairs of SpO(2) were investigated. Seven and a half percent of systolic blood pressure pairs had a discrepancy greater than 20 mmHg and less than one percent of the SpO2 pairs had a discrepancy greater than 10. We could not find any technical alarms from the monitors that could explain the large difference. However, SAI calculated for the waveforms associated with this group of cases was significantly larger than the SAI values calculated for the control waveform data of the same patients with small discrepancies. CONCLUSION: Charted vital signs reflect in large the raw data as reported by bedside monitors. Poor signal quality could partially explain the existence of cases of large discrepancies. More... »

PAGES

263-271

References to SciGraph publications

  • 1994-05. Data quality of bedside monitoring in an intensive care unit in INTERNATIONAL JOURNAL OF CLINICAL MONITORING AND COMPUTING
  • 1996-07. Comparison of four methods of automated recording of physiologic data at one minute intervals in JOURNAL OF CLINICAL MONITORING AND COMPUTING
  • 1991-12. Real time data acquisition: recommendations for the medical information bus (MIB) in INTERNATIONAL JOURNAL OF CLINICAL MONITORING AND COMPUTING
  • 2008-01. The Impact of a Clinical Information System in an Intensive Care Unit in JOURNAL OF CLINICAL MONITORING AND COMPUTING
  • 1991-04. Normal fluctuation of physiologic cardiovascular variables during anesthesia and the phenomenon of “smoothing” in JOURNAL OF CLINICAL MONITORING AND COMPUTING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10877-009-9192-x

    DOI

    http://dx.doi.org/10.1007/s10877-009-9192-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1003867727

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/19629728


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    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/2008/1117", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Public Health and Health Services", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Algorithms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Artificial Intelligence", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Diagnosis, Computer-Assisted", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Middle Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Monitoring, Physiologic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Nurses", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Pattern Recognition, Automated", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Physical Examination", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Point-of-Care Systems", 
            "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": "Vital Signs", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of California Los Angeles", 
              "id": "https://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Neuroinformatics Service and Support, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sapo", 
            "givenName": "Monica", 
            "id": "sg:person.0671337457.08", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0671337457.08"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Electronic Science and Technology of China", 
              "id": "https://www.grid.ac/institutes/grid.54549.39", 
              "name": [
                "Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine, University of California, NPI 18-240, 90095, Los Angeles, CA, USA", 
                "School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wu", 
            "givenName": "Shaozhi", 
            "id": "sg:person.01227027640.38", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01227027640.38"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California Los Angeles", 
              "id": "https://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine, University of California, NPI 18-240, 90095, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Asgari", 
            "givenName": "Shadnaz", 
            "id": "sg:person.01334404745.42", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334404745.42"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Ronald Reagan UCLA Medical Center", 
              "id": "https://www.grid.ac/institutes/grid.413083.d", 
              "name": [
                "Department of Nursing, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "McNair", 
            "givenName": "Norma", 
            "id": "sg:person.0710753044.70", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710753044.70"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California Los Angeles", 
              "id": "https://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Neuroinformatics Service and Support, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Buxey", 
            "givenName": "Farzad", 
            "id": "sg:person.01371060623.81", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01371060623.81"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Ronald Reagan UCLA Medical Center", 
              "id": "https://www.grid.ac/institutes/grid.413083.d", 
              "name": [
                "Department of Neurosurgery, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Martin", 
            "givenName": "Neil", 
            "id": "sg:person.015255370547.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015255370547.46"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California Los Angeles", 
              "id": "https://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine, University of California, NPI 18-240, 90095, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hu", 
            "givenName": "Xiao", 
            "id": "sg:person.01026220275.59", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026220275.59"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1197/jamia.m2219", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003766307"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jcrc.2004.09.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005779247"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10877-007-9104-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007842801", 
              "https://doi.org/10.1007/s10877-007-9104-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10877-007-9104-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007842801", 
              "https://doi.org/10.1007/s10877-007-9104-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01739125", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011796362", 
              "https://doi.org/10.1007/bf01739125"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01739125", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011796362", 
              "https://doi.org/10.1007/bf01739125"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01618113", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019797440", 
              "https://doi.org/10.1007/bf01618113"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01259562", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034623354", 
              "https://doi.org/10.1007/bf01259562"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01259562", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034623354", 
              "https://doi.org/10.1007/bf01259562"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jcrc.2004.10.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035696648"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1213/00000539-200009000-00022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043574498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1213/00000539-200009000-00022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043574498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02221750", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051722708", 
              "https://doi.org/10.1007/bf02221750"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02221750", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051722708", 
              "https://doi.org/10.1007/bf02221750"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0967-3334/29/4/004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059123275"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0967-3334/30/11/006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059123399"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0967-3334/30/11/006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059123399"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/00000539-200009000-00022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060126623"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/4233.640653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061171190"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/51.248164", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061184433"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tbme.2008.2008636", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061527419"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tbme.2009.2015459", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061527644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/titb.2009.2034845", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061656821"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1074315530", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082384327", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1083130914", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2009-10", 
        "datePublishedReg": "2009-10-01", 
        "description": "OBJECTIVE: (1) To investigate if there exist any discrepancies between the values of vital signs charted by nurses and those recorded by bedside monitors for a group of patients admitted for neurocritical care. (2) To investigate possible interpretations of discrepancies by exploring information in the alarm messages and the raw waveform data from monitors.\nMETHODS: Each charted vital sign value was paired with a corresponding value from data collected by an archival program of bedside monitors such that the automatically archived data preceded the charted data and had minimal time lag to the charted value. Next, the absolute differences between the paired values were taken as the discrepancy between charted and automatically-collected data. Archived alarm messages were searched for technical alarms of sensor/lead failure types. Additionally, 7-min waveform data around the place of large discrepancy were analyzed using signal abnormality indices (SAI) for quantifying the quality of recorded signals.\nRESULTS: About 31,145 pairs of systolic blood pressure (BP-S) and 67,097 pairs of SpO(2) were investigated. Seven and a half percent of systolic blood pressure pairs had a discrepancy greater than 20 mmHg and less than one percent of the SpO2 pairs had a discrepancy greater than 10. We could not find any technical alarms from the monitors that could explain the large difference. However, SAI calculated for the waveforms associated with this group of cases was significantly larger than the SAI values calculated for the control waveform data of the same patients with small discrepancies.\nCONCLUSION: Charted vital signs reflect in large the raw data as reported by bedside monitors. Poor signal quality could partially explain the existence of cases of large discrepancies.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10877-009-9192-x", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1118054", 
            "issn": [
              "1387-1307", 
              "1573-2614"
            ], 
            "name": "Journal of Clinical Monitoring and Computing", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "23"
          }
        ], 
        "name": "A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices", 
        "pagination": "263-271", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "126d44bfabd5f078b6a207e944074b49413acd096ee76f5dd519941196536bd5"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "19629728"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "9806357"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10877-009-9192-x"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1003867727"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10877-009-9192-x", 
          "https://app.dimensions.ai/details/publication/pub.1003867727"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T09:26", 
        "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/v90/0000000345_0000000345/records_64117_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs10877-009-9192-x"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    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/s10877-009-9192-x'

    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/s10877-009-9192-x'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10877-009-9192-x'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10877-009-9192-x'


     

    This table displays all metadata directly associated to this object as RDF triples.

    242 TRIPLES      21 PREDICATES      64 URIs      36 LITERALS      24 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10877-009-9192-x schema:about N07e489a319ae455d97deaad845cf45c2
    2 N1afba0349c8746ff88fdebb6d9d5fceb
    3 N2693c24c430f4327abfca29d286b34cb
    4 N2c61664272bf4ca2a24223f448ed951c
    5 N35a60dc314c24979937a5a50c2aff6e5
    6 N489ac116670e4c91ae411ad68c50cd5b
    7 N4ea6f109fda84067a14eec574527014c
    8 N60e712c3b776425ebaad7e040cec06c6
    9 N715e7e0672ca4f6bb0cfd0196ef00d88
    10 N9271da859a1d4dd18aca630e6b70ff66
    11 Na054f730b501422c84dc4818104fff41
    12 Naa56fe4dfcdd476bb45b279cd59b6259
    13 Nbc3f712f3cb5446f831f24987a97533a
    14 Nde29f6331a05407e92cb67cb8c3ea816
    15 Nf468f9ddde3c4ae7ba9b5b2998733e99
    16 anzsrc-for:11
    17 anzsrc-for:1117
    18 schema:author N601476bf55fb463dabafec7e2ad00c4e
    19 schema:citation sg:pub.10.1007/bf01259562
    20 sg:pub.10.1007/bf01618113
    21 sg:pub.10.1007/bf01739125
    22 sg:pub.10.1007/bf02221750
    23 sg:pub.10.1007/s10877-007-9104-x
    24 https://app.dimensions.ai/details/publication/pub.1074315530
    25 https://app.dimensions.ai/details/publication/pub.1082384327
    26 https://app.dimensions.ai/details/publication/pub.1083130914
    27 https://doi.org/10.1016/j.jcrc.2004.09.005
    28 https://doi.org/10.1016/j.jcrc.2004.10.002
    29 https://doi.org/10.1088/0967-3334/29/4/004
    30 https://doi.org/10.1088/0967-3334/30/11/006
    31 https://doi.org/10.1097/00000539-200009000-00022
    32 https://doi.org/10.1109/4233.640653
    33 https://doi.org/10.1109/51.248164
    34 https://doi.org/10.1109/tbme.2008.2008636
    35 https://doi.org/10.1109/tbme.2009.2015459
    36 https://doi.org/10.1109/titb.2009.2034845
    37 https://doi.org/10.1197/jamia.m2219
    38 https://doi.org/10.1213/00000539-200009000-00022
    39 schema:datePublished 2009-10
    40 schema:datePublishedReg 2009-10-01
    41 schema:description OBJECTIVE: (1) To investigate if there exist any discrepancies between the values of vital signs charted by nurses and those recorded by bedside monitors for a group of patients admitted for neurocritical care. (2) To investigate possible interpretations of discrepancies by exploring information in the alarm messages and the raw waveform data from monitors. METHODS: Each charted vital sign value was paired with a corresponding value from data collected by an archival program of bedside monitors such that the automatically archived data preceded the charted data and had minimal time lag to the charted value. Next, the absolute differences between the paired values were taken as the discrepancy between charted and automatically-collected data. Archived alarm messages were searched for technical alarms of sensor/lead failure types. Additionally, 7-min waveform data around the place of large discrepancy were analyzed using signal abnormality indices (SAI) for quantifying the quality of recorded signals. RESULTS: About 31,145 pairs of systolic blood pressure (BP-S) and 67,097 pairs of SpO(2) were investigated. Seven and a half percent of systolic blood pressure pairs had a discrepancy greater than 20 mmHg and less than one percent of the SpO2 pairs had a discrepancy greater than 10. We could not find any technical alarms from the monitors that could explain the large difference. However, SAI calculated for the waveforms associated with this group of cases was significantly larger than the SAI values calculated for the control waveform data of the same patients with small discrepancies. CONCLUSION: Charted vital signs reflect in large the raw data as reported by bedside monitors. Poor signal quality could partially explain the existence of cases of large discrepancies.
    42 schema:genre research_article
    43 schema:inLanguage en
    44 schema:isAccessibleForFree false
    45 schema:isPartOf N1b198c4e0a9a4165b6440d04a71bec2a
    46 Nd97fbd72b12c4ed6b86bfdf07e4cae57
    47 sg:journal.1118054
    48 schema:name A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices
    49 schema:pagination 263-271
    50 schema:productId N2e73dbebe7f8488fb1a1adb623452ab5
    51 N5f885f4e78554adabc7bec26c8ec4531
    52 N77b97ae9233c4ecc9ef0ce1a78d2c2bc
    53 Ne20bd04896794dc68f5d08d3c462998d
    54 Neeeb9c44129943a69f07b44e29f90337
    55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003867727
    56 https://doi.org/10.1007/s10877-009-9192-x
    57 schema:sdDatePublished 2019-04-11T09:26
    58 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    59 schema:sdPublisher N48e5ca752ffc4595ba27c2b1516b51f8
    60 schema:url http://link.springer.com/10.1007%2Fs10877-009-9192-x
    61 sgo:license sg:explorer/license/
    62 sgo:sdDataset articles
    63 rdf:type schema:ScholarlyArticle
    64 N07e489a319ae455d97deaad845cf45c2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    65 schema:name Monitoring, Physiologic
    66 rdf:type schema:DefinedTerm
    67 N1afba0349c8746ff88fdebb6d9d5fceb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    68 schema:name Nurses
    69 rdf:type schema:DefinedTerm
    70 N1b198c4e0a9a4165b6440d04a71bec2a schema:issueNumber 5
    71 rdf:type schema:PublicationIssue
    72 N23beda6fa1b140549e54e715a457353c rdf:first sg:person.01026220275.59
    73 rdf:rest rdf:nil
    74 N2693c24c430f4327abfca29d286b34cb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    75 schema:name Vital Signs
    76 rdf:type schema:DefinedTerm
    77 N2c61664272bf4ca2a24223f448ed951c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    78 schema:name Pattern Recognition, Automated
    79 rdf:type schema:DefinedTerm
    80 N2e73dbebe7f8488fb1a1adb623452ab5 schema:name nlm_unique_id
    81 schema:value 9806357
    82 rdf:type schema:PropertyValue
    83 N35a60dc314c24979937a5a50c2aff6e5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    84 schema:name Diagnosis, Computer-Assisted
    85 rdf:type schema:DefinedTerm
    86 N44578a2ed1a8422192b2e72cbe2146af rdf:first sg:person.01334404745.42
    87 rdf:rest N5d2e9a720bdd4bf68033e5d267fc6134
    88 N489ac116670e4c91ae411ad68c50cd5b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    89 schema:name Sensitivity and Specificity
    90 rdf:type schema:DefinedTerm
    91 N48e5ca752ffc4595ba27c2b1516b51f8 schema:name Springer Nature - SN SciGraph project
    92 rdf:type schema:Organization
    93 N4ea6f109fda84067a14eec574527014c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    94 schema:name Artificial Intelligence
    95 rdf:type schema:DefinedTerm
    96 N5d2e9a720bdd4bf68033e5d267fc6134 rdf:first sg:person.0710753044.70
    97 rdf:rest N9db6a288dd6a4a82b11572a1dfd6eb8c
    98 N5f885f4e78554adabc7bec26c8ec4531 schema:name dimensions_id
    99 schema:value pub.1003867727
    100 rdf:type schema:PropertyValue
    101 N601476bf55fb463dabafec7e2ad00c4e rdf:first sg:person.0671337457.08
    102 rdf:rest N8b84751f2c3444b3839cba4ee01bcdb6
    103 N60e712c3b776425ebaad7e040cec06c6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    104 schema:name Physical Examination
    105 rdf:type schema:DefinedTerm
    106 N6891c3d8c7974dc585af7d6e95f4d25b rdf:first sg:person.015255370547.46
    107 rdf:rest N23beda6fa1b140549e54e715a457353c
    108 N715e7e0672ca4f6bb0cfd0196ef00d88 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    109 schema:name Middle Aged
    110 rdf:type schema:DefinedTerm
    111 N77b97ae9233c4ecc9ef0ce1a78d2c2bc schema:name doi
    112 schema:value 10.1007/s10877-009-9192-x
    113 rdf:type schema:PropertyValue
    114 N8b84751f2c3444b3839cba4ee01bcdb6 rdf:first sg:person.01227027640.38
    115 rdf:rest N44578a2ed1a8422192b2e72cbe2146af
    116 N9271da859a1d4dd18aca630e6b70ff66 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    117 schema:name Point-of-Care Systems
    118 rdf:type schema:DefinedTerm
    119 N9db6a288dd6a4a82b11572a1dfd6eb8c rdf:first sg:person.01371060623.81
    120 rdf:rest N6891c3d8c7974dc585af7d6e95f4d25b
    121 Na054f730b501422c84dc4818104fff41 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    122 schema:name Reproducibility of Results
    123 rdf:type schema:DefinedTerm
    124 Naa56fe4dfcdd476bb45b279cd59b6259 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Female
    126 rdf:type schema:DefinedTerm
    127 Nbc3f712f3cb5446f831f24987a97533a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    128 schema:name Male
    129 rdf:type schema:DefinedTerm
    130 Nd97fbd72b12c4ed6b86bfdf07e4cae57 schema:volumeNumber 23
    131 rdf:type schema:PublicationVolume
    132 Nde29f6331a05407e92cb67cb8c3ea816 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    133 schema:name Algorithms
    134 rdf:type schema:DefinedTerm
    135 Ne20bd04896794dc68f5d08d3c462998d schema:name pubmed_id
    136 schema:value 19629728
    137 rdf:type schema:PropertyValue
    138 Neeeb9c44129943a69f07b44e29f90337 schema:name readcube_id
    139 schema:value 126d44bfabd5f078b6a207e944074b49413acd096ee76f5dd519941196536bd5
    140 rdf:type schema:PropertyValue
    141 Nf468f9ddde3c4ae7ba9b5b2998733e99 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    142 schema:name Humans
    143 rdf:type schema:DefinedTerm
    144 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    145 schema:name Medical and Health Sciences
    146 rdf:type schema:DefinedTerm
    147 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
    148 schema:name Public Health and Health Services
    149 rdf:type schema:DefinedTerm
    150 sg:journal.1118054 schema:issn 1387-1307
    151 1573-2614
    152 schema:name Journal of Clinical Monitoring and Computing
    153 rdf:type schema:Periodical
    154 sg:person.01026220275.59 schema:affiliation https://www.grid.ac/institutes/grid.19006.3e
    155 schema:familyName Hu
    156 schema:givenName Xiao
    157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026220275.59
    158 rdf:type schema:Person
    159 sg:person.01227027640.38 schema:affiliation https://www.grid.ac/institutes/grid.54549.39
    160 schema:familyName Wu
    161 schema:givenName Shaozhi
    162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01227027640.38
    163 rdf:type schema:Person
    164 sg:person.01334404745.42 schema:affiliation https://www.grid.ac/institutes/grid.19006.3e
    165 schema:familyName Asgari
    166 schema:givenName Shadnaz
    167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334404745.42
    168 rdf:type schema:Person
    169 sg:person.01371060623.81 schema:affiliation https://www.grid.ac/institutes/grid.19006.3e
    170 schema:familyName Buxey
    171 schema:givenName Farzad
    172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01371060623.81
    173 rdf:type schema:Person
    174 sg:person.015255370547.46 schema:affiliation https://www.grid.ac/institutes/grid.413083.d
    175 schema:familyName Martin
    176 schema:givenName Neil
    177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015255370547.46
    178 rdf:type schema:Person
    179 sg:person.0671337457.08 schema:affiliation https://www.grid.ac/institutes/grid.19006.3e
    180 schema:familyName Sapo
    181 schema:givenName Monica
    182 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0671337457.08
    183 rdf:type schema:Person
    184 sg:person.0710753044.70 schema:affiliation https://www.grid.ac/institutes/grid.413083.d
    185 schema:familyName McNair
    186 schema:givenName Norma
    187 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710753044.70
    188 rdf:type schema:Person
    189 sg:pub.10.1007/bf01259562 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034623354
    190 https://doi.org/10.1007/bf01259562
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1007/bf01618113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019797440
    193 https://doi.org/10.1007/bf01618113
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1007/bf01739125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011796362
    196 https://doi.org/10.1007/bf01739125
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1007/bf02221750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051722708
    199 https://doi.org/10.1007/bf02221750
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1007/s10877-007-9104-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007842801
    202 https://doi.org/10.1007/s10877-007-9104-x
    203 rdf:type schema:CreativeWork
    204 https://app.dimensions.ai/details/publication/pub.1074315530 schema:CreativeWork
    205 https://app.dimensions.ai/details/publication/pub.1082384327 schema:CreativeWork
    206 https://app.dimensions.ai/details/publication/pub.1083130914 schema:CreativeWork
    207 https://doi.org/10.1016/j.jcrc.2004.09.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005779247
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1016/j.jcrc.2004.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035696648
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1088/0967-3334/29/4/004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059123275
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1088/0967-3334/30/11/006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059123399
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1097/00000539-200009000-00022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060126623
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1109/4233.640653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061171190
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1109/51.248164 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061184433
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1109/tbme.2008.2008636 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061527419
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1109/tbme.2009.2015459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061527644
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1109/titb.2009.2034845 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061656821
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1197/jamia.m2219 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003766307
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1213/00000539-200009000-00022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043574498
    230 rdf:type schema:CreativeWork
    231 https://www.grid.ac/institutes/grid.19006.3e schema:alternateName University of California Los Angeles
    232 schema:name Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine, University of California, NPI 18-240, 90095, Los Angeles, CA, USA
    233 Neuroinformatics Service and Support, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
    234 rdf:type schema:Organization
    235 https://www.grid.ac/institutes/grid.413083.d schema:alternateName Ronald Reagan UCLA Medical Center
    236 schema:name Department of Neurosurgery, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA
    237 Department of Nursing, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA
    238 rdf:type schema:Organization
    239 https://www.grid.ac/institutes/grid.54549.39 schema:alternateName University of Electronic Science and Technology of China
    240 schema:name Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine, University of California, NPI 18-240, 90095, Los Angeles, CA, USA
    241 School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, China
    242 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...