TY - JOUR
T1 - Modeling flowsheet data to support secondary use
AU - Westra, Bonnie L.
AU - Christie, Beverly
AU - Johnson, Steven G.
AU - Pruinelli, Lisiane
AU - La Flamme, Anne
AU - Sherman, Suzan G.
AU - Park, Jung In
AU - Delaney, Connie W.
AU - Gao, Grace
AU - Speedie, Stuart
PY - 2017/9/1
Y1 - 2017/9/1
N2 - The purpose of this study was to create information models from flowsheet data using a data-driven consensusbasedmethod. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thromboembolism, genitourinary system including catheter-associated urinary tract infection, and painmanagement) and five high-volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for falls to 78% for the respiratory system. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.
AB - The purpose of this study was to create information models from flowsheet data using a data-driven consensusbasedmethod. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thromboembolism, genitourinary system including catheter-associated urinary tract infection, and painmanagement) and five high-volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for falls to 78% for the respiratory system. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.
KW - Electronic health records
KW - Information models
KW - Meaningful use
KW - Nursing informatics
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UR - http://www.scopus.com/inward/citedby.url?scp=85016105383&partnerID=8YFLogxK
U2 - 10.1097/CIN.0000000000000350
DO - 10.1097/CIN.0000000000000350
M3 - Article
C2 - 28346243
AN - SCOPUS:85016105383
SN - 1538-2931
VL - 35
SP - 452
EP - 458
JO - CIN - Computers Informatics Nursing
JF - CIN - Computers Informatics Nursing
IS - 9
ER -