Clinical Decision Support Systems in the Emergency Department: Opportunities to Improve Triage Accuracy
Pediatric patients historically have had a lower level of consistency in triage decisions, and up to 50% of patients with acute myocardial infarction are undertriaged or assigned an acuity level that is lower than what it should be based on their final diagnosis.4-6 Mis-triage is a problem among nur...
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description | Pediatric patients historically have had a lower level of consistency in triage decisions, and up to 50% of patients with acute myocardial infarction are undertriaged or assigned an acuity level that is lower than what it should be based on their final diagnosis.4-6 Mis-triage is a problem among nurses of all experience levels4 and can lead to dangerous delays in care.Clinical Decision Support Systems Clinical decision support systems (CDSSs) were first introduced into health care in the 1970s and experienced renewed focus in the 2000s after the Centers for Medicare and Medicaid Services began incentivizing health care institutions for programs that utilized them to improve patient care, processes, and outcomes. CDSSs suggested, studied, or utilized in the emergency department include those designed to help nurses and other health care professionals assess and stratify risk for acute coronary syndrome, acute myocardial infarction,5,6,8 sepsis,9 syncope,10 and head injuries.11,12 These conditions all represent potential life-threatening situations and are known for their sometimes subtle or atypical clinical presentations.Identifying Clinical Deterioration and Sepsis Abnormalities in vital signs captured in the electronic health record can help identify septic shock or other clinical deterioration up to several hours prior to a serious adverse event.13 For example, studies have shown that at least 80% of adult patients who have experienced severe sepsis have had tachycardia and tachypnea.9 However, studies also have shown that many septic children present in compensated shock, with tachycardia being the only indicator of potential decompensation.14 These physiologic differences, and the fact that febrile illnesses are so common in children, make sepsis very challenging to identify in the pediatric population. Early warning scores that provide real-time alerts based on vital signs and laboratory data also have been successful in supporting early identification and treatment of patients at risk for myocardial infarction.9Stratifying Risk for Pediatric Head Injuries Another challenge within the process of triage decision making is predicting which children younger than 2 years are at risk for underlying skull fracture or intracranial bleeding after a sustained or suspected minor head injury.3,17 Head injury risk variances stratified by the age of the child, the mechanism of injury, the region of skull injured, and the presence or size of a hematoma are reflect |
doi_str_mv | 10.1016/j.jen.2018.12.016 |
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CDSSs suggested, studied, or utilized in the emergency department include those designed to help nurses and other health care professionals assess and stratify risk for acute coronary syndrome, acute myocardial infarction,5,6,8 sepsis,9 syncope,10 and head injuries.11,12 These conditions all represent potential life-threatening situations and are known for their sometimes subtle or atypical clinical presentations.Identifying Clinical Deterioration and Sepsis Abnormalities in vital signs captured in the electronic health record can help identify septic shock or other clinical deterioration up to several hours prior to a serious adverse event.13 For example, studies have shown that at least 80% of adult patients who have experienced severe sepsis have had tachycardia and tachypnea.9 However, studies also have shown that many septic children present in compensated shock, with tachycardia being the only indicator of potential decompensation.14 These physiologic differences, and the fact that febrile illnesses are so common in children, make sepsis very challenging to identify in the pediatric population. Early warning scores that provide real-time alerts based on vital signs and laboratory data also have been successful in supporting early identification and treatment of patients at risk for myocardial infarction.9Stratifying Risk for Pediatric Head Injuries Another challenge within the process of triage decision making is predicting which children younger than 2 years are at risk for underlying skull fracture or intracranial bleeding after a sustained or suspected minor head injury.3,17 Head injury risk variances stratified by the age of the child, the mechanism of injury, the region of skull injured, and the presence or size of a hematoma are reflected in validated medical decision rules for pediatric patients.</description><identifier>ISSN: 0099-1767</identifier><identifier>EISSN: 1527-2966</identifier><identifier>DOI: 10.1016/j.jen.2018.12.016</identifier><identifier>PMID: 30846145</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accuracy ; Acute coronary syndromes ; Bleeding ; Cardiac arrhythmia ; Children ; Clinical decision making ; Clinical outcomes ; Coronary artery disease ; Critical incidents ; Decision making ; Decision support systems ; Decision Support Systems, Clinical ; Deterioration ; Emergency Service, Hospital - organization & administration ; Emergency services ; Fractures ; Head injuries ; Health services ; Heart attacks ; Humans ; Injuries ; Laboratories ; Life threatening ; Medicaid ; Medical diagnosis ; Medicare ; Myocardial infarction ; Nurses ; Patients ; Pediatrics ; Quality Improvement ; Risk assessment ; Sepsis ; Triage - standards</subject><ispartof>Journal of emergency nursing, 2019-03, Vol.45 (2), p.220-222</ispartof><rights>2019 Emergency Nurses Association</rights><rights>Copyright Elsevier Limited Mar 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c381t-ec7210c5b8c4dedcf65919f3c8b6b8508972b6f78a9682658665d3f4a18db4eb3</citedby><cites>FETCH-LOGICAL-c381t-ec7210c5b8c4dedcf65919f3c8b6b8508972b6f78a9682658665d3f4a18db4eb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2187919695?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3550,12846,27924,27925,30999,45995,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30846145$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Stone, Elizabeth L.</creatorcontrib><title>Clinical Decision Support Systems in the Emergency Department: Opportunities to Improve Triage Accuracy</title><title>Journal of emergency nursing</title><addtitle>J Emerg Nurs</addtitle><description>Pediatric patients historically have had a lower level of consistency in triage decisions, and up to 50% of patients with acute myocardial infarction are undertriaged or assigned an acuity level that is lower than what it should be based on their final diagnosis.4-6 Mis-triage is a problem among nurses of all experience levels4 and can lead to dangerous delays in care.Clinical Decision Support Systems Clinical decision support systems (CDSSs) were first introduced into health care in the 1970s and experienced renewed focus in the 2000s after the Centers for Medicare and Medicaid Services began incentivizing health care institutions for programs that utilized them to improve patient care, processes, and outcomes. CDSSs suggested, studied, or utilized in the emergency department include those designed to help nurses and other health care professionals assess and stratify risk for acute coronary syndrome, acute myocardial infarction,5,6,8 sepsis,9 syncope,10 and head injuries.11,12 These conditions all represent potential life-threatening situations and are known for their sometimes subtle or atypical clinical presentations.Identifying Clinical Deterioration and Sepsis Abnormalities in vital signs captured in the electronic health record can help identify septic shock or other clinical deterioration up to several hours prior to a serious adverse event.13 For example, studies have shown that at least 80% of adult patients who have experienced severe sepsis have had tachycardia and tachypnea.9 However, studies also have shown that many septic children present in compensated shock, with tachycardia being the only indicator of potential decompensation.14 These physiologic differences, and the fact that febrile illnesses are so common in children, make sepsis very challenging to identify in the pediatric population. Early warning scores that provide real-time alerts based on vital signs and laboratory data also have been successful in supporting early identification and treatment of patients at risk for myocardial infarction.9Stratifying Risk for Pediatric Head Injuries Another challenge within the process of triage decision making is predicting which children younger than 2 years are at risk for underlying skull fracture or intracranial bleeding after a sustained or suspected minor head injury.3,17 Head injury risk variances stratified by the age of the child, the mechanism of injury, the region of skull injured, and the presence or size of a hematoma are reflected in validated medical decision rules for pediatric patients.</description><subject>Accuracy</subject><subject>Acute coronary syndromes</subject><subject>Bleeding</subject><subject>Cardiac arrhythmia</subject><subject>Children</subject><subject>Clinical decision making</subject><subject>Clinical outcomes</subject><subject>Coronary artery disease</subject><subject>Critical incidents</subject><subject>Decision making</subject><subject>Decision support systems</subject><subject>Decision Support Systems, Clinical</subject><subject>Deterioration</subject><subject>Emergency Service, Hospital - organization & administration</subject><subject>Emergency services</subject><subject>Fractures</subject><subject>Head injuries</subject><subject>Health services</subject><subject>Heart attacks</subject><subject>Humans</subject><subject>Injuries</subject><subject>Laboratories</subject><subject>Life threatening</subject><subject>Medicaid</subject><subject>Medical diagnosis</subject><subject>Medicare</subject><subject>Myocardial infarction</subject><subject>Nurses</subject><subject>Patients</subject><subject>Pediatrics</subject><subject>Quality Improvement</subject><subject>Risk assessment</subject><subject>Sepsis</subject><subject>Triage - standards</subject><issn>0099-1767</issn><issn>1527-2966</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kU9v1DAQxS0EokvpB-CCLHHpJantxP_gVC2lrVSph7ZnK3Emi6PECbZTab89Xrb0wIHTSKPfezN6D6FPlJSUUHExlAP4khGqSsrKvHmDNpQzWTAtxFu0IUTrgkohT9CHGAdCCJdUv0cnFVG1oDXfoN12dN7ZZsTfwbroZo8f1mWZQ8IP-5hgith5nH4Cvpog7MDbfSaXJqQJfPqK7_-wq3fJQcRpxrfTEuZnwI_BNTvAl9auobH7j-hd34wRzl7mKXr6cfW4vSnu7q9vt5d3ha0UTQVYySixvFW27qCzveCa6r6yqhWt4kRpyVrRS9VooZjgSgjeVX3dUNW1NbTVKTo_-uYvfq0Qk5lctDCOjYd5jYZRpTmvZKUz-uUfdJjX4PN3B0rmu0LzTNEjZcMcY4DeLMFNTdgbSsyhBTOY3II5tGAoM3mTNZ9fnNd2gu5V8Tf2DHw7ApCjeHYQTLQuZwudC2CT6Wb3H_vfDiiYGA</recordid><startdate>201903</startdate><enddate>201903</enddate><creator>Stone, Elizabeth L.</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7QJ</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AN0</scope><scope>ASE</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FPQ</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HEHIP</scope><scope>K6X</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2S</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>201903</creationdate><title>Clinical Decision Support Systems in the Emergency Department: Opportunities to Improve Triage Accuracy</title><author>Stone, Elizabeth L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-ec7210c5b8c4dedcf65919f3c8b6b8508972b6f78a9682658665d3f4a18db4eb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Accuracy</topic><topic>Acute coronary syndromes</topic><topic>Bleeding</topic><topic>Cardiac arrhythmia</topic><topic>Children</topic><topic>Clinical decision making</topic><topic>Clinical outcomes</topic><topic>Coronary artery disease</topic><topic>Critical incidents</topic><topic>Decision making</topic><topic>Decision support systems</topic><topic>Decision Support Systems, Clinical</topic><topic>Deterioration</topic><topic>Emergency Service, Hospital - organization & administration</topic><topic>Emergency services</topic><topic>Fractures</topic><topic>Head injuries</topic><topic>Health services</topic><topic>Heart attacks</topic><topic>Humans</topic><topic>Injuries</topic><topic>Laboratories</topic><topic>Life threatening</topic><topic>Medicaid</topic><topic>Medical diagnosis</topic><topic>Medicare</topic><topic>Myocardial infarction</topic><topic>Nurses</topic><topic>Patients</topic><topic>Pediatrics</topic><topic>Quality Improvement</topic><topic>Risk assessment</topic><topic>Sepsis</topic><topic>Triage - standards</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stone, Elizabeth L.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>British Nursing Database</collection><collection>British Nursing Index</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>British Nursing Index</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Sociology Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of emergency nursing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stone, Elizabeth L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clinical Decision Support Systems in the Emergency Department: Opportunities to Improve Triage Accuracy</atitle><jtitle>Journal of emergency nursing</jtitle><addtitle>J Emerg Nurs</addtitle><date>2019-03</date><risdate>2019</risdate><volume>45</volume><issue>2</issue><spage>220</spage><epage>222</epage><pages>220-222</pages><issn>0099-1767</issn><eissn>1527-2966</eissn><abstract>Pediatric patients historically have had a lower level of consistency in triage decisions, and up to 50% of patients with acute myocardial infarction are undertriaged or assigned an acuity level that is lower than what it should be based on their final diagnosis.4-6 Mis-triage is a problem among nurses of all experience levels4 and can lead to dangerous delays in care.Clinical Decision Support Systems Clinical decision support systems (CDSSs) were first introduced into health care in the 1970s and experienced renewed focus in the 2000s after the Centers for Medicare and Medicaid Services began incentivizing health care institutions for programs that utilized them to improve patient care, processes, and outcomes. CDSSs suggested, studied, or utilized in the emergency department include those designed to help nurses and other health care professionals assess and stratify risk for acute coronary syndrome, acute myocardial infarction,5,6,8 sepsis,9 syncope,10 and head injuries.11,12 These conditions all represent potential life-threatening situations and are known for their sometimes subtle or atypical clinical presentations.Identifying Clinical Deterioration and Sepsis Abnormalities in vital signs captured in the electronic health record can help identify septic shock or other clinical deterioration up to several hours prior to a serious adverse event.13 For example, studies have shown that at least 80% of adult patients who have experienced severe sepsis have had tachycardia and tachypnea.9 However, studies also have shown that many septic children present in compensated shock, with tachycardia being the only indicator of potential decompensation.14 These physiologic differences, and the fact that febrile illnesses are so common in children, make sepsis very challenging to identify in the pediatric population. Early warning scores that provide real-time alerts based on vital signs and laboratory data also have been successful in supporting early identification and treatment of patients at risk for myocardial infarction.9Stratifying Risk for Pediatric Head Injuries Another challenge within the process of triage decision making is predicting which children younger than 2 years are at risk for underlying skull fracture or intracranial bleeding after a sustained or suspected minor head injury.3,17 Head injury risk variances stratified by the age of the child, the mechanism of injury, the region of skull injured, and the presence or size of a hematoma are reflected in validated medical decision rules for pediatric patients.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30846145</pmid><doi>10.1016/j.jen.2018.12.016</doi><tpages>3</tpages></addata></record> |
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subjects | Accuracy Acute coronary syndromes Bleeding Cardiac arrhythmia Children Clinical decision making Clinical outcomes Coronary artery disease Critical incidents Decision making Decision support systems Decision Support Systems, Clinical Deterioration Emergency Service, Hospital - organization & administration Emergency services Fractures Head injuries Health services Heart attacks Humans Injuries Laboratories Life threatening Medicaid Medical diagnosis Medicare Myocardial infarction Nurses Patients Pediatrics Quality Improvement Risk assessment Sepsis Triage - standards |
title | Clinical Decision Support Systems in the Emergency Department: Opportunities to Improve Triage Accuracy |
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