1675. Implementation of Electronic Travel History Screening at an Urban Medical Center
Identifieur interne : 000751 ( Main/Exploration ); précédent : 000750; suivant : 0007521675. Implementation of Electronic Travel History Screening at an Urban Medical Center
Auteurs : Annabelle M. De St. Maurice [États-Unis] ; Sandra Martinez [États-Unis] ; Sarah Sweeney [États-Unis] ; Elizabeth Genta [États-Unis] ; Shaunte Walton [États-Unis] ; Zachary A. Rubin [États-Unis] ; Daniel Uslan [États-Unis]Source :
- Open Forum Infectious Diseases [ 2328-8957 ] ; 2019.
Abstract
Middle East Respiratory Syndrome (MERS), caused by a novel coronavirus, can lead to severe respiratory failure and death. CDC recommends screening patients who traveled to endemic countries for fever, respiratory symptoms, and exposure to MERS-positive contacts and healthcare facilities. UCLA is a large, academic, medical center located in a diverse city with frequent international travel. We implemented a travel screening (TS) questionnaire in our electronic medical record (EMR) (Figure 1) to identify high-risk patients in order to implement early isolation practices and testing. This study describes the use and performance of our TS for identifying suspect MERS cases.
An EMR-based tool prompts nurses to ask patients at triage or admission whether they have traveled out of the country in the past 30 days (Figure 1). If patients answer affirmatively, the EMR prompts nurses to inquire about travel to specific high-risk countries and to review symptoms and exposure risks. Upon notification of a potential MERS case, the EID physician on-call reviews the TS, clinical history, epidemiologic risks, and makes a determination whether further evaluation and/or isolation for suspect MERS is necessary. We reviewed travel history, demographics, and symptoms of patients who triggered a positive TS from April 2017 to September 2018.
The ED completed 115,815 distinct TS on 81,197 individuals during this time period. The median time from ED arrival to TS completion was 6.4 minutes. 308 ED encounters triggered a positive TS; an additional 257 encounters in other units triggered a positive TS, resulting in 565 positive TS (Table 1). 122 (22%) expressed ≥1 MERS symptom and 29 (24%) expressed both fever and respiratory symptoms. Of these symptomatic patients, 0 had a history of contact with a MERS case; 3 had a history of contact with a healthcare facility while traveling; and 4 had a history of contact with camels. No patients were diagnosed with MERS (Table 2).
A history of travel to the MERS endemic countries is relatively common at a large urban hospital. Routine electronic screening of patients is an efficient way to identify high-risk travelers. This EMR tool could be modified for other emerging pathogens, such as measles or Ebola, to identify high-risk patients.
Url:
DOI: 10.1093/ofid/ofz360.1539
PubMed: NONE
PubMed Central: 6809912
Affiliations:
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">1675. Implementation of Electronic Travel History Screening at an Urban Medical Center</title>
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<front><div type="abstract" xml:lang="en"><title>Abstract</title>
<sec id="s2"><title>Background</title>
<p>Middle East Respiratory Syndrome (MERS), caused by a novel coronavirus, can lead to severe respiratory failure and death. CDC recommends screening patients who traveled to endemic countries for fever, respiratory symptoms, and exposure to MERS-positive contacts and healthcare facilities. UCLA is a large, academic, medical center located in a diverse city with frequent international travel. We implemented a travel screening (TS) questionnaire in our electronic medical record (EMR) (Figure 1) to identify high-risk patients in order to implement early isolation practices and testing. This study describes the use and performance of our TS for identifying suspect MERS cases.</p>
</sec>
<sec id="s3"><title>Methods</title>
<p>An EMR-based tool prompts nurses to ask patients at triage or admission whether they have traveled out of the country in the past 30 days (Figure 1). If patients answer affirmatively, the EMR prompts nurses to inquire about travel to specific high-risk countries and to review symptoms and exposure risks. Upon notification of a potential MERS case, the EID physician on-call reviews the TS, clinical history, epidemiologic risks, and makes a determination whether further evaluation and/or isolation for suspect MERS is necessary. We reviewed travel history, demographics, and symptoms of patients who triggered a positive TS from April 2017 to September 2018.</p>
</sec>
<sec id="s4"><title>Results</title>
<p>The ED completed 115,815 distinct TS on 81,197 individuals during this time period. The median time from ED arrival to TS completion was 6.4 minutes. 308 ED encounters triggered a positive TS; an additional 257 encounters in other units triggered a positive TS, resulting in 565 positive TS (Table 1). 122 (22%) expressed ≥1 MERS symptom and 29 (24%) expressed both fever and respiratory symptoms. Of these symptomatic patients, 0 had a history of contact with a MERS case; 3 had a history of contact with a healthcare facility while traveling; and 4 had a history of contact with camels. No patients were diagnosed with MERS (Table 2).</p>
</sec>
<sec id="s5"><title>Conclusion</title>
<p>A history of travel to the MERS endemic countries is relatively common at a large urban hospital. Routine electronic screening of patients is an efficient way to identify high-risk travelers. This EMR tool could be modified for other emerging pathogens, such as measles or Ebola, to identify high-risk patients.</p>
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<p><graphic xlink:href="ofidis_ofz360_f1522.jpg" position="float" mimetype="image" orientation="portrait"></graphic>
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<p><graphic xlink:href="ofidis_ofz360_f1523.jpg" position="float" mimetype="image" orientation="portrait"></graphic>
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<sec id="s6"><title>Disclosures</title>
<p><bold>All authors:</bold>
No reported disclosures.</p>
</sec>
</div>
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<region><li>Californie</li>
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<name sortKey="Genta, Elizabeth" sort="Genta, Elizabeth" uniqKey="Genta E" first="Elizabeth" last="Genta">Elizabeth Genta</name>
<name sortKey="Martinez, Sandra" sort="Martinez, Sandra" uniqKey="Martinez S" first="Sandra" last="Martinez">Sandra Martinez</name>
<name sortKey="Rubin, Zachary A" sort="Rubin, Zachary A" uniqKey="Rubin Z" first="Zachary A" last="Rubin">Zachary A. Rubin</name>
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<name sortKey="Uslan, Daniel" sort="Uslan, Daniel" uniqKey="Uslan D" first="Daniel" last="Uslan">Daniel Uslan</name>
<name sortKey="Walton, Shaunte" sort="Walton, Shaunte" uniqKey="Walton S" first="Shaunte" last="Walton">Shaunte Walton</name>
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