An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome
For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use...
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Published in | Yonsei medical journal Vol. 61; no. 5; pp. 416 - 422 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
Yonsei University College of Medicine
01.05.2020
연세대학교의과대학 |
Subjects | |
Online Access | Get full text |
ISSN | 0513-5796 1976-2437 1976-2437 |
DOI | 10.3349/ymj.2020.61.5.416 |
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Abstract | For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED).
An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted.
During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years,
<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%,
<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms.
An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED. |
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AbstractList | Purpose: For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED).
Materials and Methods: An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient’s electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted.
Results: During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, p<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, p<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2–3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5–3.4 min) for the group with non-cardiac-related symptoms.
Conclusion: An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED. KCI Citation Count: 0 For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED).PURPOSEFor patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED).An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted.MATERIALS AND METHODSAn automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted.During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, p<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, p<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms.RESULTSDuring the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, p<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, p<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms.An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED.CONCLUSIONAn automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED. For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED). An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted. During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, <0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, <0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms. An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED. |
Author | Choi, Jong Soo Hur, Sujeong Kim, Taerim Cha, Won Chul Lee, Jeanhyoung Kang, Mira Chang, Dong Kyung |
AuthorAffiliation | 3 Health Information and Strategy Center, Samsung Medical Center, Seoul, Korea 4 Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea 1 Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea 2 Department of Nursing, Samsung Medical Center, Seoul, Korea 5 Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea 6 Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea |
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Cites_doi | 10.1161/JAHA.116.003528 10.1001/archinternmed.2011.327 10.1377/hlthaff.24.5.1205 10.1093/bioinformatics/btz075 10.3346/jkms.2016.31.8.1331 10.1111/j.1748-720X.2011.00572.x 10.2196/10666 10.1161/01.CIR.0000121424.76486.20 10.1377/hlthaff.2012.0693 10.1097/NNE.0000000000000632 10.1177/0018720815576827 10.1377/hlthaff.W5.10 10.4103/ija.IJA_346_18 10.1097/00001888-200402000-00019 10.1016/j.annemergmed.2006.03.032 |
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References | Helman (10.3349/ymj.2020.61.5.416_ref13) 2019; 36 Walker (10.3349/ymj.2020.61.5.416_ref10) 2005; Suppl Web Exclusives Kellermann (10.3349/ymj.2020.61.5.416_ref7) 2013; 32 R Core Team (10.3349/ymj.2020.61.5.416_ref21) 2018 Yiadom (10.3349/ymj.2020.61.5.416_ref16) 2017; 6 Sutcliffe (10.3349/ymj.2020.61.5.416_ref1) 2004; 79 Mehta (10.3349/ymj.2020.61.5.416_ref14) 2019; 35 Akhlaq (10.3349/ymj.2020.61.5.416_ref8) 2017; 23 Hoffman (10.3349/ymj.2020.61.5.416_ref5) 2011; 39 Suppl 1 Edwards (10.3349/ymj.2020.61.5.416_ref9) 2010; 24 Kim (10.3349/ymj.2020.61.5.416_ref20) 2016; 27 Choi (10.3349/ymj.2020.61.5.416_ref18) 2011; 22 Institute of Medicine, Board on Health Care Services, Committee on Data Standards for Patient Safety (10.3349/ymj.2020.61.5.416_ref2) 2004 Pandya (10.3349/ymj.2020.61.5.416_ref24) 2018; 62 Shapiro (10.3349/ymj.2020.61.5.416_ref3) 2006; 48 Lee (10.3349/ymj.2020.61.5.416_ref23) 2017; 2016 Cha (10.3349/ymj.2020.61.5.416_ref19) 2016; 31 Opsahl (10.3349/ymj.2020.61.5.416_ref22) 2019; 44 Zahabi (10.3349/ymj.2020.61.5.416_ref4) 2015; 57 Khalilia (10.3349/ymj.2020.61.5.416_ref15) 2015; 2015 De Luca (10.3349/ymj.2020.61.5.416_ref17) 2004; 109 Sittig (10.3349/ymj.2020.61.5.416_ref6) 2011; 171 Hammond (10.3349/ymj.2020.61.5.416_ref12) 2005; 24 Yoo (10.3349/ymj.2020.61.5.416_ref25) 2018; 6 Mead (10.3349/ymj.2020.61.5.416_ref11) 2006; 20 |
References_xml | – volume: 36 start-page: 462 year: 2019 ident: 10.3349/ymj.2020.61.5.416_ref13 publication-title: ALTEX – volume: 27 start-page: 436 year: 2016 ident: 10.3349/ymj.2020.61.5.416_ref20 publication-title: J Korean Soc Emerg Med – volume: 23 start-page: 838 year: 2017 ident: 10.3349/ymj.2020.61.5.416_ref8 publication-title: J Innov Health Inform – volume: 22 start-page: 591 year: 2011 ident: 10.3349/ymj.2020.61.5.416_ref18 publication-title: J Korean Soc Emerg Med – volume: 6 start-page: e003528 year: 2017 ident: 10.3349/ymj.2020.61.5.416_ref16 publication-title: J Am Heart Assoc doi: 10.1161/JAHA.116.003528 – volume: 171 start-page: 1281 year: 2011 ident: 10.3349/ymj.2020.61.5.416_ref6 publication-title: Arch Intern Med doi: 10.1001/archinternmed.2011.327 – volume: 24 start-page: 1205 year: 2005 ident: 10.3349/ymj.2020.61.5.416_ref12 publication-title: Health Aff (Millwood) doi: 10.1377/hlthaff.24.5.1205 – volume: 2016 start-page: 753 year: 2017 ident: 10.3349/ymj.2020.61.5.416_ref23 publication-title: AMIA Annu Symp Proc – volume: 35 start-page: 3536 year: 2019 ident: 10.3349/ymj.2020.61.5.416_ref14 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btz075 – volume: 31 start-page: 1331 year: 2016 ident: 10.3349/ymj.2020.61.5.416_ref19 publication-title: J Korean Med Sci doi: 10.3346/jkms.2016.31.8.1331 – volume: 39 Suppl 1 start-page: 77 year: 2011 ident: 10.3349/ymj.2020.61.5.416_ref5 publication-title: J Law Med Ethics doi: 10.1111/j.1748-720X.2011.00572.x – volume-title: R: A Language and Environment for Statistical Computing year: 2018 ident: 10.3349/ymj.2020.61.5.416_ref21 – volume: 6 start-page: e10666 year: 2018 ident: 10.3349/ymj.2020.61.5.416_ref25 publication-title: JMIR Mhealth Uhealth doi: 10.2196/10666 – volume: 109 start-page: 1223 year: 2004 ident: 10.3349/ymj.2020.61.5.416_ref17 publication-title: Circulation doi: 10.1161/01.CIR.0000121424.76486.20 – volume: 2015 start-page: 717 year: 2015 ident: 10.3349/ymj.2020.61.5.416_ref15 publication-title: AMIA Annu Symp Proc – volume: 32 start-page: 63 year: 2013 ident: 10.3349/ymj.2020.61.5.416_ref7 publication-title: Health Aff (Millwood) doi: 10.1377/hlthaff.2012.0693 – volume: 44 start-page: 326 year: 2019 ident: 10.3349/ymj.2020.61.5.416_ref22 publication-title: Nurse Educ doi: 10.1097/NNE.0000000000000632 – volume: 57 start-page: 805 year: 2015 ident: 10.3349/ymj.2020.61.5.416_ref4 publication-title: Hum Factors doi: 10.1177/0018720815576827 – volume-title: Patient safety: achieving a new standard for care year: 2004 ident: 10.3349/ymj.2020.61.5.416_ref2 – volume: 20 start-page: 71 year: 2006 ident: 10.3349/ymj.2020.61.5.416_ref11 publication-title: J Healthc Inf Manag – volume: 24 start-page: 22 year: 2010 ident: 10.3349/ymj.2020.61.5.416_ref9 publication-title: J Healthc Inf Manag – volume: Suppl Web Exclusives start-page: W5-10 year: 2005 ident: 10.3349/ymj.2020.61.5.416_ref10 publication-title: Health Aff (Millwood) doi: 10.1377/hlthaff.W5.10 – volume: 62 start-page: 838 year: 2018 ident: 10.3349/ymj.2020.61.5.416_ref24 publication-title: Indian J Anaesth doi: 10.4103/ija.IJA_346_18 – volume: 79 start-page: 186 year: 2004 ident: 10.3349/ymj.2020.61.5.416_ref1 publication-title: Acad Med doi: 10.1097/00001888-200402000-00019 – volume: 48 start-page: 426 year: 2006 ident: 10.3349/ymj.2020.61.5.416_ref3 publication-title: Ann Emerg Med doi: 10.1016/j.annemergmed.2006.03.032 |
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Title | An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome |
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