TY - JOUR
T1 - Systematic review of clinical decision support systems for pre-hospital acute coronary syndrome identification
AU - Knoery, Charles
AU - Heaton, Janet
AU - Polson, Rob
AU - Bond, RR
AU - Iftikhar, Aleeha
AU - Rjoob, Khaled
AU - McGilligan, V. E.
AU - Peace, Aaron
AU - Leslie, Stephen
N1 - Publisher Copyright:
© 2020 Lippincott Williams and Wilkins. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - OBJECTIVES: Timely prehospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the prehospital environment. The review aim was to describe the accuracy of CDSS and individual components in the prehospital ACS management. METHODS: This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the prehospital setting, the influence of computer-aided decision-making and of 4 components: electrocardiogram, biomarkers, patient history, and examination findings. The impact of these components on sensitivity, specificity, and positive and negative predictive values was assessed. RESULTS: A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. CDSS which incorporated all 4 components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values. CONCLUSIONS: Although heterogeneity precluded meta-analysis, this review emphasizes the potential of ACS CDSS in prehospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.
AB - OBJECTIVES: Timely prehospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the prehospital environment. The review aim was to describe the accuracy of CDSS and individual components in the prehospital ACS management. METHODS: This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the prehospital setting, the influence of computer-aided decision-making and of 4 components: electrocardiogram, biomarkers, patient history, and examination findings. The impact of these components on sensitivity, specificity, and positive and negative predictive values was assessed. RESULTS: A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. CDSS which incorporated all 4 components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values. CONCLUSIONS: Although heterogeneity precluded meta-analysis, this review emphasizes the potential of ACS CDSS in prehospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.
KW - acute coronary syndrome
KW - algorithm
KW - clinical decision support systems
KW - diagnosis
KW - emergency medical services
UR - https://journals.lww.com/critpathcardio/Abstract/publishahead/Systematic_review_of_clinical_decision_support.99972.aspx
UR - http://www.scopus.com/inward/record.url?scp=85089128413&partnerID=8YFLogxK
U2 - 10.1097/HPC.0000000000000217
DO - 10.1097/HPC.0000000000000217
M3 - Review article
C2 - 32209826
VL - 19
SP - 119
EP - 125
JO - Critical Pathways in Cardiology
JF - Critical Pathways in Cardiology
SN - 1535-282X
IS - 3
ER -