Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial

Introduction Occurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system...

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Autores principales:	Ursula Marschall, S Fatima Faqar-Uz-Zaman, Natalie Filmann, Dora Mahkovic, Michael von Wagner, Charlotte Detemble, Ulf Kippke, Luxia Anantharajah, Philipp Baumartz, Paula Sobotta, Wolf O Bechstein, Andreas A Schnitzbauer
Formato:	article
Lenguaje:	EN
Publicado:	BMJ Publishing Group 2021
Materias:	Medicine R
Acceso en línea:	https://doaj.org/article/76b6636926744dd2997e23e11a4a1230
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spelling	oai:doaj.org-article:76b6636926744dd2997e23e11a4a12302021-11-11T19:00:10ZStudy protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial10.1136/bmjopen-2020-0413962044-6055https://doaj.org/article/76b6636926744dd2997e23e11a4a12302021-01-01T00:00:00Zhttps://bmjopen.bmj.com/content/11/1/e041396.fullhttps://doaj.org/toc/2044-6055Introduction Occurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system have been developed to enhance clinical performance by suggesting differential diagnoses to a given case, based on an integrated medical knowledge base and machine learning techniques. The purpose of the study is to evaluate the diagnostic accuracy of Ada, an app-based diagnostic tool and the impact on patient outcome.Methods and analysis The eRadaR trial is a prospective, double-blinded study with patients presenting to the emergency room (ER) with abdominal pain. At initial contact in the ER, a structured interview will be performed using the Ada-App and both, patients and attending physicians, will be blinded to the proposed diagnosis lists until trial completion. Throughout the study, clinical data relating to diagnostic findings and types of therapy will be obtained and the follow-up until day 90 will comprise occurrence of complications and overall survival of patients. The primary efficacy of the trial is defined by the percentage of correct diagnoses suggested by Ada compared with the final discharge diagnosis. Further, accuracy and timing of diagnosis will be compared with decision making of classical doctor–patient interaction. Secondary objectives are complications, length of hospital stay and overall survival.Ethics and dissemination Ethical approval was received by the independent ethics committee (IEC) of the Goethe-University Frankfurt on 9 April 2020 including the patient information material and informed consent form. All protocol amendments must be reported to and adapted by the IEC. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings.Trial registration number DRKS00019098.Ursula MarschallS Fatima Faqar-Uz-ZamanNatalie FilmannDora MahkovicMichael von WagnerCharlotte DetembleUlf KippkeLuxia AnantharajahPhilipp BaumartzPaula SobottaWolf O BechsteinAndreas A SchnitzbauerBMJ Publishing GrouparticleMedicineRENBMJ Open, Vol 11, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R
spellingShingle	Medicine R Ursula Marschall S Fatima Faqar-Uz-Zaman Natalie Filmann Dora Mahkovic Michael von Wagner Charlotte Detemble Ulf Kippke Luxia Anantharajah Philipp Baumartz Paula Sobotta Wolf O Bechstein Andreas A Schnitzbauer Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
description	Introduction Occurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system have been developed to enhance clinical performance by suggesting differential diagnoses to a given case, based on an integrated medical knowledge base and machine learning techniques. The purpose of the study is to evaluate the diagnostic accuracy of Ada, an app-based diagnostic tool and the impact on patient outcome.Methods and analysis The eRadaR trial is a prospective, double-blinded study with patients presenting to the emergency room (ER) with abdominal pain. At initial contact in the ER, a structured interview will be performed using the Ada-App and both, patients and attending physicians, will be blinded to the proposed diagnosis lists until trial completion. Throughout the study, clinical data relating to diagnostic findings and types of therapy will be obtained and the follow-up until day 90 will comprise occurrence of complications and overall survival of patients. The primary efficacy of the trial is defined by the percentage of correct diagnoses suggested by Ada compared with the final discharge diagnosis. Further, accuracy and timing of diagnosis will be compared with decision making of classical doctor–patient interaction. Secondary objectives are complications, length of hospital stay and overall survival.Ethics and dissemination Ethical approval was received by the independent ethics committee (IEC) of the Goethe-University Frankfurt on 9 April 2020 including the patient information material and informed consent form. All protocol amendments must be reported to and adapted by the IEC. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings.Trial registration number DRKS00019098.
format	article
author	Ursula Marschall S Fatima Faqar-Uz-Zaman Natalie Filmann Dora Mahkovic Michael von Wagner Charlotte Detemble Ulf Kippke Luxia Anantharajah Philipp Baumartz Paula Sobotta Wolf O Bechstein Andreas A Schnitzbauer
author_facet	Ursula Marschall S Fatima Faqar-Uz-Zaman Natalie Filmann Dora Mahkovic Michael von Wagner Charlotte Detemble Ulf Kippke Luxia Anantharajah Philipp Baumartz Paula Sobotta Wolf O Bechstein Andreas A Schnitzbauer
author_sort	Ursula Marschall
title	Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
title_short	Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
title_full	Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
title_fullStr	Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
title_full_unstemmed	Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial
title_sort	study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eradar trial
publisher	BMJ Publishing Group
publishDate	2021
url	https://doaj.org/article/76b6636926744dd2997e23e11a4a1230
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Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial

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