search
Back to results

Artificial Intelligence (IA) Advanced Triage Tool for G&O Emergencies (TIAGO)

Primary Purpose

Emergencies

Status
Recruiting
Phase
Not Applicable
Locations
Spain
Study Type
Interventional
Intervention
Advanced triage tool for Gynecology and Obstetrics emergencies based on artificial intelligence algorithms.
Sponsored by
Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Emergencies

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)FemaleDoes not accept healthy volunteers

Inclusion Criteria:

  • Being over 18 years
  • Understand and accept the study procedures
  • Sign the informed consent.

Exclusion Criteria:

  • Not being able to understand the nature of the study and/or the procedures to be followed
  • Not signing the informed consent
  • Be under 18 years of age
  • Emergency level 1 through current triage system

Sites / Locations

  • Hospital de la Santa Creu i Sant PauRecruiting

Arms of the Study

Arm 1

Arm Type

Other

Arm Label

Intervention

Arm Description

Inclusion in the study will be proposed to all patients who come to the Emergency Department of the Gynecology and Obstetrics Service The planned procedures for this group are as follows: Obtaining informed consent. Sequential triage - Patients will be evaluated sequentially using the MAT system according to standard practice. Next, another professional from the center, trained in the use of the Mediktor Hospital ® tool, will perform the advanced triage in the same space, both professionals being blind to the result of each of the tools. Once the sequential triage is finished, the patient's care will be carried out according to usual clinical practice, following the triage assessment carried out with the MAT system. Retrieval and introduction of data in DRF - Data of the study variables will be retrieved from the emergency report issued in the Gynecology and Obstetrics Emergency area and will be entered into an electronic DRF for subsequent analysis and processing.

Outcomes

Primary Outcome Measures

Number of patients with equivalence between emergency triage classifications
Correspondence of emergency grading between Advanced IA Triage Tool (Mediktor Hospital) and the current triage system.

Secondary Outcome Measures

Number of patients with the same diagnosis on advanced triage tool and emergency discharge report (gold-standard)
Assess the correlation between the pre-diagnosis provided by the advanced triage tool and the diagnosis offered by the physician in the emergency discharge report.
Number of patients with good correlation between complimentary tests requested by the advanced triage tool with gold-standard
Assess the correlation between the complementary tests proposed by the advanced triage tool and those requested by the doctors during the emergency room visit, following the care protocols of the center.

Full Information

First Posted
April 28, 2022
Last Updated
May 29, 2022
Sponsor
Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
search

1. Study Identification

Unique Protocol Identification Number
NCT05382000
Brief Title
Artificial Intelligence (IA) Advanced Triage Tool for G&O Emergencies
Acronym
TIAGO
Official Title
Evaluation of an Advanced Triage Tool for Gynecology and Obstetrics Emergencies Based on Artificial Intelligence Algorithms
Study Type
Interventional

2. Study Status

Record Verification Date
May 2022
Overall Recruitment Status
Recruiting
Study Start Date
May 11, 2022 (Actual)
Primary Completion Date
August 1, 2022 (Anticipated)
Study Completion Date
December 1, 2022 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

Brief Summary
Triage represents the first opportunity to classify patients who come to an Emergency Department (ED) and to be able to identify, prioritize high-risk patients and efficiently allocate the limited resources that are available. Therefore, the purpose of triage in the ED is to prioritize patients, detecting those that are urgent (that cannot wait to be attended). Urgency is defined as that clinical situation with the capacity to generate deterioration or danger to the health or life of the patient, depending on the time elapsed between its appearance and the establishment of an effective treatment, which determines a healthcare episode with significant intervention needs in a short period of time. There are currently six triage systems or models systematically structured into 5 levels. Although simple in concept, the practice of triage is challenging due to time pressure, the limitations of available information, the various medical conditions of the patients, and a great reliance on intuition on the part of the professionals who perform it. which conditions a great variability in it. On the other hand, almost half of adult ED visits nationwide are classified as level 3 in a 5-level structured triage system, which makes level 3 a heterogeneous group with patients with diverse pathologies, in which triage is not capable of accurately differentiating them, and this inability poses safety risks for the most severely ill patients ("under-triage") and may influence the accuracy and efficiency in resource allocation when patients with low acuity are overrated. Therefore, it seems necessary to develop new triage procedures that allow us to improve their accuracy and reduce inter-individual variability. TIAGO is a prospective, single-center, observational, comparative study to determine the validity of the Mediktor ® Triage and its effectiveness with respect to the current triage system and the "gold standard" (physician's diagnosis).
Detailed Description
Prospective interventional, comparative study to determine the validity of the Mediktor ® Triage and its effectiveness with respect to "Model Andorra of Triage" (MAT) system and the "gold standard" (doctor's diagnosis). Obtaining informed consent. Participation in the study will be offered to all those patients who attend the Emergency Department of Gynecology and Obstetrics of the Hospital de la Santa Creu i Sant Pau during the study period and who meet the inclusion criteria. An information sheet on the study will also be provided to each patient. Sequential triage Once the patient's consent has been obtained, the patient will be assessed sequentially in the same triage space. Initially, a nurse from the Gynecology and Obstetrics Service will classify the patient in the triage box using the MAT system according to the usual practice. Then, another professional from the center, trained in the use of the Mediktor Hospital ® tool, and who has not been present in the conventional sorting, will perform the advanced triage in the same space, both professionals being blind to the result of each of the tools. In the event that the first triage performed with MAT gave the investigators an emergency level 1, the triage with the Mediktor tool would not be performed, since in this case the immediate care of the patient would be prioritized. Attention in the Emergency Service Once the sequential triage is completed, the patient will return to the Gynecology and Obstetrics Emergency Room. The patient's care will be performed according to usual clinical practice, following the triage assessment performed with the MAT system. Data recovery and entry in Data Recovery Form (DRF) All data of the study variables will be retrieved from the emergency report issued in the area of Gynecology and Obstetrics Emergencies and will be entered in an electronic DRF for further analysis and processing. Evaluation of Effectiveness Main evaluation variables Level of triage assigned by MAT, Level of triage assigned by Mediktor Hospital Secondary evaluation variables Affiliation variables (administrative): Date of birth, sex, residence, financing, date and time of arrival in the emergency room or administrative record, form of arrival in the emergency room (own foot, ambulance, etc.…), reason for the urgency ( common illness, traffic accident, school…). Triage variables: Triage date and time, triage duration time, coded clinical reason for consultation, readmission within 72 hours, readmission reason, triage level, number of reevaluations, triage level of each reevaluation. Care variables: date and time of the emergency room visit, request for additional test, type of additional test, analytical parameters requested (if applicable), diagnosis according to International Classification of Diseases (ICD) (primary and secondary), most important procedures performed, patient admission > 24h), date and time of admission, urgent surgery, time of stay in the emergency room (LOS) which is the time that the patient remains in the emergency room from the time of admission to the hospital until the patient is discharged or hospitalized. Number of patients admitted to the hospital and number of patients discharged. Number of emergency consultations / revisits in the first 72 hours after discharge. Variables of discharge: circumstance of discharge or reason for emergency discharge (home discharge, hospital admission, transfer to another center, voluntary discharge, escape, exit…), identification of the transfer center, date and time of discharge, date and time of administrative discharge, departure transport, cause of success, time spent in emergencies, registration canceled

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Emergencies

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Model Description
Once the patient's consent has been obtained, the patient will be assessed sequentially in the same triage space. Initially, a nurse will classify the patient in the triage box using the MAT system according to the usual practice. Then, another professional from the center, trained in the use of the Mediktor Hospital ® tool, and who has not been present in the conventional sorting, will perform the advanced IA triage in the same space, both professionals being blind to the result of each of the tools. Attention in the Emergency Service Once the sequential triage is completed, the patient will return to the Gynecology and Obstetrics Emergency Room. The patient's care will be performed according to usual clinical practice, following the triage assessment performed with the MAT system.
Masking
None (Open Label)
Allocation
N/A
Enrollment
1000 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Intervention
Arm Type
Other
Arm Description
Inclusion in the study will be proposed to all patients who come to the Emergency Department of the Gynecology and Obstetrics Service The planned procedures for this group are as follows: Obtaining informed consent. Sequential triage - Patients will be evaluated sequentially using the MAT system according to standard practice. Next, another professional from the center, trained in the use of the Mediktor Hospital ® tool, will perform the advanced triage in the same space, both professionals being blind to the result of each of the tools. Once the sequential triage is finished, the patient's care will be carried out according to usual clinical practice, following the triage assessment carried out with the MAT system. Retrieval and introduction of data in DRF - Data of the study variables will be retrieved from the emergency report issued in the Gynecology and Obstetrics Emergency area and will be entered into an electronic DRF for subsequent analysis and processing.
Intervention Type
Diagnostic Test
Intervention Name(s)
Advanced triage tool for Gynecology and Obstetrics emergencies based on artificial intelligence algorithms.
Intervention Description
After the conventional triage, a second independent doctor will make the suit with the Mediktor Hospital tool.. In less than 3 minutes and with an average of 14 questions, Mediktor performs an interrogation very similar to what an emergency doctor would do. The professional version allows the health professional to modify the course of the questions in the middle of the evaluation, if he considers it necessary to go deeper into some aspect of the anamnesis. The system allows you to see in real time the diseases that Mediktor considers possible during the evaluation. At the end of the triage process, Mediktor offers the level of urgency and a list of possible diagnoses based on the signs and symptoms answered. The professional can change the level of urgency if he considers it beneficial for the patient. Once the two triages (Conventional and Mediktor) have been carried out, the patient will be seen according to the care protocols of the center.
Primary Outcome Measure Information:
Title
Number of patients with equivalence between emergency triage classifications
Description
Correspondence of emergency grading between Advanced IA Triage Tool (Mediktor Hospital) and the current triage system.
Time Frame
3 days
Secondary Outcome Measure Information:
Title
Number of patients with the same diagnosis on advanced triage tool and emergency discharge report (gold-standard)
Description
Assess the correlation between the pre-diagnosis provided by the advanced triage tool and the diagnosis offered by the physician in the emergency discharge report.
Time Frame
3 days
Title
Number of patients with good correlation between complimentary tests requested by the advanced triage tool with gold-standard
Description
Assess the correlation between the complementary tests proposed by the advanced triage tool and those requested by the doctors during the emergency room visit, following the care protocols of the center.
Time Frame
3 days

10. Eligibility

Sex
Female
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Being over 18 years Understand and accept the study procedures Sign the informed consent. Exclusion Criteria: Not being able to understand the nature of the study and/or the procedures to be followed Not signing the informed consent Be under 18 years of age Emergency level 1 through current triage system
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Josep Estadella Tarriel
Phone
+34 652455257
Email
jestadella@santpau.cat
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Josep Estadella Tarriel
Organizational Affiliation
Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
Official's Role
Principal Investigator
Facility Information:
Facility Name
Hospital de la Santa Creu i Sant Pau
City
Barcelona
Country
Spain
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Josep Estadella
Phone
+34935537041
Email
jestadella@santpau.cat
First Name & Middle Initial & Last Name & Degree
Josep Esatdella

12. IPD Sharing Statement

Plan to Share IPD
Yes
IPD Sharing Plan Description
All data that underlie results in a publication will be available once the data analysis is completed and the publication have been published.
IPD Sharing Time Frame
All data will be available once the study is published . It will be available for 5 years after publication date.
IPD Sharing Access Criteria
Requests will be reviewed by Primary Investigator.
Citations:
PubMed Identifier
35251669
Citation
Mueller B, Kinoshita T, Peebles A, Graber MA, Lee S. Artificial intelligence and machine learning in emergency medicine: a narrative review. Acute Med Surg. 2022 Mar 1;9(1):e740. doi: 10.1002/ams2.740. eCollection 2022 Jan-Dec.
Results Reference
background
PubMed Identifier
29321109
Citation
Berlyand Y, Raja AS, Dorner SC, Prabhakar AM, Sonis JD, Gottumukkala RV, Succi MD, Yun BJ. How artificial intelligence could transform emergency department operations. Am J Emerg Med. 2018 Aug;36(8):1515-1517. doi: 10.1016/j.ajem.2018.01.017. Epub 2018 Jan 4. No abstract available.
Results Reference
background
PubMed Identifier
30795786
Citation
Raita Y, Goto T, Faridi MK, Brown DFM, Camargo CA Jr, Hasegawa K. Emergency department triage prediction of clinical outcomes using machine learning models. Crit Care. 2019 Feb 22;23(1):64. doi: 10.1186/s13054-019-2351-7.
Results Reference
background
PubMed Identifier
28888332
Citation
Levin S, Toerper M, Hamrock E, Hinson JS, Barnes S, Gardner H, Dugas A, Linton B, Kirsch T, Kelen G. Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index. Ann Emerg Med. 2018 May;71(5):565-574.e2. doi: 10.1016/j.annemergmed.2017.08.005. Epub 2017 Sep 6.
Results Reference
background
PubMed Identifier
29188913
Citation
Moreno Barriga E, Pueyo Ferrer I, Sanchez Sanchez M, Martin Baranera M, Masip Utset J. [A new artificial intelligence tool for assessing symptoms in patients seeking emergency department care: the Mediktor application]. Emergencias. 2017 Dic;29(6):391-396. Spanish.
Results Reference
background
PubMed Identifier
28751363
Citation
Kuriyama A, Urushidani S, Nakayama T. Five-level emergency triage systems: variation in assessment of validity. Emerg Med J. 2017 Nov;34(11):703-710. doi: 10.1136/emermed-2016-206295. Epub 2017 Jul 27.
Results Reference
background
PubMed Identifier
23296233
Citation
Julian-Jimenez A, Palomo de los Reyes MJ, Lain Teres N. [Coment on the original article: modelo predictor de ingreso hospitalario a la llegada al servicio de Urgencias]. An Sist Sanit Navar. 2012 Sep-Dec;35(3):493-6; author reply 497-9. doi: 10.23938/ASSN.0113. No abstract available. Spanish.
Results Reference
background
PubMed Identifier
26063343
Citation
Elias P, Damle A, Casale M, Branson K, Churi C, Komatireddy R, Feramisco J. A Web-Based Tool for Patient Triage in Emergency Department Settings: Validation Using the Emergency Severity Index. JMIR Med Inform. 2015 Jun 10;3(2):e23. doi: 10.2196/medinform.3508. Erratum In: JMIR Med Inform. 2015 Jun 15;3(3):e24.
Results Reference
background
PubMed Identifier
21843217
Citation
Storm-Versloot MN, Ubbink DT, Kappelhof J, Luitse JS. Comparison of an informally structured triage system, the emergency severity index, and the manchester triage system to distinguish patient priority in the emergency department. Acad Emerg Med. 2011 Aug;18(8):822-9. doi: 10.1111/j.1553-2712.2011.01122.x.
Results Reference
background
PubMed Identifier
19875271
Citation
Moll HA. Challenges in the validation of triage systems at emergency departments. J Clin Epidemiol. 2010 Apr;63(4):384-8. doi: 10.1016/j.jclinepi.2009.07.009. Epub 2009 Oct 28.
Results Reference
background

Learn more about this trial

Artificial Intelligence (IA) Advanced Triage Tool for G&O Emergencies

We'll reach out to this number within 24 hrs