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Effects of Expert Arbitration on Clinical Outcomes When Disputes Over Diagnosis Arise Between Physicians and Their Artificial Intelligence Counterparts: a Randomized, Multicenter Trial in Pediatric Outpatients

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ClinicalTrials.gov Identifier: NCT04011761
Recruitment Status : Not yet recruiting
First Posted : July 8, 2019
Last Update Posted : July 8, 2019
Sponsor:
Information provided by (Responsible Party):
Huiying Liang, Guangzhou Women and Children's Medical Center

Brief Summary:
We have recently developed an artificial intelligence (AI) framework to diagnose common pediatric diseases. This randomized controlled clinical trial aims to investigate the effects of expert arbitration on clinical outcomes in the situation where the AI-based diagnosis differs from the diagnosis made by pediatricians.

Condition or disease Intervention/treatment Phase
Pediatric Outpatients Encountered in Three Specialty Clinics, i.e. Respirology, Gastroenterology, and Genito-urology Other: expert arbitration over discordant diagnoses made by AI diagnostic system and human doctors, respectively Not Applicable

Detailed Description:
Based on the historical clinical data of more than 1 million pediatric outpatients in the Guangzhou Women and Children's Medical Center, an AI diagnostic framework has recently been developed for common pediatric diseases [Liang H et al. evaluation and accurate diagnosis of pediatric disease using artificial intelligence. Nat Med. 2019;25(3):433-8]. This AI framework utilizes predefined schema to extract informative clinical data from free text and reaches clinical diagnoses by hypothetico-deductive reasoning. In internal validation, the AI system showed accuracy rates ranging from 0.85 for gastrointestinal disease to 0.98 for neuropsychiatric disorders, suggesting that it might be a promising assisting diagnostic tool in clinical practice. However, there is a lack of evidence-based strategy on how to handle the scenarios where the AI-based diagnosis and the diagnosis made by pediatricians are discordant. It is legitimate to assume that diseases with discordant diagnoses present more similar clinical features; in this case it is necessary to introduce an extra arbitrator for differential and decisive diagnosis. Therefore, we conduct this randomized controlled trial to: 1) compare the accuracy of the two diagnostic modes in a real-world clinical setting where the AI-based diagnosis and the diagnosis made by pediatricians are discordant by introducing an expert arbitrator; and 2) look further into the change of clinical outcomes (hospital revisit and hospitalization in the next 3 months after initial visit; average total outpatient cost) due to introduction of the expert arbitrator. Please note that although the aforementioned AI framework was designed for diagnosis of a wide range of diseases, this clinical trial is limited to outpatients encountered in three specialty clinics, i.e. respirology, gastroenterology, and genito-urology. The reason for this selection is that the discordant diagnoses are assumed to be more common for these two specialties according to the internal validation result.

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 10000 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description: parallel assignment
Masking: None (Open Label)
Primary Purpose: Treatment
Official Title: Effects of Expert Arbitration on Clinical Outcomes When Disputes Over Diagnosis Arise Between Physicians and Their Artificial Intelligence Counterparts: a Randomized, Multicenter Trial in Pediatric Outpatients
Estimated Study Start Date : November 1, 2019
Estimated Primary Completion Date : October 31, 2020
Estimated Study Completion Date : April 30, 2021

Arm Intervention/treatment
Active Comparator: Experimental Arm
Each participant receives two diagnoses: one from the AI diagnostic system and the other from pediatricians, and the two diagnoses are discordant. Participants in the experimental arm will be referred to an expert arbitrator for differential and decisive diagnosis and will receive treatment prescribed by the expert arbitrator.
Other: expert arbitration over discordant diagnoses made by AI diagnostic system and human doctors, respectively
Each participant receives two diagnoses: one from the AI diagnostic system and the other from pediatricians, and the two diagnoses are discordant. Participants in the experimental arm will be referred to an expert arbitrator for differential and decisive diagnosis and will receive treatment prescribed by the expert arbitrator.

No Intervention: Control Arm
Each participant receives two diagnoses: one from the AI diagnostic system and the other from pediatricians, and the two diagnoses are discordant. Participants in the control arm will receive treatment prescribed by pediatricians.



Primary Outcome Measures :
  1. Hospital revisit [ Time Frame: The next 3 months after the initial visit ]
    Within the first 3 months after the initial visit, active follow-up via phone call will be performed each month to collect the information on hospital revisit.

  2. Hospitalization in the next 3 months after the initial visit [ Time Frame: The next 3 months after the initial visit ]
    be performed each month to collect the information on hospitalization.

  3. Average total outpatient cost [ Time Frame: The next 3 months after the initial visit ]
    be performed each month to collect the information on the amount of money spending on healthcare.


Secondary Outcome Measures :
  1. Accuracy rate of AI-based diagnosis and accuracy rate of the diagnoses made by pediatricians, using the diagnoses made by the expert arbitrator as the decisive diagnoses. [ Time Frame: The next 3 months after the initial visit ]
  2. Counseling time spent with each patient [ Time Frame: The next 3 months after the initial visit ]


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Ages Eligible for Study:   up to 18 Years   (Child, Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  1. Outpatients who visits the respirology clinics or the gastroenterology clinics during the recruitment period.
  2. Written informed consent is provided by parents/guardians

Exclusion Criteria:

1. Patients with any conditions that require immediate diagnosis and treatment.


Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04011761


Contacts
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Contact: Huiying Liang, PhD +86-20-3885-7692 lianghuiying@hotmail.com
Contact: Kuanrong Li, PhD +86-20-33857716 lik@gwcmc.org

Locations
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China, Guangdong
Guangzhou Women and Children's Medical Center
Guangzhou, Guangdong, China, 510623
Contact: Huiying Liang, PhD    +86-20-3885 7692    lianghuiying@hotmail.com   
Contact: Kuanrong Li, PhD    +86-20-3885 7716    lik@gwcmc.org   
Sponsors and Collaborators
Guangzhou Women and Children's Medical Center
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Responsible Party: Huiying Liang, Group Head, Guangzhou Women and Children's Medical Center
ClinicalTrials.gov Identifier: NCT04011761    
Other Study ID Numbers: aiwcmc
First Posted: July 8, 2019    Key Record Dates
Last Update Posted: July 8, 2019
Last Verified: June 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No