Human Algorithm Interactions for Acute Respiratory Failure Diagnosis

University of Michigan

Status: Completed

Conditions: Acute Respiratory Failure

Treatments: Other: AI model biased against pneumonia; Other: AI model biased against COPD; Other: Artificial intelligence model predictions with explanation; Other: AI model biased against heart failure; Other: Artificial Intelligence model predictions without explanation

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT06098950

HUM00180745

R01HL158626 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

Artificial intelligence (AI) shows promising in identifying abnormalities in clinical images. However, systematically biased AI models, where a model makes inaccurate predictions for entire subpopulations, can lead to errors and potential harms. When shown incorrect predictions from an AI model, clinician diagnostic accuracy can be harmed. This study aims to study the effectiveness of providing clinicians with image-based AI model explanations when provided AI model predictions to help clinicians better understand the logic of an AI model's prediction. It will evaluate whether providing clinicians with AI model explanations can improve diagnostic accuracy and help clinicians catch when models are making incorrect decisions. As a test case, the study will focus on the diagnosis of acute respiratory failure because determining the underlying causes of acute respiratory failure is critically important for guiding treatment decisions but can be clinically challenging.

To determine if providing AI explanations can improve clinician diagnostic accuracy and alleviate the potential impact of showing clinicians a systematically biased AI model, a randomized clinical vignette survey study will be conducted. During the survey, study participants will be shown clinical vignettes of patients hospitalized with acute respiratory failure, including the patient's presenting symptoms, physical exam, laboratory results, and chest X-ray. Study participants will then be asked to assess the likelihood that heart failure, pneumonia and/or Chronic Obstructive Pulmonary Disease (COPD) is the underlying diagnosis. During specific vignettes in the survey, participants will also be shown standard or systematically biased AI models that provide an estimate the likelihood that heart failure, pneumonia and/or COPD is the underlying diagnosis. Clinicians will be randomized see AI predictions alone or AI predictions with explanations when shown AI models. This survey design will allow for testing the hypothesis that systematically biased models would harm clinician diagnostic accuracy, but commonly used image-based explanations would help clinicians partially recover their performance.

Enrollment: 457 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Physicians, nurse practitioners, and physician assistants that care for patients with acute respiratory failure as part of their clinical practice

Exclusion criteria

• Physicians, nurse practitioners, and physician assistants that only provide patient care in outpatient settings

Trial design

Primary purpose: Other

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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457 participants in 6 patient groups

AI model biased for heart failure, no AI explanation

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against heart failure, always predicting that heart failure is present with high likelihood in patients with a body mass index (BMI) at or above 30. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will not be shown an AI explanation when shown AI model predictions.

Treatment:

Other: AI model biased against heart failure

Other: Artificial Intelligence model predictions without explanation

AI model biased for pneumonia, no AI explanation

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against pneumonia, always predicting that pneumonia is present with high likelihood in patients 80 years or older. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will not be shown an AI explanation when shown AI model predictions.

Treatment:

Other: AI model biased against pneumonia

Other: Artificial Intelligence model predictions without explanation

AI model biased for COPD, no AI explanation

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against COPD, always predicting that COPD is present with high likelihood when a pre-processing filter was applied to the patient's X-ray. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will not be shown an AI explanation when shown AI model predictions.

Treatment:

Other: Artificial Intelligence model predictions without explanation

Other: AI model biased against COPD

AI model biased for heart failure, Image-based AI explanation presented

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against heart failure, always predicting that heart failure is present with high likelihood in patients with a body mass index (BMI) at or above 30. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will also be shown AI explanation when shown AI model predictions.

Treatment:

Other: AI model biased against heart failure

Other: Artificial intelligence model predictions with explanation

AI model biased for pneumonia, Image-based AI explanation presented

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against pneumonia, always predicting that pneumonia is present with high likelihood in patients 80 years or older. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will also be shown AI explanation when shown AI model predictions.

Treatment:

Other: AI model biased against pneumonia

Other: Artificial intelligence model predictions with explanation

AI model biased for COPD, Image-based AI explanation presented

Experimental group

Description:

Participants in this arm will be shown standard AI model predictions during 3 patient clinical vignettes within the survey and systematically biased AI model predictions during 3 clinical vignettes. When shown systematically biased AI model predictions, the model will be biased against COPD, always predicting that COPD is present with high likelihood when a pre-processing filter was applied to the patient's X-ray. Standard predictions will be shown for the other 2 diagnoses. Participants in this arm will also be shown AI explanation when shown AI model predictions.

Treatment:

Other: AI model biased against COPD

Other: Artificial intelligence model predictions with explanation