Since the launch of Chat GPT in 2022, the integration of artificial intelligence (AI) into healthcare is inevitable. While the utilization of AI will streamline processes, improve efficiencies, save time, and eliminate waste for many subspecialties like radiology, anesthesiology, primary care, and others, many have questioned how this will be employed in more subjective disease states like psychiatry and acute and chronic pain care. Basically, “Can the subjective become objective?” One challenge with subjective assessments is that their interpretation is ripe for racial, gender, and class-based bias. Sadly, biased assessments lead to disparities in care. While there are countless attempts to mitigate these disparities through education, training, and algorithmic care, these disparities still exist and are often linked to the implicit biases of the provider.
What happens if the assessor is removed and replaced with artificial intelligence?
In this talk, we will review the novel uses of AI and other objective, validated, physiologic based technologies in pain assessment. We will also examine the current research behind the use of AI to assess pain via voice, facial expressions, sympathetic tone, brain waves, and spinal cord electrical activity. Lastly, we will discuss how objectifying this process can improve patient outcomes by eliminating the primary source of bias, us.
Learning Objectives:
Analyze the potential impact of artificial intelligence (AI) integration in healthcare, with a focus on its role in pain assessment.
Evaluate the challenges and opportunities of utilizing AI technology in subjective disease states like pain management.
Investigate the ethical considerations around using AI to mitigate biases based on race, gender, and social class in healthcare, and discuss the implications of shifting towards more objective assessment methods in improving care equity.
Evaluate how AI can address biases in subjective assessments by exploring its applications in various physiological indicators such as voice, facial expressions, and brain waves.
Examine how AI can enhance objectivity in pain assessment, potentially improving patient outcomes by reducing provider-related biases and disparities in care.
