Abstract

Utilizing Artificial Intelligence in Emergency-Department-Based Screening and Brief Intervention (SBI)

Author: Shashank Somasundaram

Nearly 1 in 12 American adults suffer from alcohol dependence, of which over 80,000 die annually from alcohol-related injuries. 2 million people suffer from prescription opioid addiction, of which over 40,000 die of overdose each year. The rise of the opioid epidemic has led to a corresponding increase in addiction, traffic collisions, overdoses and deaths. Measures have been taken to reduce over-prescription of opiates, but with little impact. Efforts to educate the population about the dangers of general substance abuse have been largely limited by a shortage of human capital and time. A rapidly popularizing alternative to in-person screening and intervention is using technology to blanket-screen select populations, such as emergency department patients. For instance, one research study at the UCIMC ED screens all trauma patients for risk of alcohol dependence. Another study seeks to better educate patients receiving opiates about the dangers and proper disposal of medication. While these computerized brief intervention programs in drug and alcohol abuse have been promising, they have yet to demonstrate that screening and brief intervention (SBI) is more effective by automation than in-person. The intricacies and nuances of a tailored discussion on substance abuse are a far call even from the most advanced programs available today. One way to revolutionize public health and the field of personalized medicine, is the development of an electronic tool to effectively obtain patient history, tailor recommendations to specific scenarios, and create an appropriate strategic action plan. A wide-spread implementation of this technology would translate into seamless care for patients, and facilitate public awareness, lowered costs, both in prevention and long-term treatment, as well as lowered substance abuse. Many small advances have been made on various fronts of preventative medicine. The integration of these diagnostic tools into a single, comprehensive technological SBI interface may prove to be a worthy foray into the future of personalized medicine at the emergency-department level.