Advanced Analytics & Patient Outcomes in Applied Behavior Analysis

Original Air Date: December 14, 2023

CEU offered: 1.5 Learning CEU

Webinar Duration: 90 minutes

CE Instructors:

  • David J. Cox, Ph.D., M.S.B., BCBA-D,


Abstract:

Patients, their caregivers, and payers often want to know exactly what they will get when receiving ABA and how long it will last. They also often want to know how they can identify ABA providers who are better at providing ABA services than other providers. However, the complexity of ABA service delivery and idiosyncratic intervention and goal design make answering questions about patient outcomes challenging.

In this presentation, we review categories of quality measurement stakeholders often seek and how advanced analytics (e.g., statistical modeling, machine learning) allow us to answer questions about patient outcomes.

Specifically, we show one way that ABA providers and payers can model and predict patient outcomes as a function of each patient’s unique clinical profile. From there, all stakeholders can identify which patients are making progress above, at, or below expectations so that relevant action can be taken accordingly.

Further, as outcome measures gain adoption, advanced analytics offer opportunities for bringing applications of artificial intelligence to bear on ABA such as ABA hours/dosage recommender systems, patient-provider matching, treatment pathway analysis, and dynamic treatment recommender systems to optimize patient outcomes.

Learning Objectives

  1. Describe the three types of quality measures and provide examples from ABA.
  2. Describe three methods for identifying patient profiles to account for clinical severity in analytics of patient outcomes.
  3. Describe how advanced analytics allow for predicting patient outcomes in ABA that can inform conversations around quality measurement, provider comparisons, and improved clinical decision-making.


Instructor(s)

David Cox

Dr. David J. Cox, Ph.D., M.S.B., BCBA-D has worked within the behavioral health industry for 17 years. He began working in behavioral health by providing and then supervising Applied Behavior Analysis (ABA) programs for individuals with autism spectrum disorders. After 8 years of clinical work, Dr. Cox went back to school to earn his Ph.D. in Behavior Analysis from the University of Florida, Post-Doctoral Training in Behavioral Pharmacology and Behavioral Economics from Johns Hopkins University School of Medicine, and Post-Doctoral Training in Data Science from the Insight! Data Science program. Since 2014, Dr. Cox’s research and applied work has focused on how to effectively leverage technology, quantitative modeling, and artificial intelligence to ethically optimize behavioral health outcomes and clinical decision-making. Based on his individual and collaborative work, he has published 45+ peer-reviewed articles, four books, and 150+ presentations at scientific conferences.