We Did It! Better Outcome Insights by Partnering Design and AI

Session Description: In designing continuing education, the ultimate goal is to positively impact patient outcomes. The World Health Organization (WHO) reports that 80% of patient health outcomes are due to non-medical social factors, with only 20% resulting from medical care or interventions. Therefore, understanding the interrelationship between social determinants of health (SDOH) and patient outcomes is crucial for designing effective continuing education.

Inspired by this fundamental concept, we developed an online module titled ‘Social Determinants of Health and Pain Management.’ This module examines pain management through the lens of social determinants of health, using several strategies designed to improve both the quality and quantity of learners’ commitment to change. Our preliminary commitment to change response rate has improved to approximately 90% responding to at least a broad commitment. Half of those with broad commitments have elaborated in detail regarding the specific changes they intend to make.

The literature indicates that reflective learning and reflective practice are important characteristics for professional competence among healthcare practitioners (1,2). Reflective learning enables healthcare practitioners to thoughtfully consider their clinical environments and practices, which can, in turn, influence behavior change (3). Guided self-reflection was one of the key strategies used in our design process.

In this workshop, we will discuss how integrating SDOH, along with our application of reflective and case-based learning, influenced our outcomes data. We'll share some of the strategies behind our design process and demonstrate how this project has led to changes in the knowledge, skills, and attitudes of healthcare professionals. We will explore the importance of guided self-reflection in lifelong learning and discuss ways to integrate it into the design to improve learner-reported commitment to change. As we walk through how guided self-reflection was used in our project, participants will also have opportunities to reflect on their own experiences. We are confident that all involved in this workshop will walk away with innovative solutions to improve outcomes data through collaborative learning.

We are excited to share our findings with our colleagues as we continue to gather more data on this module throughout the end of the year. As artificial intelligence (AI) becomes increasingly prevalent in our professional landscape, we aim to leverage AI tools to analyze the data we have collected. We will discuss how we utilized AI to assess our program and share the prompts that guided this process. Additionally, during the workshop, participants will have the opportunity to use AI tools to analyze sample data, gaining practical experience they can apply to their own projects.