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Accelerating Competency Development with AI

October 3, 2023
October 3, 2023

This blog Is taken from a recent HealthStream webinar entitled "jane, Accelerating Competency Development with AI." The webinar was moderated by Jill Lamle, Campaign Marketing Manager for Competency and featured:

  • Trisha Coady, BSN, RN, Senior Vice President, Workforce Development
  • Jill Benns, MSN, MBA, Alum PCCN, NPD-BC, Managing Editor, Clinical Competency
  • Kelly Aldrich, DNP, MS, RN-BC, FHIMSS, FAAN, Informatics Nurse Specialist

After engaging many clinical leaders and educators across the country, HealthStream deployed a multi-year investment in the design of a patented, evidence-based competency development system. More than ever, objective evaluation and standardization are critical to ensure safe care delivery. The results of this process will allow leaders to leverage technology to assess and improve both clinical knowledge and judgement

 

Data Trends in Competency

Aldrich began by sharing the current state of competency in the post-pandemic healthcare environment and the importance of evolving competency solutions even as learners themselves continue to evolve. She cited a recent study that found that up to 65% of adverse patient events could have been prevented if nurses had made better decisions. This finding highlights the importance of, not just knowledge, but skills and clinical judgement. 

The same study found that less than 20% of employers believe that their new hires have the clinical judgement skills required to make safe and effective decisions. 

However, putting everyone on the same learning path is not the best solution even though, until now, it has been extremely difficult to personalize a learner’s educational journey to ensure both patient safety and learner satisfaction. Aldrich also pointed out that the current staffing situation in healthcare means that whatever time is spent on education must be purposeful and able to remediate gaps in knowledge and judgement.

 

Leveraging Technology and AI

Aldrich went on to describe the three elements of developing competency and the role of AI in supporting that development.

  • Knowledge: Evaluate what each nurse knows, develop those skills with cognitive software, and validate the knowledge and knowledge acquisition.
  • Skills: Evaluate and develop skills through the use of cognitive courseware.
  • Judgement: Evaluate how well nurses make decisions and develop that skill through the use of preceptor tools and simulation.

Assessing knowledge, evaluating and developing skills and clinical judgement is challenging, but technology offers a safe, effective and efficient means to improve the processes for all three elements of competency development. Aldrich, who is on the Board of the American Nurse Association Innovation Council shared that in addition to the staffing issues, the council is also looking at the well-being of the healthcare workforce. Attracting and retaining nurses has never been more important, and technology and automation can help.

 

Assessing Clinical Judgement

jane is a resource that combines knowledge assessments, critical thinking assessments and an extensive CE library to support learners with an individualized learning program. As jane was in development, developers noticed a discrepancy between clinical knowledge and clinical judgement scores. The average score for knowledge assessments was 72% while the score for clinical judgement trailed significantly at 57%. The significantly lower scores in clinical judgement can help inform where educators put their attention and resources for improvement.

As clinical judgement and safety are so closely correlated, Aldrich pointed out that it is important to not burden clinicians with outdated educational models. Rather, leaders should consider more effective and positive ways in which to improve performance and to measure, monitor and evolve the ways in which we build competency.

 

The Future of Targeted Competency Development

An understanding of the modern learner is essential to competency development. Benns shared some of their characteristics. Modern learners are:

  • Struggling to balance job responsibilities, remote work technology and work-life balance leaving them with little time for learning.
  • Facing interruptions, multiple job responsibilities, and time constraints that have created shorter attention spans – most will stop watching a video at the 4-minute mark.
  • Motivated to develop professionally at their own pace and their mobility and passion for learning have led them to a career span of just 5-10 years – considerably shorter than what is typically seen in nursing.

Benns shared that these characteristics mean that individualization, debriefing and self-reflection need to be the new cornerstones for learning management. Technology enables learners to practice their skills and their judgement with tools like AI, bots and simulation environments. These kinds of technologies enable educators to capture the results of those interactions, measure results and recommend the educational path to improvement. AI helps to eliminate some non-critical tasks and helps to focus on what is essential to improvement.