Increasing Efficiency and Efficacy of Electronic Health Record Onboarding with Cognitive Adaptive Technology

Purpose: Informatics educators and instructional designers at Stanford Health Care optimized our electronic health record (EHR) onboarding education of new providers and nurses by adopting cognitive, adaptive technology to increase learning efficiency and efficacy.

Background/significance: Most providers and staff enter our organization with prior EHR experience. Our goal was to optimize the onboarding program to include adaptability based on expertise and get the clinician to the bedside faster. We needed our learning methodology and technology to measure competency and capture analytic reporting for post-class personalized coaching.

Method: Six onboarding courses were chosen for a pilot, including five provider courses and one nursing course. We used a blended learning approach (synchronous and asynchronous learning) and the cognitive adaptive technology (CAT) (Amplifire authoring software) to create curriculum capable of adapting to the learner’s prior knowledge of the EHR. The CAT tests the learner’s comprehension, and the learner cannot complete the eLearning without demonstrating complete mastery. Post-eLearning completion analytics captures topic areas of struggle, which allows educators to provide personalized follow-up education.

Results: eLearning training time for providers was reduced by approximately one hour (2.5 hours reduced to 1.5 hours). Classroom time was reduced from 4 -16 hours (based on specialty) to 2 hours across specialties. Our inpatient RN course (nurses with experience in the EHR) was reduced from 4 hours of classroom time to 2 hours of self-paced learning. In our post-class surveys, learners report a positive experience

Conclusion/implications: Our optimization of EHR onboarding reduced training time.