Healthcare Course Catalog

Course content has been co-developed and efficacy-tested by co-development partners at renowned Health Systems across the country. Course content can be quickly deployed as is, or there are opportunities to develop new course content, supported by a dedicated content and design team.

On The Floor Faster, Better Patient Care

Intermountain Health Saint Joseph Hospital’s Nurse Onboarding Overhaul

In 2022, Intermountain Health Saint Joseph Hospital, formerly SCL Health, faced resource-straining onboarding processes and wanted to reduce nurse turnover. To address these challenges, a revamped onboarding strategy was implemented, featuring a standardized approach and the integration of Amplifire’s adaptive e-learning platform. This overhaul was aimed at enhancing efficiency, reducing training time, and improving patient outcomes.

Intermountain Health Saint Joseph Hospital’s streamlined onboarding process now serves as a benchmark for other healthcare organizations, demonstrating how adaptive e-learning can facilitate quicker onboarding, smarter learning, and better patient care.

Redefining Epic Training in Healthcare

How UCHealth Eliminated Misinformation through Personalized Learning Paths

Traditionally, EHR onboarding training follows a “one-size-fits-all” approach, which fails to address the individual learning needs of both new and experienced clinicians and directly contributes to clinician dissatisfaction and burnout. Learn how UCHealth, a nationally recognized network of 14 hospitals and more than 33,000 employees, reimagined their EHR onboarding and training program to better meet their providers’ needs by partnering with Amplifire.

Download the study to learn more.

6 Key Takeaways from the Becker’s Webinar on Personalized EHR Onboarding

Discover why adaptive, personalized learning is essential for ensuring both new and experienced Epic users get the training they need to optimize performance and patient care.

For healthcare leaders seeking to boost efficiency and satisfaction among their clinicians, EHR onboarding presents a tremendous opportunity for improvement. Personalization has become the key to enhancing the learning experience, addressing the specific needs of individual learners, and improving their proficiency. In the recent Becker’s webinar, Kelley Williamson of UCHealth shared how allowing physicians to choose their own onboarding journey improved physician satisfaction and provided UCHealth with the data they needed to make informed decisions.

As Anne Hyland, Senior Director of Healthcare Client Solutions and EHR Program Director at Amplifire, explained during the webinar, “Personalized EHR Onboarding: Data-Driven Strategies for Efficiency and Satisfaction”, healthcare training is inherently time-consuming, resource-intensive, and costly. Trainers often face the challenge of balancing the need to cover all the necessary material l while reducing the time it takes to do so to facilitate training efficiency. Amplifire’s approach digs deeper into learning personalization for EHR onboarding, revealing some unexpected truths about even the most experienced EHR users.

Here are six key takeaways from this insightful webinar to consider when evaluating the efficacy of your EHR training program:

1. One-size-fits-all Training Falls Short of Addressing Individual Needs

Healthcare organizations have long relied on standardized training methods, but one-size-fits-all approaches often fail to meet the unique needs of diverse learners. In large health systems, the user base consists of individuals with varied experiences, roles, and specialties. A standard training program cannot cater to the specific knowledge gaps and responsibilities of each individual.

Take UCHealth, for example. Their providers—one of the most expensive and valuable resources within the system—were vocally dissatisfied with their previous “click-through-for-credit” learning system and lengthy, required in-person session. This approach left learners disengaged and underprepared to navigate the complexities of their EHR. Despite having completed their training, errors persisted in crucial tasks like admissions, discharges, and transfers. These mistakes ultimately impacted the overall efficiency of the health system and patient care.

The lesson here is clear: generic training methods don’t account for the nuances of individual workflows or knowledge gaps. A more tailored, data-driven approach is required to ensure that clinicians not only complete the training but truly master the system.

2. In-Application and At-the-Elbow Training Are Not Enough for True Mastery

Many healthcare organizations employ at-the-elbow support and in-application guides to assist clinicians during the onboarding process. While these tools provide assistance in real-time, they fall short when it comes to deeper, personalized learning. These forms of support may address immediate questions or provide orientation but lack the scientific rigor needed to ensure long-term retention and mastery of the EHR system.

Amplifire’s approach goes beyond this, using adaptive learning methodologies grounded in cognitive science. Brain science-based learning techniques focus on improving retention through strategies such as spaced repetition, confidence-based assessments, and active recall. These methods have been shown to help learners retain knowledge longer, learn faster, and apply information more accurately.

Adaptive learning personalizes the training process to each user’s unique needs, ensuring that they not only complete online training but also remember how to accurately navigate the EHR when they are back on the floor. 

3. Experienced Clinicians May Require More Training Than Expected

One of the most surprising findings from UCHealth’s EHR training journey was that Epic-experienced clinicians exhibited just as much “confidently held misinformation^®” (CHM^®) as new users that just completed other online EHR learning. CHM^® occurs when users are confident in their knowledge but are, in fact, mistaken. This is particularly dangerous in clinical environments where confidence can lead to incorrect actions that impact patient outcomes.

At UCHealth, Amplifire analyzed data from around 1,800 learners and uncovered nearly 18,000 instances of CHM^® across both experienced and novice users, and the CHM^® for those that had just complete other online training on the exact content only had a reduced level of CHM^® by a couple of percentage points. This indicates that prior exposure to the EHR system does not always correlate to efficient and accurate EHR use, nor just traditional online learning. Even seasoned users who have been working with the EHR for years may develop inaccurate shortcuts, gain unreliable tribal knowledge, or rely on outdated processes. Based on the data, even those that had just spent time learning the EHR displayed only 55% confidently correct knowledge.  

Matt Hays, Amplifire’s VP of Research and Analytics, stressed the significance of this finding: “Regardless of their previous experience or recent training, learners still had almost 18,000 things that would have been mistakes had they not been corrected.” This demonstrates the critical need for personalized training that identifies and rectifies these hidden knowledge gaps.

4. Amplifire Uniquely Identifies and Corrects Confidently Held Misinformation^®

Amplifire stands out in its ability to detect CHM^® at an individual level and correct it effectively, making it a vital tool for personalized learning. The platform uses an algorithm based on cognitive science research to identify instances where learners are confident in incorrect information. This is a game-changer for healthcare organizations, where traditional training platforms often overlook these hidden areas of misunderstanding.

The power of Amplifire lies in its capacity to uncover these dangerous gaps and then correct them in a way that ensures long-term retention. The algorithm does this by leveraging cognitive triggers like delayed feedback, priming, spacing, and repetition among others.

As Matt Hays noted, “The Amplifire algorithm leverages research in cognitive science, especially phenomena that run counter to how it feels like teaching works best or how it feels like learning is most effective.” In other words, the system uses evidence-based methods that may not always feel intuitive but are proven to correct misinformation and help people learn faster and remember longer.

5. Personalized Learning Saves Time While Enhancing Effectiveness

A common concern about personalized learning is that it might be more time-consuming than traditional methods. However, Amplifire’s adaptive learning platform actually accelerates the training process. By focusing only on the material that learners don’t already know or are unsure about, the platform allows them to bypass unnecessary content and spend their time more efficiently.

This efficiency translates into shorter training times without sacrificing quality. Clinicians are able to achieve mastery faster because they aren’t wasting time on concepts they’ve already learned or trudging through generalized content. For healthcare organizations, this means less time spent in training and more time for clinicians to focus on patient care and billable hours.

6. Satisfied Clinicians Lead to Improved Patient Care and Operational Efficiency

The ultimate goal of personalized EHR onboarding is to make clinicians more efficient in their use of the EHR system. When clinicians can quickly and accurately navigate the system, they have more time to dedicate to patient care. This, in turn, contributes to better patient outcomes and increased clinician satisfaction. Based on data from KLAS Arch Collaborative, the initial EHR onboarding experience directly correlates to clinician satisfaction metrics, giving health systems a key opportunity to make a difference for their providers’ wellbeing.

Before implementing Amplifire, 71% of UCHealth clinicians reported negative experiences with one-size-fits-all training. With personalized learning, however, their training was streamlined, focused, and respectful of their existing knowledge and expertise. Kelley Williamson shared how providers described their improved learning experience, “They love to be able to say, ‘Let me take my time or let me speed up. And I don’t have to sit in the classroom where the instructor is going through step by step.’ And that’s a really huge satisfier.” And this shift not only improved their satisfaction with the training process but also had a trickle-down effect, improving overall healthcare delivery. 

For healthcare systems that value clinician time, well-being, and patient care, personalized learning through Amplifire is an essential tool for achieving both operational efficiency and high-quality care.

UCHealth’s adoption of Amplifire’s adaptive learning platform illustrates the profound impact of personalized, data-driven training on clinician performance and satisfaction. By addressing confidently held misinformation, speeding up the learning process, and tailoring the experience to individual needs, Amplifire has helped UCHealth improve operational efficiency and boost clinician satisfaction. To learn more about how UCHealth transformed their EHR onboarding process with Amplifire, access the webinar recording and see how personalized learning can revolutionize your organization’s approach to training.

Personalized EHR onboarding: Data-driven strategies for efficiency and satisfaction

Beckers Webinar, September 2024

Nearly half of physicians continue to be affected by burnout, according to recent findings from the American Medical Association. Reducing the administrative burden and operational inefficiencies faced by physicians, including those related to the EHR, remains a crucial priority for hospitals and health systems. 

Leaders from Aurora, Colo.-based UCHealth understand that supporting physicians’ well-being starts on day one. During this live virtual session, experts will discuss how allowing physicians to choose their own onboarding journey improved new physician satisfaction at UCHealth, and how adaptive learning provides flexibility, efficiency, and confident mastery of the EHR.

Featuring:

PANELISTS:
Kelley Williamson
Director, IT, UCHealth 

Matthew Hays, PhD.
VP, Research and Analytics, Amplifire

MODERATOR:
Anne Hyland, Healthcare Client Solutions, Amplifire  

Fill out the form below to watch the webinar:

How Innovative EHR Training Can Improve Clinician Well-being

Healthcare is experiencing widespread burnout. Through extensive research, a group of healthcare organizations committed to improving the EHR experience through shared research, standardized surveys, and benchmarking, has identified EHR-related factors as burnout contributors. But the good news is, pinpointing specific EHR experience factors, like tool inefficiency, lack of training, poor proficiency, allows for directed intervention and improvement. 

Hear how experts delve into the realm of EHR training, sharing insights on successful strategies and pitfalls to avoid. 

Featuring:

PANELISTS:
Jenna Anderson
Strategy and Operations Director, Arch Collaborative 

Erin Banaszak
Supervisor, PROpel Team, Enterprise Clinical Informatics, Froedtert

MODERATOR:
Anne Hyland, EHR Program Director, Amplifire  

Fill out the form below to watch the webinar:

Transforming Initial EHR Education: A Partnership between UW Medicine, Tegria, and Amplifire

Summary: UW Medicine’s EHR Education Plan

Case Study from KLAS Arch Collaborative

In 2022, UW Medicine faced a staffing crisis with high turnover rates, so they undertook a comprehensive review of their onboarding training program. Recognizing the need to expedite clinician onboarding without compromising quality, UW Medicine evaluated traditional eLearning as well as adaptive learning, which combines adaptive functionality with cognitive, science-based techniques to expedite the learning process, forge long-lasting retention, and promote seamless real-world applications. They made the strategic decision to adopt adaptive learning and partnered with Amplifire.

The Amplifire platform offers proficient clinicians a faster path to progression, and those who need more support receive a personalized learning experience. Amplifire’s analytics also provide insights into learner performance and content effectiveness. The implementation occurred in phases, guided by a steering committee and supported by Tegria. Tegria played a pivotal role by advising, curriculum mapping, mentoring, authoring content, and facilitating feedback sessions. Since the Amplifire implementation, the platform has revealed knowledge disparities, saved significant time, and generated positive learner feedback. The success of the phased approach, resource allocation, and collaboration between UW Medicine and Tegria contributed to Amplifire’s effectiveness in addressing the staffing crisis and improving onboarding efficiency.

Background

Findings

How UW Medicine benefitted from the Amplifire implementation:

• Amplifire analytics: These analytics gave visibility into learner knowledge, revealing a blend of confidently held misinformation, uncertainty, and mastery across different courses. This information brought to light that many people would have gone to the floor unprepared.
• Time savings: UW Medicine’s instructor-led courses were up to eight hours long, but once the content was transformed and placed into Amplifire, a learner’s training time was trimmed to an average of two hours. This information led the teams to realign UW Medicine’s onboarding training strategy and timeline, figuring out how to optimally use the extra time and send clinicians to the floor faster.
• Learner feedback: The feedback collected via surveys was overwhelmingly positive. The main themes from the learners’ feedback included these points:
  • The Amplifire training saved time because clinicians no longer had to review content they already knew
  • Learners gained UW Medicine–specific knowledge
  • Individuals who were skeptical of the new platform recognized its value since the system conveniently walked them through the necessary tools

About KLAS

KLAS is a data-driven company on a mission to improve the world’s healthcare by enabling provider and payer voices to be heard and counted. Working with thousands of healthcare professionals, KLAS collects insights on software, services and medical equipment to deliver reports, trending data and statistical overviews. KLAS data is accurate, honest and impartial. The research directly reflects the voice of healthcare professionals and acts as a catalyst for improving vendor performance.

To learn more about KLAS and the insights we provide, visit KLASresearch.com

Amplifire, new member of the KLAS Arch Collaborative, shares exciting results around EHR training at 2023 Learning Summit

BOULDER, Colo., Aug. 2, 2023 /PRNewswire/ — Knowledge Factor, Inc. (“Amplifire“), the leading adaptive eLearning and content creation platform leveraging advances in brain science, and sponsor of the Healthcare Alliance, a growing consortium of over 25 world-renowned U.S. health systems, was honored to present at the 2023 KLAS Arch Collaborative Learning Summit in Salt Lake City, Utah, sharing results around electronic health records (EHR) training. As a new member of the Arch Collaborative, Amplifire joins hundreds of healthcare organizations revolutionizing healthcare quality by improving the EHR training experience. The Summit was Amplifire’s first opportunity to contribute to this initiative through partnerships and shared performance data.

Anna Eissenberg, Client Engagement Director, Amplifire, and Lindsay Coffman, Interim Director Clinical Informatics Education and Adoption, Providence, presented “Reimagining Epic Onboarding with Cognitive Science and Data.” Providence shared their transition from in-person training to online learning as part of a blended learning strategy with Amplifire to remedy costly training that lacked data insights. For inpatient nursing, they achieved a 41-48% training time reduction, saving $667,317 in Q1 2023. Learner analytics identified knowledge gaps and helped optimize the training experience and improve course content. Notably, clinician satisfaction metrics improved.

At the Learning Summit, a presentation by University of Washington and Tegria Healthcare & Technology Services also highlighted results from Amplifire-based EHR training. Keynote speaker Dr. Brent James, Amplifire Clinical Innovations Advisory Board Chairman, discussed tools that drive dramatic clinical change.

“The Amplifire team was thrilled that Healthcare Alliance members, Providence and UW Medicine, shared their insight among other thought leaders within the Arch Collaborative. Peer-to-peer guidance and inspiration are hallmarks of the Learning Summit, and Amplifire is gratified to empower a growing number of innovative health systems. Like KLAS, Amplifire is committed to improving caregiver wellness by enhancing training effectiveness and the learner experience,” noted Dr. Bryan Bushick, General Manager, Healthcare Alliance, and Amplifire’s Chief Healthcare Innovation Officer.

“KLAS is thrilled to have Amplifire as a part of the Arch Collaborative community and looks forward to measuring Amplifire’s impact on clinician experience. As a provider-led effort, the Arch Collaborative is supported by EHR vendors, professional services firms, and third-party education tools, like Amplifire, to share, learn, and improve the healthcare industry,” said Jenna Anderson, Strategy and Operations Director, Arch Collaborative.

Amplifire was also included in the recent KLAS report “EHR Education Software and Services: A Guide to Vendor and Firm Offerings.”

About Amplifire
Amplifire is a next-generation learning platform with more than four billion interactions and is an innovator in high-stakes training for critical roles. The Amplifire platform harnesses advances in cognitive science to create personalized learning and drive successful outcomes. The platform’s adaptive algorithm guides millions of learners to mastery across healthcare, government, and other segments, providing unique analytics that offer valuable learner insights.