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Competency Management for the Next Generation

April 4th, 2024
April 4th, 2024

The unprecedented staffing and financial pressures currently faced by the healthcare industry along with the presence of multiple generations in the healthcare workforce has intensified the need to reevaluate traditional means of competency management. In a recent HealthStream webinar, Jill Benns, RN, MSN, MBA,/HCM,NPD, BC, Alumnus, PCCN, HealthStream’s Managing Editor, jane AI™, and Hailey Fisher, HealthStream’s Senior Solutions Executive shared how a personalized approach to training can improve quality outcomes, and reduce seat time while also reducing the gap between knowledge and clinical judgement.

 

The Educator’s Role in Competency Management

Benns began by clarifying the role of educators in competency management and acknowledged that it is a dynamic process. The process needs to support the ongoing assessment of performance which means that educators need to accept responsibility for measuring, documenting, and supporting competency while also addressing any deficiencies that are identified. In order to do that, educators need to have expertise in competency in order to manage and evaluate competency programs.

 

Avoiding the Pitfalls of Competency Management

Benns acknowledged that, for many educators, competency management has devolved into an obligatory process for managing checklists. Both nurses and leaders report that competency management feels tedious, is not reflective of nursing practice, and fails to help nurses grow in their practice. A one-size-fits-all approach which fails to meet the needs of many learners likely contributes to these perceptions. 

Benns also shared that multiple organizations have expressed concerns about current competency management practices. A 2021 article from the American Nurses Association (ANA) described the need for change and called for restructuring the processes to leverage artificial intelligence (AI) infused clinical practice methodologies to better support competency development. Additionally, the National Council of State Boards of Nursing (NCSBN) has developed the next generation blueprint for the NCLEX RN exam which includes an increased focus on clinical judgement. The Journal of Nursing Education has also advocated for the infusion of low and high fidelity simulation to help nurses synthesize information and apply it in medically complex situations.

Benns reported that in 2017, 23% of nurses believed that they had a strong foundation for competency preparedness. By 2021, that number had dropped to just 9%.

Benns believes that the message is clear. “As the landscape of healthcare and nursing education continues to change, competency management must evolve. It needs to be customized to the unique needs of learners and the answers will lie in how leaders are able to leverage technology to accomplish this,” said Benns.

 

Competency Management Solutions – Leveraging Technology

While AI may have negative connotations for some, it has actually been in use in healthcare for quite some time. AI has been useful in providing decision support for charting, predicting patterns in morbidity and mortality, supporting tools that support sound documentation, and other tools such as acuity models and medication guardrails that have been supporting decision making and patient safety. It has been shown to provide informatics and automation support and has created opportunities for portability, standardization, and transformation for many aspects of healthcare. It also has some meaningful applications for learning and competency management.

Benns shared that HealthStream’s jane AI can process what nurses know and do not know along with the associated learning level and is then able to provide individual learning recommendations. This helps educators to right-size the learning process for each nurse as they move from novice to intermediate to expert skill levels. “When used correctly and supported by clinical educators, AI can provide a succinct assessment of clinical care and patient management topics for a specific individual,” said Benns.

 

Leveraging AI – HealthStream’s jane AI 

With 40 clinical pathways across 10 disciplines, jane AI can provide unbiased, customized competency pathways to help:

  • Assess new employee competencies
  • Accelerate employee orientation
  • Identify potential preceptors
  • Reduce seat time by focusing on precisely what a learner needs and allowing them to skip over courses that have already been mastered

Because competency encompasses both knowledge and judgement, jane AI can also assess clinical judgement through the use of interactive, open-ended chat and a series of scenario-based videos that help assess a nurse’s ability to identify problems, process clinical observations, determine urgency, and take appropriate action. Micro-learning courses, in a mobile-friendly format, support nurses with an active learning approach and an ability to do self-assessments at a time and place that is convenient for the nurse.

This customized approach to competency management can result in higher nurse retention and satisfaction as nurses appreciate the personalized development plans. It is also a useful tool for leaders as it provides reporting that includes national benchmarks and can track performance at the organization, facility, department, and individual levels.

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