Faculty development initiatives for the integration of informatics competencies and point-of-care technologies in undergraduate nursing education

Are Nursing Faculty Future-Ready? The Effects of Emerging Technologies on Nursing Education

BACKGROUND

Preparing the next generation of nurses requires consideration for the integration of emerging technologies. This refers specifically to technologies that will shape and affect how care is delivered-not in today's health care facilities but in facilities 20 years from now and beyond.

METHOD

A cross-sectional survey examining how seven emerging technologies were integrated into nursing curricula was developed and distributed to nursing faculty. A multiple linear regression model was used to analyze the data for the level of integration. The model was adjusted for all demographic measures, and the independent variables of interest were developed from unified theory of acceptance and use of technology (UTAUT) constructs.

RESULTS

Performance, attitude, social influence, and effort were insignificant. Education and training, costs, and complexity were noted as top barriers to adoption.

CONCLUSION

A literature gap regarding integrating emerging technologies in nursing curricula exists. Further research is warranted to understand factors influencing integration. [J Nurs Educ. 2023;62(12):689-700.].

Education and Training on Electronic Medical Records (EMRs) for health care professionals and students: A Scoping Review

BACKGROUND AND OBJECTIVES

The ability of health care providers and students to use EMRs efficiently can lead to achieving improved clinical outcomes. Training policies and strategies play a major role in successful technology implementation and ongoing use of the EMR systems. To provide evidence-based guidance for developing and implementing educational interventions and training, we reviewed and summarized the current literature on EMR training targeting both healthcare professionals (HCP) and students.

METHODS

We used the Joanna Briggs Institute (JBI) approach for scoping reviews and the PRISMA extension of scoping reviews (PRISMA-ScR) checklist for reporting our review. 46 full-text articles that met the eligibility criteria were selected for the review. Narrative synthesis was performed to summarize the evidence using numerical and descriptive analysis. We used inductive content analysis for categorizing the training methods. Also, the modified version of the Kirkpatrick's levels model was used for abstracting the training outcome.

RESULTS

Five types of training methods were identified: one-on-one training, peer-coach training, classroom training (CRT), computer-based training (CBT), and blended training. A variety of CBT platforms were used, including a prototype academic electronic medical record system (AEMR), AEMR/simulated EMR (Sim-EMR), mobile based AEMR, eLearning, and electronic educational materials. Each training intervention could have resulted in several outcomes. Most outcomes were related to levels 1-3 of the Kirkpatrick model that involves learners (n = 108), followed by level 4a that involves organizations (n = 7), and lastly level 4b that involves patients (n = 1). The outcomes related to participants' knowledge (level 2b) was the most often measured training outcome (n = 44).

CONCLUSIONS

This review presents a comprehensive synthesis of the evidence on EMR training. A variety of training methods, participants, locations, strategies, and outcomes were described in the studies. Training should be aligned with the particular training needs, training objectives, EMR system utilized, and organizational environment. A training plan should include an overall goal and SMART (Specific, Measurable, Achievable, Realistic, Tangible) training objectives, that would allow a more rigorous evaluation of the training outcomes.

Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges

Context:

The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events in real time with the intent to improve patient outcomes and reduce costs. There is an urgent need for a systematic framework to guide the development and application of e-HPA to ensure that the field develops in a scientifically sound, ethical, and efficient manner.

Objectives:

Building upon earlier frameworks of model development and utilization, we identify the emerging opportunities and challenges of e-HPA, propose a framework that enables us to realize these opportunities, address these challenges, and motivate e-HPA stakeholders to both adopt and continuously refine the framework as the applications of e-HPA emerge.

Methods:

To achieve these objectives, 17 experts with diverse expertise including methodology, ethics, legal, regulation, and health care delivery systems were assembled to identify emerging opportunities and challenges of e-HPA and to propose a framework to guide the development and application of e-HPA.

Findings:

The framework proposed by the panel includes three key domains where e-HPA differs qualitatively from earlier generations of models and algorithms (Data Barriers, Transparency, and Ethics) and areas where current frameworks are insufficient to address the emerging opportunities and challenges of e-HPA (Regulation and Certification; and Education and Training). The following list of recommendations summarizes the key points of the framework:

Data Barriers: Establish mechanisms within the scientific community to support data sharing for predictive model development and testing.

Transparency: Set standards around e-HPA validation based on principles of scientific transparency and reproducibility.

Ethics: Develop both individual-centered and society-centered risk-benefit approaches to evaluate e-HPA.

Regulation and Certification: Construct a self-regulation and certification framework within e-HPA.

Education and Training: Make significant changes to medical, nursing, and paraprofessional curricula by including training for understanding, evaluating, and utilizing predictive models.

Mobile applications in nursing education and practice

Students in an RN-BSN completion program capstone course investigated and critically evaluated mobile medical applications using an information literacy conceptual framework. Students also analyzed their potential usefulness as a resource in nursing practice. Student evaluations focused on usability and applicability when recommending the use of mobile applications as a point-of-care reference tools. This pilot assignment offers an innovative teaching strategy for integrating 1 aspect of informatics instruction into the nursing curriculum.

Integrating informatics into the BSN curriculum: a review of the literature

Even though health informatics (HI) education is an essential component of the undergraduate nursing curriculum, it remains controversial with no clear consensus on which knowledge and skills should be integrated in a baccalaureate nursing program. The purpose of this review article is to integrate literature on HI education in the nursing curriculum by examining previous and current literature on this topic, synthesizing the findings, and recommending guidelines and future directions for nurse educators. The computerized databases of CINAHL, MEDLINE, ERIC, Academic Search Premier, and Google Scholar were used to generate relevant literature. Nineteen studies published between 2000 and 2010 on HI education were included in this review, and from the critical and synthesis of those reports emerged four overarching themes: (a) lack of consensus on HI education; (b) impact on patient care outcomes; (c) faculty development through organizational collaboration; and (d) global disparities in HI education. Implications for nursing education and patient outcomes in clinical practice are also discussed. Further studies are warranted to promote the understanding and awareness of HI education in undergraduate nursing curriculum.