Student Name
Capella University
NURS-FPX 6109 Integrating Technology into Nursing Education
Prof. Name
Date
Educational Technology Assessment Needs
Evaluating the requirements for educational technology presents a complex challenge for nurse managers and healthcare administrators. In the context of modern nursing education and emerging public health crises, such as the opioid epidemic, it is crucial to reassess and improve educational resources. The objective of this assessment is to optimize the instructional tools currently used in nursing education so that they not only meet immediate training needs but also align with organizational strategies aimed at improving patient outcomes. This paper provides recommendations to enhance the educational infrastructure at St. Anthony Medical Center (SAMC), emphasizing the integration of technology to advance nurse competency and patient care quality.
How Nurses Currently Use Educational Technology
At SAMC, educational technology is deeply embedded in both the learning environment and ongoing professional development for nurses. Staff rely on Clinical Decision Support Systems (CDSS) and online learning platforms managed through the hospital’s Learning Management System (LMS) (Capella University, n.d.). These technologies provide access to internal protocols, disease management modules, and care guideline courses. Additionally, High-Fidelity Simulation (HFS) is leveraged for operational education and emergency response training.
HFS creates a controlled environment for nurses to practice real-life clinical scenarios, enhancing skill acquisition and confidence. In clinical practice, CDSS supports rapid decision-making and ensures compliance with established clinical standards (Ostropolets et al., 2020). Despite these benefits, gaps remain—particularly in opioid management. CDSS requires updates to align with current standards, and e-learning platforms should be used more comprehensively to provide up-to-date guidance (Regmi & Jones, 2020).
For instance, Dr. Cartwright identified a lack of standardized training on opioid administration across departments, highlighting deficiencies in adopting educational technology for consistent clinical practices (Capella University, n.d.). Current use of technology assumes alignment with contemporary best practices, yet observations reveal a gap between existing tools and emerging healthcare needs, such as opioid management (Huter et al., 2020).
The Comparison with the Desired Technology State
Educational technologies like CDSS and e-learning platforms are vital for improving clinical data processes and facilitating online learning. Effective implementation enhances nurses’ understanding of patient needs and adherence to clinical protocols (Ostropolets et al., 2020; Regmi & Jones, 2020). A SWOT analysis was conducted to evaluate the current technology state.
| SWOT Component | Details |
|---|---|
| Strengths | Existing proficiency with CDSS and e-learning platforms; supports continuous nursing education |
| Opportunities | Incorporate evidence-based, updated modules; expand nurses’ knowledge and competencies; improve clinical skills and patient outcomes |
| Weaknesses | Outdated CDSS inconsistent with opioid care protocols; uneven education and training among divisions; limited data on technology adoption and impact |
| Threats | Resistance to technology updates; regulatory and compliance risks related to inadequate opioid management training; outdated clinical guidelines risking quality of care |
Current assessment shows that SAMC’s CDSS is outdated, particularly in opioid care, and e-learning modules are inconsistently deployed across departments (Spithoff et al., 2020; Regmi & Jones, 2020). Standardized education, especially for opioid prescribing, is missing, which undermines consistent learning outcomes (Gugala et al., 2022). Addressing these gaps requires updating CDSS, streamlining e-learning modules, and promoting standardization to enhance nurses’ technical skills and patient care.
Assessment of Metrics for Educational Technology Use
Measuring the effectiveness of educational technology at SAMC is essential to evaluate its impact on nurse training and patient outcomes. Common metrics include training completion rates, engagement levels, satisfaction surveys, and performance in e-learning assessments. While these provide insights into technology adoption, they do not fully capture its clinical impact. Comprehensive evaluation should include patient outcome measures, staff retention over time, and the influence of training on care delivery (Barteit et al., 2020).
Practical approaches to enhance evaluation include:
- Nurse Feedback Surveys: Capture qualitative insights about usability, perceived benefits, and ease of use (Elia et al., 2019).
- Clinical Performance Metrics: Monitor reduction in errors and adherence to best practices following training to assess tool effectiveness (Akinola & Telukdarie, 2023).
- Advanced Analytics: Use learning algorithms and statistical analysis to improve the accuracy of insights, providing a holistic view of technology effectiveness (Rehman et al., 2022).
Integrating these approaches ensures educational tools are widely accepted, improving clinical outcomes and aligning with SAMC’s mission.
Organizational Mission Aligned with the Technology
Aligning educational technology with SAMC’s mission is critical to its impact. The hospital prioritizes efficient patient care while fostering continuous professional development. Technology, such as e-learning platforms and simulation-based training, supports this mission by providing nurses with accessible opportunities for ongoing education and skills enhancement.
These programs keep nurses current with evidence-based practices, improving patient care outcomes (Regmi & Jones, 2020). Simulation and online tools allow nurses to practice complex procedures safely, enhancing competency without risking patient safety. An updated CDSS further supports real-time clinical decisions, ensuring adherence to best practices and improving outcomes (Ostropolets et al., 2020). Analytics within LMS platforms track progress, identify gaps, and help target additional training, particularly for high-risk areas such as opioid prescribing (Singh & Matthees, 2021).
Recommendations
To enhance nursing education at SAMC, the following strategies are recommended:
- Expand E-Learning Platforms: Develop comprehensive, interactive platforms addressing critical topics like opioid management, alternative pain therapies, and updated care practices. Include scenario-based simulations to improve engagement and knowledge retention (Regmi & Jones, 2020).
- Update the CDSS: Regularly update CDSS to reflect evidence-based clinical practices, enhancing decision support and learning opportunities for nurses (Spithoff et al., 2020).
- Ensure Equal Access: Provide all nurses with access to digital learning resources, standardized training, and structured completion procedures (Akinola & Telukdarie, 2023).
- Integrate LMS and CDSS: Align LMS modules with CDSS updates to deliver practical, real-time guidance for critical issues like opioid prescribing.
- Continuous Feedback: Collect nurse input through surveys and focus groups to identify improvement areas and evaluate the impact of technology on professional development (Haleem et al., 2022).
These strategies collectively support SAMC’s goal of fostering professional growth and improving patient care outcomes.
Conclusion
Educational technology plays a pivotal role in advancing nursing education and patient care at SAMC. Implementing a dynamic e-learning platform, updating CDSS, and aligning technology with strategic objectives enhances learning outcomes, professional growth, and clinical performance. Such improvements are essential for addressing emerging healthcare challenges, including the opioid crisis, while fulfilling SAMC’s mission of efficient, high-quality patient care.
References
Akinola, S., & Telukdarie, A. (2023). Sustainable digital transformation in healthcare: Advancing a digital vascular health innovation solution. Sustainability, 15(13), 10417. https://doi.org/10.3390/su151310417
Barteit, S., Guzek, D., Jahn, A., Bärnighausen, T., Jorge, M. M., & Neuhann, F. (2020). Evaluation of e-learning for medical education in low-and middle-income countries: A systematic review. Computers & Education, 145, 103726. https://doi.org/10.1016/j.compedu.2019.103726
Capella University. (n.d.). Vila Health: Educational technology needs assessment. Capella.edu. https://www.capella.edu/
Elia, G., Solazzo, G., Lorenzo, G., & Passiante, G. (2019). Assessing learners’ satisfaction in collaborative online courses through a big data approach. Computers in Human Behavior, 92, 589–599. https://doi.org/10.1016/j.chb.2018.04.033
NURS FPX 6109 Assessment 1 Vila Health: Educational Technology Needs Assessment
Gugala, E., Briggs, O., Moczygemba, L. R., Brown, C. M., & Hill, L. G. (2022). Opioid harm reduction: A scoping review of physician and system-level gaps in knowledge, education, and practice. Substance Abuse, 43(1), 972–987. https://doi.org/10.1080/08897077.2022.2060423
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
Huter, K., Krick, T., Domhoff, D., Seibert, K., Wolf-Ostermann, K., & Rothgang, H. (2020). Effectiveness of digital technologies to support nursing care: Results of a scoping review. Journal of Multidisciplinary Healthcare, 13, 1905–1926. https://doi.org/10.2147/jmdh.s286193
O’Brien, N., Li, E., Chaibva, C. N., Gomez Bravo, R., Kovacevic, L., Kwame Ayisi-Boateng, N., & Neves, A. L. (2023). Strengths, weaknesses, opportunities, and threats analysis of the use of digital health technologies in primary health care in the sub-Saharan African region: Qualitative study. Journal of Medical Internet Research, 25, e45224. https://doi.org/10.2196/45224
Ostropolets, A., Zhang, L., & Hripcsak, G. (2020). A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time. Journal of the American Medical Informatics Association, 27(12), 1968–1976. https://doi.org/10.1093/jamia/ocaa200
Regmi, K., & Jones, L. (2020). A systematic review of the factors – enablers and barriers – affecting e-learning in health sciences education. BMC Medical Education, 20(1), 1–18. https://doi.org/10.1186/s12909-020-02007-6
NURS FPX 6109 Assessment 1 Vila Health: Educational Technology Needs Assessment
Rehman, A., Naz, S., & Razzak, I. (2022). Leveraging big data analytics in healthcare enhancement: Trends, challenges and opportunities. Multimedia Systems, 28(4), 1339–1371. https://doi.org/10.1007/s00530-020-00736-8
Singh, J., & Matthees, B. (2021). Facilitating interprofessional education in an online environment during the COVID-19 pandemic: A mixed method study. Healthcare, 9(5), 567. https://doi.org/10.3390/healthcare9050567
Spithoff, S., Mathieson, S., Sullivan, F., Guan, Q., Sud, A., Hum, S., & O’Brien, M. A. (2020). Clinical decision support systems for opioid prescribing for chronic non-cancer pain in primary care: A scoping review. Journal of the American Board of Family Medicine, 33(4), 529–540. https://doi.org/10.3122/jabfm.2020.04.190199