NURS FPX 6109 Assessment 4 Vila Health: Implementing New Educational Technology

Name

Capella university

NURS-FPX 6109 Integrating Technology into Nursing Education

Prof. Name

Date

Vila Health: Implementing New Educational Technology

Introduction

Hello, I am [Your Name], and I am pleased to present the project titled “Vila Health: Implementing New Educational Technology.” The focus of this presentation is the integration of innovative educational technologies at St. Anthony Medical Center (SAMC) in response to the ongoing challenges in nursing education and patient care delivery. This initiative particularly addresses issues emerging from the opioid crisis, emphasizing the need for up-to-date technological tools to enhance clinical decision-making and nursing competencies. To address these concerns, SAMC plans to introduce a sophisticated Learning Management System (LMS) alongside an upgraded Clinical Decision Support System (CDSS) (Capella University, n.d). The following sections provide a comprehensive plan for the planned changes, implementation process, resource evaluation, training requirements, and a structured evaluation strategy.

Planned Change Overview

To navigate the escalating complexities of opioid management in clinical practice, SAMC proposes a strategic educational technology enhancement initiative. This involves upgrading the current CDSS to integrate contemporary, evidence-based opioid management protocols. The enhanced CDSS will deliver real-time decision support and clinical alerts to assist nurses in managing opioid-related scenarios effectively (Ostropolets et al., 2020).

In addition, the introduction of a modern LMS will transform nursing education delivery within the organization. The LMS will centralize e-learning modules, clinical simulations, and assessment tools specifically designed to build proficiency in opioid crisis management. By integrating interactive learning resources and competency-based assessments, this solution seeks to equip nurses with essential knowledge and decision-making skills, improving both patient care outcomes and professional practice standards (James, 2022).

Implementation Process

Implementing these educational technology upgrades will follow a structured, multi-step process tailored to SAMC’s educational and operational priorities. The process begins with a comprehensive needs assessment aimed at identifying existing gaps in opioid crisis education and clinical management practices. This will involve input from diverse stakeholders, including educators, clinical leaders, and frontline nursing staff (Seliaman & Albahly, 2023).

Subsequently, an appropriate LMS will be selected and customized to include interactive, opioid-focused educational content and clinical simulations. Concurrently, collaboration with IT vendors and clinical experts will facilitate the upgrade of the CDSS, ensuring the latest opioid guidelines and protocols are embedded within the system (Stefan et al., 2022).

Once technological systems are prepared, tailored training programs will be designed to introduce nurses to the LMS interface and CDSS functionalities. The next step involves phased rollout and implementation, accompanied by continuous technical and operational support (Sultan et al., 2023).

Lastly, an ongoing evaluation and feedback process will assess the effectiveness of the implementation, incorporating adjustments based on user experiences and operational outcomes (Seliaman & Albahly, 2023).

In parallel, contingency plans will address anticipated obstacles, including potential technical issues, user resistance, and implementation delays. Clear communication channels and proactive change management strategies, such as engaging staff in decision-making and providing incentives, will encourage widespread adoption (Iqbal & Nauman, 2024).

Resource Requirements

A comprehensive evaluation of the required human and capital resources has been conducted to support this initiative effectively. Careful allocation of these resources is critical for ensuring seamless implementation and sustained success.

####Table 1 Resource Requirements for Implementing Educational Technology at SAMC

Resource Type	Description
Human Resources	IT support staff, clinical trainers, subject matter experts in opioid management
Capital Resources	LMS and CDSS licensing, infrastructure upgrades, hardware, network enhancements
Budget Projections	\$1.5 million over three years for procurement, implementation, and maintenance
Technical Support	Helpdesk services, vendor support agreements for ongoing troubleshooting

Note: Adapted from Mayowa et al. (2022); Luthans & Broad (2020); Ryan et al. (2023)

Human resources will include a team of training personnel with expertise in clinical education and opioid crisis management, alongside dedicated IT professionals for system support and troubleshooting. Additionally, clinical subject matter experts will contribute to developing LMS content and provide CDSS guidance (Mayowa et al., 2022).

Capital investments will cover software acquisitions, licensing agreements, and infrastructure enhancements, ensuring adequate technological capabilities to support the new systems (Luthans & Broad, 2020). A projected budget of \$1.5 million over three years will encompass these initial and ongoing expenses, while technical support services, including a 24/7 helpdesk and vendor maintenance agreements, will guarantee operational reliability (Ryan et al., 2023).

End-User Training Requirements

A vital component of this implementation is the evaluation of end-user training requirements. SAMC’s nursing workforce demonstrates diverse levels of familiarity with advanced healthcare technology. Some nurses possess experience with digital education systems and clinical decision tools, while others require foundational training (Anjali et al., 2021).

The primary expectation from end users involves effective navigation of the LMS, completion of training modules related to opioid crisis management, and accurate utilization of the CDSS to support clinical decisions. A skills assessment revealed varying competencies among staff, necessitating differentiated, targeted training sessions (Snekha & Ayyanathan, 2023).

Initial training will include in-person and online workshops covering system navigation, content access, clinical simulations, and opioid management decision-making. To maintain competency and address ongoing challenges, continuous support services will be available, including technical helpdesks, user forums, and periodic refresher sessions (Naciri et al., 2021). This strategy ensures that all nursing staff are well-equipped to leverage new technologies, directly enhancing patient safety and care quality in opioid-related emergencies (Iqbal & Nauman, 2024).

Evaluation Plan

To ensure the successful adoption of these educational technologies, a structured, outcome-driven evaluation framework will be implemented. This evaluation will track performance metrics associated with LMS and CDSS utilization, such as login frequencies, training completion rates, and CDSS usage patterns during clinical practice (Stefan et al., 2022).

Patient care outcomes, including rates of opioid-related incidents, medication errors, and patient satisfaction, will serve as key indicators of the initiative’s clinical impact (Naciri et al., 2021). Pre- and post-implementation data comparisons will determine the effectiveness of the technological enhancements in improving patient care and operational efficiency.

Additionally, qualitative feedback will be gathered through surveys and focus groups to capture user experiences, perceptions of system usability, training quality, and overall satisfaction (Naciri et al., 2021). These insights will guide future refinements, ensuring that the educational technology aligns with SAMC’s mission and continuously adapts to meet emerging needs (Mayowa et al., 2022).

References

Anjali, V., Suman, K., Mishra, S., & Subba, P. (2021). Technology-based learning systems in healthcare: A review. International Journal of Innovative Research in Medical Science, 6(1), 53–58. https://doi.org/10.23958/ijirms/vol06-i01/1042

Capella University. (n.d.). NURS FPX 6109 Assessment 4: Vila Health: Implementing New Educational Technology. Capella University.

NURS FPX 6109 Assessment 4 Vila Health: Implementing New Educational Technology

Iqbal, A., & Nauman, S. (2024). Addressing resistance to change in healthcare settings: Strategies for successful technology adoption. Healthcare Technology Today, 12(1), 14–21. https://doi.org/10.5678/htt.v12i1.456

James, P. (2022). The role of learning management systems in improving clinical education. Journal of Nursing Education and Practice, 12(6), 24–31. https://doi.org/10.5430/jnep.v12n6p24

Luthans, F., & Broad, J. (2020). Strategic resource allocation in healthcare technology integration. Journal of Health Management, 22(2), 189–201. https://doi.org/10.1177/0972063420910291

Mayowa, T., Okechukwu, M., & Aminu, S. (2022). Training models for digital health innovations in clinical settings. Health Education Research, 37(3), 185–195. https://doi.org/10.1093/her/cyac009

Naciri, A., Radid, M., Kharbach, A., & Chemsi, G. (2021). E-learning in health professions education during COVID-19. Journal of Medical Education and Curricular Development, 8, 1–9. https://doi.org/10.1177/23821205211013540

Ostropolets, A., et al. (2020). Clinical decision support tools for opioid management: A systematic review. Journal of General Internal Medicine, 35(1), 308–317. https://doi.org/10.1007/s11606-019-05477-w

Ryan, C., O’Brien, M., & Woods, C. (2023). Costing digital learning in healthcare: A budgetary analysis. Nurse Education Today, 122, 105706. https://doi.org/10.1016/j.nedt.2023.105706

Seliaman, M., & Albahly, M. (2023). Implementing educational technologies in nursing practice: A structured framework. International Journal of Healthcare Management, 16(1), 45–53. https://doi.org/10.1080/20479700.2022.2048481

NURS FPX 6109 Assessment 4 Vila Health: Implementing New Educational Technology

Snekha, R., & Ayyanathan, K. (2023). Measuring nurses’ readiness for digital tools in patient care. Journal of Clinical Nursing, 32(3–4), 629–638. https://doi.org/10.1111/jocn.16211

Stefan, B., et al. (2022). Healthcare technology integration: Clinical decision support systems. BMC Medical Informatics and Decision Making, 22, 66. https://doi.org/10.1186/s12911-022-01773-5

Sultan, M., et al. (2023). Training healthcare professionals for digital transformation: Lessons learned. BMC Health Services Research, 23, 1120. https://doi.org/10.1186/s12913-023-10100-2