NURS FPX 4905 Assessment 3 Technology and Professional Standards

Name

Capella university

NURS-FPX4905 Capstone Project for Nursing

Prof. Name

Date

Technology and Professional Standards

Technology and professional standards significantly influence the quality, safety, and efficiency of healthcare practices. Within regenerative medicine, where diagnostic complexity often delays treatment, the integration of advanced tools and strict adherence to nursing standards are critical for achieving accurate and timely outcomes (Kantaros & Ganetsos, 2023). This discussion explores the role of the BSN-prepared nurse at The Longevity Center, emphasizing contributions to process improvement, interprofessional collaboration, and adherence to regulatory recommendations. Additionally, it examines existing technologies, evidence-based recommendations, and strategies for implementing advanced diagnostic tools while addressing potential challenges.

Role of the BSN-Prepared Nurse in Process Improvement and Professional Standards

BSN-prepared nurses play a vital role in enhancing diagnostic accuracy and timeliness at The Longevity Center by aligning care with professional standards and focusing on process improvement. Delays in diagnosis require a proactive nursing approach grounded in evidence-based practice, strong communication, and patient advocacy.

Nurses ensure comprehensive patient assessments, accurate interpretation of blood panels, and meticulous review of patient histories. Their responsibilities also include identifying inefficiencies within diagnostic workflows and proposing improvements consistent with the American Nurses Association (ANA) Code of Ethics, which emphasizes accountability and the delivery of safe and effective care (American Nurses Association, 2025).

Furthermore, BSN-prepared nurses contribute by identifying cases requiring advanced evaluation or additional diagnostic tools. For example, delays in interpreting Longevity blood panels or inconsistent documentation may result in missed treatment opportunities. Nurses help standardize history collection and collaborate during case reviews to prevent these lapses.

Although nurses may not always hold decision-making authority, their observations, advocacy, and interprofessional communication directly influence the continuity and quality of care, ensuring timely identification of patient needs.

Interprofessional Collaboration in Regenerative Healthcare

Interprofessional collaboration at The Longevity Center strengthens diagnostic accuracy and improves patient outcomes. Collaboration typically involves nurses, nurse practitioners, physicians, and administrative staff, ensuring diverse perspectives in care delivery.

During practicum experiences, collaboration occurred through joint patient chart reviews and discussions regarding treatment readiness, such as for platelet-rich plasma (PRP) or stem cell therapy. These activities ensured that diagnostic decisions reflected input from multiple disciplines.

Moving forward, more structured collaboration could be achieved through:

Interdisciplinary case huddles
Shared electronic platforms for communication
Real-time updates on intake and follow-up

Such strategies minimize miscommunication, reduce diagnostic delays, and ensure continuity of care (Kantaros & Ganetsos, 2023). The benefits extend beyond efficiency—they foster safer care, more accurate diagnoses, and higher patient satisfaction by ensuring that no clinical information is overlooked.

Government Agency Recommendations

Regulatory agencies provide crucial guidance for improving diagnostic practices at The Longevity Center.

Agency/Organization	Key Recommendations	Relevance to Longevity Center
The Joint Commission (2021)	Emphasizes accurate, timely diagnosis; requires effective communication and standardized data collection.	Supports consistent patient intake and better diagnostic clarity.
Agency for Healthcare Research and Quality (2024)	Advocates for decision-support tools, evidence-based protocols, and reduced variability in care.	Encourages adoption of clinical decision support systems to improve outcomes.
National Database of Nursing Quality Indicators (Montalvo, 2020)	Focuses on nursing roles in timely assessments, proper documentation, and collaborative care.	Reinforces nurse involvement in minimizing diagnostic delays.

Together, these recommendations highlight the need for standardized processes, early interventions, and coordinated teamwork to enhance patient safety and reduce errors.

Current Technology Utilized

The Longevity Center currently employs three main technologies:

Ultrasound Imaging: Used to guide regenerative medicine procedures such as PRP and stem cell injections, reducing procedural risks.
Electronic Health Records (EHRs): Store patient histories, lab findings, and progress notes.
Longevity Blood Panel: Provides a detailed evaluation of inflammation, hormones, micronutrients, and metabolic status.

However, several challenges limit effectiveness:

Lack of EHR integration with external diagnostic systems, causing manual data entry and potential transcription errors.
Absence of a centralized decision support system, which results in missed or delayed diagnostic opportunities.

While these technologies enable a baseline level of safe care, interoperability and real-time decision support tools remain underdeveloped (Yamada et al., 2021).

Literature-Based Technology Recommendations for Improving Diagnostic Delays

Technology	Pros	Cons	Evidence
Clinical Decision Support Systems (CDSS)	Real-time alerts, abnormal lab flagging, evidence-based treatment suggestions.	Requires customization, may cause alert fatigue, costly implementation.	Yamada et al. (2021)
AI-Assisted Diagnostics	Rapid data analysis, pattern recognition in complex labs/imaging.	Expensive, privacy risks, limited provider acceptance.	Nosrati & Nosrati (2023)
Remote Patient Monitoring (RPM)	Early detection of health changes, personalized care.	Adherence issues, technical glitches, EHR integration challenges.	Petrosyan et al. (2022)

These technologies, when integrated effectively, can minimize diagnostic delays, improve accuracy, and enhance patient safety.

Potential Implementation Issues and Solutions for New Diagnostic Technologies

The adoption of CDSS, AI diagnostics, and RPM tools faces multiple barriers:

High Costs – Upfront investments in software, hardware, and licensing.
- Solution: Seek grant funding, phased rollouts, and partnerships with tech providers.
Staff Resistance – Concerns about workload, unfamiliarity with digital systems.
- Solution: Provide targeted training and pilot programs for gradual adoption.
Data Integration Challenges – Incompatibility with existing EHRs.
- Solution: Use third-party integration platforms and staged implementation.
Privacy and Compliance Risks – Especially with AI tools requiring large datasets.
- Solution: Establish strict data governance and compliance frameworks.

By addressing these challenges through phased adoption, staff engagement, and funding strategies, The Longevity Center can implement advanced tools without compromising patient safety (Nosrati & Nosrati, 2023; Petrosyan et al., 2022).

Conclusion

To improve diagnostic timeliness and safety, BSN-prepared nurses must take the lead in standardizing intake, upholding professional standards, and facilitating communication. Strengthened interprofessional collaboration enhances care coordination, while advanced tools such as CDSS, AI diagnostics, and RPM can significantly reduce delays. Successful implementation will require phased integration, staff training, and funding support, ensuring that The Longevity Center achieves better outcomes while maintaining patient-centered, ethical, and safe practices.

References

Agency for Healthcare Research and Quality. (2024, November). Clinical decision support. https://www.ahrq.gov/cpi/about/otherwebsites/clinical-decision-support/index.html

American Nurses Association. (2025). Code of ethics for nurses. https://codeofethics.ana.org/home

Kantaros, A., & Ganetsos, T. (2023). From static to dynamic: Smart materials pioneering additive manufacturing in regenerative medicine. International Journal of Molecular Sciences, 24(21). https://doi.org/10.3390/ijms242115748

Montalvo, I. (2020). The National Database of Nursing Quality Indicators® (NDNQI®). https://ojin.nursingworld.org/MainMenuCategories/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/Volume122007/No3Sept07/NursingQualityIndicators.html

Nosrati, H., & Nosrati, M. (2023). Artificial intelligence in regenerative medicine: Applications and implications. Biomimetics, 8(5). https://doi.org/10.3390/biomimetics8050442