NURS FPX 6416 Assessment 3 Evaluation of an Information System Change
Student Name
Capella University
NURS-FPX 6416 Managing the Nursing Informatics Life Cycle
Prof. Name
Date
Evaluation Report
The main aim of this initiative was to improve operational performance and minimize clinical and security risks by transitioning from a manual, paper-based documentation system to an electronic health record (EHR) system. Under the previous system, patient management was inefficient due to approximately a 5% documentation error rate, misplaced records, and inconsistencies caused by manual entry. On average, retrieving a patient file required around 20 minutes, which negatively affected timely clinical decision-making and workflow efficiency.
The implementation of the EHR system was executed in four structured phases. The initial two phases concentrated on selecting a suitable vendor and providing foundational staff training to support system adoption. The third phase focused on system evaluation and iterative improvements based on user feedback, while the final phase involved full-scale deployment and integration into routine clinical workflows. Although the transition initially faced resistance from staff and technical barriers, the system ultimately strengthened patient safety, improved data integrity, and enhanced overall healthcare delivery.
Quality of Information Framework
The introduction of the EHR system has significantly improved the accuracy, completeness, and reliability of patient records. Automated validation mechanisms have reduced documentation errors from 5% to less than 1%, thereby increasing trust in clinical data and supporting better-informed decision-making. Additionally, structured training programs and an intuitive system interface have contributed to higher staff confidence and improved user satisfaction (Mishra et al., 2022).
Security measures have also been strengthened through encryption protocols and role-based access controls, ensuring compliance with HIPAA requirements and protecting sensitive patient information (Thapa & Camtepe, 2021). Continuous monitoring through audits helps maintain regulatory compliance, while feedback mechanisms such as surveys support ongoing improvements in usability and system security (Kabukye et al., 2020). Furthermore, real-time updates ensure that clinicians always access the most current patient data, enhancing clinical accuracy.
NURS FPX 6416 Assessment 3 Evaluation of an Information System Change
Table 1: Key Features of EHR Quality Improvements
| Feature | Before EHR | After EHR | Impact |
|---|---|---|---|
| Error Rate | 5% | <1% | Improved data reliability |
| Data Retrieval Time | 20 minutes | 2 minutes | Faster clinical decision-making |
| Staff Satisfaction | Moderate | High | Increased engagement and confidence |
| Security | Limited | Encryption & access control | HIPAA compliance ensured |
| Patient Wait Times | Longer | Reduced | Improved patient experience |
Outcomes of Quality Care Framework
The EHR system has significantly enhanced healthcare delivery efficiency by reducing data retrieval time from 20 minutes to approximately 2 minutes. This improvement has enabled clinicians to access patient information quickly, leading to faster and more accurate decision-making. The integration of real-time data and clinical decision-support tools has also contributed to more individualized and evidence-based patient care (Ostropolets et al., 2020).
In addition, care coordination across departments and multidisciplinary teams has improved, resulting in more streamlined workflows and reduced hospital readmission rates. These improvements collectively reflect enhanced patient outcomes and better continuity of care (Perry et al., 2020). Ongoing system monitoring remains essential to sustain these improvements and address emerging clinical and operational challenges effectively.
Structural Quality Framework
Leadership involvement played a key role in ensuring the success of the EHR implementation by securing financial resources and organizational commitment. Infrastructure and hardware capabilities were assessed to ensure they could support increased data processing demands and system scalability. The software system was evaluated for usability, interoperability, and workflow compatibility, with staff feedback incorporated to refine the interface and enhance usability (Watterson et al., 2020).
Regular system maintenance and software updates have been essential in resolving technical issues and improving overall performance. Strengthening network infrastructure and implementing robust cybersecurity protocols have further supported system stability and data protection (Huang et al., 2020). Continuous investment in technological upgrades and workforce development remains necessary to ensure long-term system sustainability.
Evaluation and Analysis
The EHR implementation process was carried out in a phased approach to ensure controlled adoption and minimize disruption.
Phase Overview
- Phase 1 (Months 1–2): Vendor selection and initial training were completed. Resistance from staff accustomed to paper-based systems was observed, but early training helped reduce concerns.
- Phase 2 (Months 3–4): System installation and workflow integration were carried out. Minor technical issues emerged, requiring system adjustments and additional training.
- Phase 3 (Months 5–6): Focus shifted to performance evaluation and optimization. Significant reductions in retrieval time and error rates were recorded. User feedback was collected to guide improvements.
- Phase 4 (Post-Deployment): Full system integration was achieved with ongoing monitoring and performance refinement.
NURS FPX 6416 Assessment 3 Evaluation of an Information System Change
Table 2: EHR Implementation Timeline and Key Activities
| Phase | Duration | Focus | Key Outcomes |
|---|---|---|---|
| Phase 1 | Months 1–2 | Vendor selection & training | Initial resistance; foundational training completed |
| Phase 2 | Months 3–4 | Implementation & integration | Minor technical issues; workflow adjustments |
| Phase 3 | Months 5–6 | Evaluation & improvement | Reduced errors; faster retrieval; feedback integration |
| Phase 4 | Ongoing | Full deployment & monitoring | System optimization and sustained performance tracking |
Recommendations for Further Improvement
To further enhance EHR effectiveness and sustainability, the following strategies are recommended:
- Continuous training programs should be implemented to address skill gaps and improve digital competency among staff.
- A dedicated technical support unit should be established to ensure rapid resolution of system-related issues.
- Regular updates to clinical decision-support tools should be prioritized to improve diagnostic accuracy and treatment planning (Kawamoto & McDonald, 2020).
- A structured and accessible user feedback system should be maintained to identify operational challenges early.
- Ongoing investment in IT infrastructure is necessary to support system scalability and performance.
- Routine audits should continue to ensure compliance with healthcare regulations and internal standards.
- Active stakeholder engagement is essential to reduce resistance and support continuous system improvement (Yigzaw et al., 2020).
Conclusion
The transition to an electronic health record system has led to substantial improvements in data accuracy, operational efficiency, and patient satisfaction. By significantly reducing documentation errors and retrieval times, the system has optimized clinical workflows and supported faster, more reliable decision-making. Despite initial implementation challenges, the EHR system has demonstrated clear benefits in enhancing healthcare delivery. Continued investment in training, infrastructure, and stakeholder engagement is essential to sustain these improvements and further advance system performance.
References
Huang, C., Koppel, R., McGreevey, J. D., Craven, C. K., & Schreiber, R. (2020). Transitions from one electronic health record to another: Challenges, pitfalls, and recommendations. Applied Clinical Informatics, 11(05), 742–754. https://doi.org/10.1055/s-0040-1718535
Kabukye, J. K., Keizer, N., & Cornet, R. (2020). Assessment of organizational readiness to implement an electronic health record system in a low-resource settings cancer hospital: A cross-sectional survey. PLoS ONE, 15(6), e0234711. https://doi.org/10.1371/journal.pone.0234711
NURS FPX 6416 Assessment 3 Evaluation of an Information System Change
Kawamoto, K., & McDonald, C. J. (2020). Designing, conducting, and reporting clinical decision support studies: Recommendations and call to action. Annals of Internal Medicine, 172(11_Supplement), S101–S109. https://doi.org/10.7326/m19-0875
Mishra, V., Liebovitz, D., Quinn, M., Kang, L., Yackel, T., & Hoyt, R. (2022). Factors that influence clinician experience with electronic health records. Perspectives in Health Information Management, 19(1), 1f. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013220/
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
NURS FPX 6416 Assessment 3 Evaluation of an Information System Change
Perry, M. F., Macias, C., Chaparro, J. D., Heacock, A. C., Jackson, K., & Bode, R. S. (2020). Improving early discharges with an electronic health record discharge optimization tool. Pediatric Quality & Safety, 5(3), e301. https://doi.org/10.1097/pq9.0000000000000301
Thapa, C., & Camtepe, S. (2021). Precision health data: Requirements, challenges and existing techniques for data security and privacy. Computers in Biology and Medicine, 129(1), 104130. https://doi.org/10.1016/j.compbiomed.2020.104130
Watterson, J. L., Rodriguez, H. P., Aguilera, A., & Shortell, S. M. (2020). Ease of use of electronic health records and relational coordination among primary care team members. Health Care Management Review, 45(3), 1–10. https://doi.org/10.1097/hmr.0000000000000222
Yigzaw, B., Budrionis, A., Ruiz, M., Henriksen, E., Halvorsen, K., & Bellika, J. G. (2020). Privacy-preserving architecture for providing feedback to clinicians on their clinical performance. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01147-5