NURS FPX 6416 Assessment 3 Evaluation of an Information System Change

Name

Capella university

NURS-FPX 6416 Managing the Nursing Informatics Life Cycle

Prof. Name

Date

Evaluation Report

The move from a manual, paper-based record-keeping system to an Electronic Health Record (EHR) system was undertaken to overcome significant operational inefficiencies and data security risks. Previously, it took approximately 20 minutes to retrieve patient information, and there was a 5% error rate due to manual input and misfiling, which compromised timely care delivery. The EHR rollout followed a phased strategy: Phase 1 involved choosing a suitable vendor and initiating basic training; Phase 2 focused on integrating the system with existing procedures; and Phase 3 emphasized post-deployment evaluation and refinements. Although there were early challenges such as resistance to change and technical interruptions, the adoption of the EHR system has notably enhanced the accuracy of data management, improved patient safety, and elevated the overall quality of care.

Evaluation and Analysis

A phased evaluation timeline ensured structured implementation and monitoring of the EHR system:

Phase	Timeframe	Key Activities	Challenges Identified	Outcomes
Phase 1	Months 1–2	Vendor selection, initial training	Staff resistance, training gaps	Awareness raised, initial training adapted
Phase 2	Months 3–4	System deployment, workflow integration	Temporary workflow disruptions	Integration completed, further training provided
Phase 3	Months 5–6	Performance evaluation, feedback-based refinements	Technical glitches, user feedback	Reduced retrieval time and error rates

Throughout the phases, assessments such as user satisfaction surveys and system performance tracking were conducted to monitor success and make necessary adjustments. The evaluation indicates meaningful progress but also highlights the importance of ongoing support and fine-tuning (Salleh et al., 2021).

Quality of Information Framework

The implementation of the EHR system has significantly bolstered data integrity and usability. Built-in validation features have curtailed the error rate from 5% to under 1%, enhancing the dependability of patient records. The intuitive user interface, coupled with comprehensive staff training, has led to greater adoption and improved confidence among users (Mishra et al., 2022).

Data privacy was another critical focus, with robust encryption protocols and stringent access controls ensuring HIPAA compliance and protecting patient information (Mishra et al., 2024). The organization has institutionalized periodic audits to sustain these privacy standards. Patient satisfaction has concurrently improved, evidenced by streamlined processes and reduced waiting periods. Feedback tools such as surveys help gauge user experience and uncover opportunities for future enhancements (Salleh et al., 2021). Furthermore, the ability to update records in real time has improved the timeliness and accuracy of clinical decision-making.

Appendix 1 – Evaluation Plan Table

Goals from the Implementation Plan	Framework Component(s)	Measurements	Frequency of Measurement	Purpose of Measurements
Efficient EHR Implementation	Data accuracy, Infrastructure readiness	Retrieval time, Error rate, Outage logs, Training completion, Integration issues	Monthly	Assesses system efficiency, reliability, and user adaptation
Optimize Accuracy and Workflow	Workflow effectiveness, Data processing	Task time, Error-free entries, Delay points, Staff feedback, System feature usage	Monthly	Ensures workflow optimization, detects inefficiencies
Staff Training and Education	Training adequacy, User proficiency	Training completion, Proficiency scores, Support requests, Satisfaction levels, Retention rates	Monthly	Identifies training gaps, monitors knowledge retention

Outcomes of Quality Care Framework

The new EHR system has had a transformative effect on clinical workflows. Average data access time has been reduced from 20 minutes to just 2 minutes, empowering healthcare providers with timely information for swift decision-making. The integration of real-time data with decision-support tools enhances the appropriateness and personalization of treatment strategies (Alexiuk et al., 2023).

Another critical improvement lies in team-based care coordination. The EHR has streamlined interdepartmental communications, minimizing delays and redundancies. Evidence of this includes a reduction in readmission rates and improvement in care outcomes, as reflected in recent performance metrics (Subbe et al., 2021).

Sustained improvements will depend on continuous monitoring and the timely resolution of emerging issues. This underscores the need for ongoing technical and clinical evaluations to maintain system alignment with evolving healthcare needs.

Structural Quality Framework

The success of the EHR implementation also owes much to a well-supported organizational structure. Executive leadership provided essential backing by allocating financial and personnel resources. Rigorous testing of hardware components ensured system readiness to handle high volumes of data storage and processing.

Evaluation of the software confirmed that it was functional, intuitive, and compatible with the institution’s existing systems (Shaikh et al., 2022). Feedback mechanisms allowed staff to suggest usability improvements, which were addressed through periodic software updates and system refinements.

Upgrades to IT infrastructure, including network bandwidth and cybersecurity measures, played a key role in supporting seamless EHR operations (Fennelly et al., 2020). To uphold system effectiveness, investments in both technology and personnel training must continue.

Recommendations for Further Improvement

To build on current successes, several recommendations have been proposed. Establishing recurring training initiatives will address ongoing competency gaps and reinforce system fluency. The formation of a dedicated IT support team will help resolve technical issues efficiently and reduce system downtime.

Enhancements to decision-support functionalities will aid clinicians in making evidence-based decisions, further elevating patient care standards (Sutton et al., 2020). Engaging users in a structured feedback loop will help identify user concerns and areas requiring upgrades. Strategic investments in IT infrastructure will accommodate system expansion and evolving operational demands.

Regular audits will be instrumental in maintaining HIPAA compliance and operational integrity. Finally, involving stakeholders in the continuous improvement process will reinforce organizational commitment and reduce resistance to future changes (Talwar et al., 2023).

Conclusion

The transition to an EHR system has successfully addressed the limitations of manual record-keeping by enhancing accuracy, reducing errors, and increasing care efficiency. Leadership commitment, structured training, and technical upgrades were instrumental in driving this change. While early challenges were encountered, the overall result is a more reliable and efficient healthcare information system. Continued optimization and stakeholder engagement will ensure the EHR system remains aligned with the organization’s long-term goals for quality and patient-centered care.

References

Alexiuk, M., Elgubtan, H., & Tangri, N. (2023). Clinical decision support tools in the EMR. Kidney International Reports, 9(1). https://doi.org/10.1016/j.ekir.2023.10.019

Fennelly, O., Cunningham, C., Grogan, L., Cronin, H., Shea, C. O., Roche, M., Lawlor, F., & Hare, N. O. (2020). Successfully implementing a national electronic health record: A rapid umbrella review. International Journal of Medical Informatics, 144(104281). https://doi.org/10.1016/j.ijmedinf.2020.104281

NURS FPX 6416 Assessment 3 Evaluation of an Information System Change

Mishra, V., Gupta, K., Saxena, D., & Singh, A. K. (2024). A global medical data security and privacy preserving standards identification framework for electronic healthcare consumers. IEEE Transactions on Consumer Electronics, 1–1. https://doi.org/10.1109/tce.2024.3373912

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/

Salleh, M. I. M., Abdullah, R., & Zakaria, N. (2021). Evaluating the effects of electronic health records system adoption on the performance of Malaysian health care providers. BioMed Central Medical Informatics and Decision Making, 21(1). https://doi.org/10.1186/s12911-021-01447-4

Shaikh, M., Vayani, A. H., Akram, S., & Qamar, N. (2022). Open-source electronic health record systems: A systematic review of most recent advances. Health Informatics Journal, 28(2). https://doi.org/10.1177/14604582221099828

Subbe, C. P., Tellier, G., & Barach, P. (2021). Impact of electronic health records on predefined safety outcomes in patients admitted to hospital: A scoping review. British Medical Journal Open, 11(1). https://doi.org/10.1136/bmjopen-2020-047446

Sutton, R., Pincock, D., Baumgart, D., Sadowski, D., Fedorak, R., & Kroeker, K. (2020). An overview of clinical decision support systems: Benefits, risks, and strategies for success. Non-profit Journalism Digital Medicine, 3(1), 1–10. https://doi.org/10.1038/s41746-020-0221-y

NURS FPX 6416 Assessment 3 Evaluation of an Information System Change

Talwar, S., Dhir, A., Islam, N., Kaur, P., & Almusharraf, A. (2023). Resistance of multiple stakeholders to E-health innovations: Integration of fundamental insights and guiding research paths. Journal of Business Research, 166, 114135. https://doi.org/10.1016/j.jbusres.2023.114135