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 transition from our existing paper-based record-keeping system to an Electronic Health Record (EHR) system was implemented to address critical inefficiencies and security vulnerabilities. The previous system’s average data retrieval time was 20 minutes, and the 5% error rate due to manual entry and misfiling created delays in patient care and risks to patient safety. The EHR implementation was structured in three phases: Phase 1 focused on vendor selection and initial training, Phase 2 on deployment and integration, and Phase 3 on evaluation and refinement. The evaluation indicates that while initial resistance and technical issues were encountered, the transition has led to substantial improvements in data management, patient safety, and overall care quality.

Quality of Information Framework

The EHR system has markedly enhanced the completeness and correctness of patient data. Automated data validation tools integrated into the EHR have reduced the error rate from 5% to less than 1%, ensuring higher accuracy in patient records. User satisfaction has significantly improved due to the system’s user-friendly interface and the extensive training provided, which has increased staff competence and confidence (Mishra et al., 2022). Patient privacy has been a priority, with advanced encryption and strict access controls implemented to safeguard sensitive information and comply with HIPAA regulations (Mishra et al., 2024). Systematic audits are conducted to ensure adherence to privacy standards. Patient satisfaction has also increased, reflected in reduced wait times and more efficient care processes. Surveys and feedback mechanisms have been employed to assess and enhance user satisfaction and privacy protections continuously (Salleh et al., 2021). The system’s ability to integrate real-time updates has been a critical factor in improving data reliability and patient outcomes.

Outcomes of Quality Care Framework

The EHR system has led to significant improvements in the efficiency of care delivery. Data retrieval times have been reduced from 20 minutes to an average of 2 minutes, allowing for faster access to patient information and timely decision-making. The integration of real-time data and decision-support tools has enhanced the appropriateness of care by providing clinicians with accurate and up-to-date information, which supports better clinical decisions and personalized patient interventions (Alexiuk et al., 2023). The EHR system has also streamlined care coordination by facilitating seamless communication between different care teams and departments. Metrics such as reduced hospital readmission rates and improved treatment outcomes indicate that the system has positively impacted patient care (Subbe et al., 2021). Continuous monitoring is necessary to address any emerging issues and ensure sustained improvements in care efficiency and appropriateness.

Structural Quality Framework

Organizational support for the EHR implementation has been robust, with senior executives playing a pivotal role in securing resources and championing the project. The effectiveness of the hardware has been assessed through rigorous testing to ensure it meets the demands of the EHR system, including data processing and storage requirements (Shaikh et al., 2022). The software’s performance has been evaluated for functionality, user-friendliness, and integration with existing systems (Shaikh et al., 2022). Feedback from staff has been used to identify areas for improvement in the software interface and features. The overall functionality of the system has been enhanced through regular updates and maintenance, addressing any technical issues promptly. The IT infrastructure, including network connectivity and data security measures, has been upgraded to support the EHR system (Fennelly et al., 2020). Continued investment in technology and staff training is essential to maintaining the system’s effectiveness and supporting its ongoing evolution.

Evaluation and Analysis

In Phase 1 (Months 1-2), the selection of the EHR vendor was completed successfully, though some initial resistance from staff familiar with the paper-based system was encountered. Initial training sessions addressed these concerns but revealed areas for additional support. Phase 2 (Months 3-4) involved deploying the EHR system and integrating it with existing workflows. Temporary disruptions occurred, necessitating further training and adjustments to system configurations. Phase 3 (Months 5-6) focused on evaluating the system’s performance and making refinements based on user feedback and performance metrics. Data retrieval times and error rates improved significantly, though ongoing technical support was required to resolve minor issues. The evaluation process included assessing user satisfaction through surveys and monitoring system performance to ensure it met the defined criteria for success (Salleh et al., 2021). The findings indicate that while the transition has been largely successful, continued efforts are needed to address residual challenges and optimize system performance.

Recommendations for Further Improvement

To enhance the EHR system’s effectiveness, we recommend implementing ongoing training programs to address staff proficiency gaps and ensure continuous improvement. Establishing a dedicated technical support team will provide timely assistance and address any system issues promptly. Regular updates to the decision-support tools and system features will further improve clinical decision-making and patient care (Sutton et al., 2020). Developing a feedback loop with users will help identify areas for enhancement and address any emerging concerns. Investing in additional technology and infrastructure upgrades will support the system’s scalability and functionality. Regular reviews and audits should be conducted to ensure compliance with privacy standards and operational efficiency. Engaging stakeholders in the continuous improvement process will help maintain buy-in and address any resistance to change (Talwar et al., 2023). These measures will ensure the EHR system continues to meet organizational needs and contribute to high-quality patient care.

Conclusion

The transition to an EHR system has effectively addressed the inefficiencies and risks associated with our previous paper-based record-keeping system. Strong leadership, thorough training, and technical support have facilitated a successful modernization of data management and patient care. The EHR system has resolved many operational challenges, enhancing data accuracy, reducing wait times, and improving overall care quality. As we continue to refine and optimize the system, our commitment to high-quality, patient-centered healthcare remains unwavering. We are dedicated to ensuring the EHR system’s continued success and its positive impact on healthcare delivery.

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

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

NURS FPX 6416 Assessment 3 Evaluation of an Information System Change

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. (2020d). 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

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

Appendix 1

Evaluation Plan Table

Goals from the Implementation Plan	Framework Component(s)	Measurements	Frequency of Measurement	Reason for Chosen Measurements
1. Implement the EHR System Efficiently	Focuses on the completeness, correctness, and accuracy of data managed by the new EHR system. Includes the infrastructure and organizational support required for successful EHR implementation.	 Measures the average time to access patient records.  Tracks errors in data input.  Records frequency and duration of outages.  Percentage of staff using the EHR.  Percentage of staff completing training.  A number of problems during system integration.	On a monthly basis	 Ensures prompt access to patient information.  Validates accuracy of data entry.  Monitors system reliability.  Assesses staff adaptation to the system.  Tracks training completion.  Identifies and resolves integration issues.
2. Optimize Data Accuracy and Workflow	Pertains to the accuracy and completeness of data as it is handled and processed within the system. Involves the efficiency and effectiveness of workflows and processes facilitated by the EHR system.	 Percentage of error-free data entries.  Time for task completion and overall efficiency.  Identifies points of delay.  Qualitative feedback from staff.  Time to identify and fix errors.  Percentage of EHR features used.	On a monthly basis	 Maintains high standards for data accuracy for effective patient care and record-keeping.  Evaluates workflow efficiency to identify areas for improvement.  Detects and addresses delays to enhance overall workflow efficiency.  Provides insights into staff perceptions of workflow changes to guide adjustments.  Ensures quick resolution of errors to maintain smooth operations.  Measures EHR feature utilization to ensure total system use. Capabilities are being fully leveraged.
3. Train and Educate Staff on the EHR	Addresses the effectiveness of the training and support infrastructure needed for staff education. Ensures that training materials are accurate and that staff can effectively use the EHR to manage data accurately.	 Percentage of staff who complete training.  Staff proficiency tests.  Number and types of support requests.  Staff satisfaction surveys.  Long-term retention of training content.  Identification of additional training requirements.	On monthly basis	 Ensures all staff complete necessary training for effective system use.  Assesses staff proficiency to ensure competent operation of the EHR system.  Tracks support requests to identify common issues and areas for improvement.  Measures staff satisfaction with training to meet their needs and expectations.  Evaluates retention of training content to ensure lasting competence.  Identifies additional training needs to address gaps in knowledge or skills.