NURS 6051 Week 8 Assignment Literature Review

NURS 6051 Week 8

Assignment Literature Review

Student Name

Walden University

NURS 6051

Professor Name

Date

Literature Review: The Use of Clinical Systems to Improve Outcomes and Efficiencies

Clinical systems, such as electronic health records (EHRs) and clinical decision support systems (CDSS), play a vital role in enhancing patient care by improving outcomes, streamlining workflows, and supporting clinical decision-making. As technology continues to evolve, healthcare professionals must evaluate its effectiveness based on evidence-based research. This paper focuses on four peer-reviewed studies that examine the application of EHRs integrated with CDSS in managing chronic diseases. The analysis highlights improvements in patient outcomes, care efficiencies, and key lessons learned from these systems.

Annotated Bibliography

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

CDS tools have been integrated within EMR systems, specifically tools such as the Statin Choice Decision Aid and the Kidney Failure Risk Equation (KFRE), which have enhanced clinical effectiveness and workflow. These instruments incorporate patients’ EMR data to offer accurate, timely, individualized recommendations for patient care. For instance, the Statin Choice Decision Aid facilitates SDM by quantifying individual cardiovascular risks, which helps in statin therapy decision-making and documentation. This increases the likelihood of following the guidelines and, at the same time, decreases the possibility of the clinician being unsure of what to do. Similarly, the KFRE is designed to automatically calculate the risk of developing kidney failure through values that are usually documented in patients’ records to help in the early identification of patients with poor prognoses. A study conducted at Johns Hopkins, where KFRE was implemented into the Epic EMR, found that nephrologists found the automated risk projections useful in planning for kidney replacement therapy and in facilitating communication with other care providers. These tools helped minimize the time spent when doing data entry and ensured more consistency in the clinical assessment. The success factors include the adoption of CDS into the current working systems, the quality of the evidence that supports the CDS, and ways of avoiding alert fatigue to make users continue to trust the generated alerts.

Chen, W., Howard, K., Gorham, G., O’Bryan, C. M., Coffey, P., Balasubramanya, B., Abeyaratne, A., & Cass, A. (2022). Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: A systematic review and meta-analysis. Journal of the American Medical Informatics Association : JAMIA, 29(10), 1757–1772. https://doi.org/10.1093/jamia/ocac110

The study focused on the design, functionality, and cost implications of EHR-based CDSS intended for chronic diseases, including diabetes, hypertension, cardiovascular disease, and chronic kidney disease. The reviews indicated that out of the 76 studies on effectiveness, 63% reflected enhanced clinical outcomes such as increased compliance with guidelines and medications and screening for diseases, among others. For example, the use of CDSS to support the care of diabetes patients was effective in enhancing HbA1c testing and subsequent management. However, the observed enhancements were mostly moderate and varied because of variations in implementation conditions and the design of the systems. Even when the effect sizes are small, CDSS can enhance efficiency by preventing clinical mistakes and optimizing care delivery. The nine studies reviewed in the economic evaluation greatly varied in cost-effectiveness, with ICR ranging between $2,192 and $151,955 per QALY. Some lessons that can be learned are the need to design CDSS for specific clinical tasks, incorporating interfaces that are friendly to the users, and incorporating the systems into EHRs for better usability, adoption, and sustainability.

Gholamzadeh, M., Abtahi, H., & Safdari, R. (2023). The application of knowledge-based clinical decision support systems to enhance adherence to evidence-based medicine in chronic disease. Journal of Healthcare Engineering, 23, e8550905. https://doi.org/10.1155/2023/8550905

The use of knowledge-based CDSSs in managing chronic illnesses has been seen to enhance treatment results, effectiveness, and processes. The 38 studies revealed that a notable majority of the patients achieved better adherence to EBM in general (84.2%); it led to improved diagnostic accuracy (81.6%), and the identification of high-risk patients was also improved (50%). For instance, several systems decreased the overall medical mistakes (47.4%) by providing patient-specific alerts in real-time and suggested treatment plans, thus assisting clinicians in avoiding certain omitted protocols or conflicting medications. An American study analyzed that, by implementing the CDSS in the EMR, the rate of controlled hypertension was enhanced by 20%. In a case in Europe, CDSS was implemented to strengthen the diabetes care pathways and to achieve uniformity and better HbA1c results. Some benefits revolved around time-saving via decision pathways and easing the cognitive load of clinicians through alerting and updated evidence. The main issues in the three articles are on the adoption of EMR systems, and the lessons learned pointed out the need to integrate EMR systems and train clinicians. Knowledge-based CDSSs played a critical role in improving clinical decision support and supporting evidence-based patient-centered care.

Grechuta, K., Shokouh, P., Alhussein, A., Wieland, D., Meyerhoff, J., Gilbert, J., Purushotham, S., & Rolland, C. (2024). Benefits of clinical decision support systems for the management of noncommunicable chronic diseases: Targeted literature review. Interactive Journal of Medical Research, 13, e58036. https://doi.org/10.2196/58036

The identified literature review outlines some of the enhanced results and benefits in the view of more management of NCDs resulting from the use of CDSSs. The studies on integrating CDSSs, including those connected with the EMRs, showed significant improvement in quality assurance (69 % of studies) and clinical outcomes (41 %). These systems enhanced treatment advice, patient critical parameters, and disease prognosis estimation, minimizing human intervention and errors. For instance, EMR-integrated CDSSs empower timely and appropriate alerts and suggestions during consultations to make patient care efficient and specific. Another one showed that CDSS alerts led to better evaluation of patients’ cardiovascular risk by changing medications according to the guidelines. Another system also assisted the providers in attaining better HbA1c control because of the recommendation for medication dosage adjustment and lifestyle changes. Moreover, CDSSs were identified to help promote interdisciplinary care of groups of nurses, physicians, and specialists by improving communication and synchronizing the interventions provided by the software with the existing guidelines. Key points learned include the need to focus on the system’s user, integration of the EMR, and constant training to enhance usage in primary care facilities.

Summary of the Learnings

The synthesis of the four peer-reviewed studies highlights the critical role of CDSS integrated with EMRs in enhancing the management of chronic diseases. Across diverse clinical settings, CDSS tools such as the Statin Choice Decision Aid and the KFRE demonstrated improved clinical decision-making, efficiency, and workflow integration, particularly when tailored to individual patient data (Alexiuk et al., 2023). Systematic reviews further support these findings, revealing that CDSS use in chronic disease care—such as for diabetes and hypertension—resulted in moderate yet meaningful improvements in clinical outcomes and guideline adherence (Chen et al., 2022). Knowledge-based systems especially boosted adherence to evidence-based medicine, improved diagnostic accuracy, and helped identify high-risk patients through real-time alerts and reduced clinical errors (Gholamzadeh et al., 2023). Moreover, CDSS tools promoted interdisciplinary collaboration, optimized treatment plans, and reduced the cognitive burden on clinicians (Grechuta et al., 2024). Common success factors across all studies included seamless EMR integration, user-centered design, evidence-based content, and ongoing clinician training. Together, these findings affirm that CDSS, when effectively implemented, support personalized, efficient, and evidence-based care for patients with chronic conditions.

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