TN004 Assignment Technologies Supporting Applied Practice

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TN004 Assignment

Technologies Supporting Applied Practice and Optimal Patient Outcomes

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Walden University

TN004 Assignment

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Date

Technologies Supporting Applied Practice and Optimal Patient Outcomes

The importance of clinical systems in transforming the healthcare delivery by enhancing efficiency, safety and patient centered outcomes is critical. Perhaps none of the disciplines better personify this idea than nursing informatics, which incorporates both nursing knowledge and information and communication technology to help streamline work processes and thereby improve patient care (Nashwan et al., 2025). The last decade is connected with the greater acceptance of the systems such as electronic health records (EHRs), clinical decision support systems (CDSS), telehealth devices, and AI-based tools, especially after the COVID-19 crisis that provoked an understanding of the need to build a digital solution. In spite of its widespread implementation, there are still questions of usability, compatibility problems and visible impact on the outcome and efficiency.

Annotated Bibliography

Tapuria, A., Porat, T., Kalra, D., Dsouza, G., Xiaohui, S., & Curcin, V. (2021). Impact of patient access to their electronic health record: systematic review. Informatics for Health and Social Care, 46(2), 194–206. https://doi.org/10.1080/17538157.2021.1879810 

Tapuria (2021) explores the effect of the direct provision of patients with access to their electronic health records (EHRs), including the effect on patient attendance, management, and clinical outcomes. The article summarizes the results of observational and quasi-experimental studies to determine the efficiency of patient-facing EHR portals in diverse healthcare settings. The topic is continuously proven to be the patient access to EHRs that are linked to improved health literacy, an increase in adherence to treatment regimens, and communication between patients and providers. Patients actively using portals were showing enhanced management of chronic diseases such as adherence to medication and follow-up visits on time. The article identifies a number of advantages of EHRs to patients. These involve increased transparency in the care process, increased patient empowerment and improved administrative workload reduction because of fewer telephone questions. Well-informed patients were reported to be in a better position to participate in shared decision-making, thus simplifying the communication process by nurses. Nevertheless, Tapuria also identifies important constraints: the arrangement and the functionality of portals depend on the system, the adoption rates among patients with low digital literacy or lack of access to technology are usually low, and the privacy and information security are also a constant problem.

In terms of efficiency, the study points out that many successful EHR portal implementations by organizations reported more efficient workflow, medication reconciliation, and reduced duplicating processes. Nevertheless, according to Tapuria, these are achieved only when institutions offer proper training of staff, educate patients, and offer ongoing support. One of the main lessons learnt is that it not only is necessary to introduce a portal but to actively work on the engagement strategies that would motivate the staff members and patients to use it. To the nursing practice, the present work is of special importance because it highlights the two-fold role of a nurse that can be played by informing patients and introducing technology into normal working procedures. Nurses play a mediating role and assist patients to make sense of their health and apply it in a way they apply to self-care. The results also bring out the role of organizational culture in facilitating the adoption of technology, where nurses play the role of change agents. Conclusively, the literature is indicating that EHR portals when well deployed, further increase patient autonomy and professional effectiveness.

Beyond the healthcare sphere, the contribution of Tapuria to the discourse of digital equity is part of the continued debate on this topic. Although patient portals have various obvious benefits, the differences in the rates of their use indicate that the strategies should be designed to target vulnerable groups. By filling these improper areas, it will be possible to guarantee that the advantages of access to EHR, namely, better results, fewer inefficiencies, and increased patient involvement, will be distributed fairly. In the future sphere of nursing informatics projects, this strengthens the need to prioritize the creation of patient-centred solutions considering diversity in digital skills and access, as well as the trust in technology.

Rony, M. K. K., Parvin, Mst. R., & Ferdousi, S. (2023). Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nursing Open, 11(1), 1–9. https://doi.org/10.1002/nop2.2070 

Rony et al. (2023) discuss the increasing role of artificial intelligence (AI) in nursing practice and how AI-based tools could facilitate decision-making, optimize processes, and help improve patient safety. The article is presented in the form of a narrative review of the literature and case study examples on the way predictive analytics, machine learning algorithms, and natural language processing (NLP) were used in the clinical setting. Data indicate that AI is able to recognize the early signs of patient decline, the presence of high-risk conditions, including sepsis, and can optimize resource allocation within a hospital. With its ability to offer timely information, AI systems enable nurses to intervene earlier on and offer more effective and targeted care. The advantages, which are described in the work, are impressive. AI could improve the safety of the patients providing early notices, rank of tasks, and assist with more productive workflows. The examples provided in cases indicated that the use of AI minimized unnecessary documentation, better scheduling, and even decreased the rates of adverse events. 

Nevertheless, at the same time, Rony et al. note major limitations. They involve the threat of biased algorithms, inconsistency in the quality of data, and reluctance of nurses to work with black box systems, which are not transparent. The authors underline the fact that trust and explainability are not a priority, and unless these issues are considered, the impact of AI systems may become irrelevant in clinical practices. Outcomes and efficiency In terms of outcomes and efficiency, AI shows potential in terms of reducing unplanned ICU transfers, improving the triage workflow, and improving predictive care within the clinical decision support context. The implementation lessons emphasize that it is important to involve nurses in the development process, offer training of a high standard, and incorporate robust ethical protective measures to safeguard patient privacy. The paper highlights the importance of equity in the AI results so that differences in care provision may not continue to exist. To nursing practice, the article confirms the transformative nature of AI but warns that its use should not be over relied upon. AI is not intended to replace clinical judgment, but must be viewed complementary to it. Nurses will continue to play a vital role in confirming AI suggestions, putting recommendations into perspective in the context of patient care, and protecting the humanistic side of work. Placing AI as an evidence-based support tool, nursing professionals will be able to use it to increase the efficiency and quality and preserve accountability in the decision-making process.

Overall, Rony et al. (2023) emphasize on the important intersection of nursing informatics and organizational strategy. The implementation of AI needs not only technical integration but also the cultural preparation of healthcare teams to be successfully implemented. Being able to build trust by communicating transparently, being inclusive in designing algorithms, and aligning AI systems with organizational objectives are key measures that can help make the most out of AI systems. This view supports that AI in nursing is not merely a technological industry but an agent of change to incorporate system-wide change with ethical leadership.

Brown-Johnson, C. G., Lessios, A. S., Thomas, S., Kim, M., Fukaya, E., Wu, S., Kling, S. M. R., Brown, G., & Winget, M. (2023). JMIR Formative Research, 7(1), e43258. https://doi.org/10.2196/43258 

Rony et al. (2023) talk about the growing popularity of artificial intelligence (AI) in nursing practice and how AI-driven technologies may assist in decision-making, improving the process, and supporting patient safety. The article is written as a review of the literature and case study examples in the format of a narrative, about how predictive analytics, machine learning algorithms and natural language processing (NLP) were applied in the clinical setting. Statistics show that AI can detect the initial signs of patient deterioration, high-risk factors, such as sepsis, and can effectively manage resource use in a hospital. Having the capacity to provide nurses with timely information as it can, AI systems allow healthcare workers to intervene sooner to provide more effective and targeted treatment. The benefits that are presented in the work are astounding. AI has the capacity to advance the safety of the patients by sending early notices, prioritize assignments, and support more effective ways of work. Examples given in cases demonstrated that the application of AI reduced the superfluous paperwork, enhanced the schedule, and even the adverse incident rates were minimized. However, simultaneously, large limitations are reported by Rony et al. They comprise a risk of biased algorithms, unequal quality of information, and the unwillingness of nurses to operate with black box systems, as it is not transparent. The authors emphasize that trust and explainability are not a priority and, unless these concerns are taken into account, the influence of AI systems can turn out to be a pointless aspect of a clinical practice.

Outcomes and efficiency AI is promising in regards to the reduction of unexpected ICU transfers, enhancing the triage process, and the provided predictor care in the clinical decision support framework. The lessons related to the implementation also note that nurses should be engaged in the development process, training of high quality should be provided to them, and the ethical protection should be strong in order to protect the privacy of a patient. The paper indicates the essentiality of equity within the AI outcomes in such a way that disparities in the delivered care can no longer be present. The article affirms to the nursing practice that AI is transformative in nature but it should not be over relied on. AI does not aim to override clinical judgment, but should be regarded as having a complement. The role of nurses in confirming AI suggestions will remain important as it will put in perspective the recommendations in the context of patient care and safeguard the humanistic aspect of work. As an evidenced-based support tool, by positioning AI, nursing professionals should have an opportunity to enhance efficiency and quality and maintain accountability in the decision process.

In general, as released by Rony et al. (2023), nursing informatics and organizational strategy are an essential intersection. Implementation of AI should be technical, but also a successful cultural training of healthcare teams should be provided to successfully implement AI. The ability to develop trust through open communication, inclusive algorithm design, and correspondence with organizational goals are some of the most important steps that can assist in extracting the maximum out of AI systems. This perspective adheres to the fact that AI in nursing does not represent solely a technology sector; this is a change-making agent that is to be integrated in terms of system-wide change and moral leadership.

Grechuta, K., Shokouh, P., Alhussein, A., Müller-Wieland, D., Meyerhoff, J., Gilbert, J., Purushotham, S., & Rolland, C. (2024). Interactive Journal of Medical Research, 13, e58036–e58036. https://doi.org/10.2196/58036 

Grechuta et al. (2024) have reviewed the literature in order to assess the efficacy of the clinical decision support system (CDSS) as a means of enhancing health outcomes and clinician activities in healthcare. The review summarizes recent findings dedicated to the implementation of CDSS in clinical settings, in especially in nursing settings. The results indicate that the tools of CDSS are the most efficient when built into electronic health records (EHRs) and developed using user-friendly strategies. In particular, it has been demonstrated that the systems have increased compliance with clinical practice, decreased medication error rates, and helped to make timely decisions by giving context-based alerts and notifications. The advantages of CDSS are properly documented. Their benefits are reduced adverse drug events and improved patient safety, and standardized processes of care and clinical documentation. Through the course of practice, nurses are provided with efficient working processes and access to the evidence-based guidelines. There are however significant limitations mentioned in the review. A commonly occurring problem is the alert fatigue when clinicians receive too many or bad notifications they tend to ignore as overrides or distrust the system. The efficiency of the CDSS is also decreased by usability issues that are difficult to detect and inability to interoperate with the legacy systems.

On an outcomes and efficiency perspective, CDSS can have a great impact on process measures, including prompt medication administration, prompt sepsis identification, and adherence to preventive care measures. Among the lessons learned during successful implementations highlighted in the review is the fact that the design process should be iterative, and that end-users need to be engaged in the development process, and alerts should be customized to particular clinical settings. In the absence of these considerations, CDSS may add more burdens to the situation instead of relieving them. To nursing practice, this review offers some rich information on how CDSS can be applied to improve decision-making, improve patient safety, and limit the number of mistakes. The results highlight the fact that successful adoption is possible only when nurses are involved in both the design and implementation stages in order to fit the real workflow. Grechuta et al. (2024) finally provide a conclusion that CDSS has a great potential of enhancing clinical outcomes and efficiency, although it can happen only in case the usability, trust, and the integration issues are properly managed.

Kwon, H., & Lee, D. (2024). Clinical decision support system for clinical nurses’ decision-making on nurse-to-patient assignment: A scoping review protocol. BMJ Open, 14(1), e080208–e080208. https://doi.org/10.1136/bmjopen-2023-080208 

Kwon et al. (2024) described a scoping review to assess the implementation of clinical decision support systems (CDSS) to enhance nurse-patient assignment (NPA). Distribution of workload and matching of both the workload with the acuity is a critical operational process since the patient safety, quality of care, and even the satisfaction of the nurse directly depend on nurse-patient assignment. The review has consolidated several studies using algorithm-related tools and decision supporting models that can achieve more productive and fair assignment processes. The results emphasize some of the main advantages of the use of CDSS in the field. Workload balancing systems assisted to lessen burnout in nurses, enhance patient monitoring, and decrease care event omissions. Various tools included the variables of patient acuity, staffing, and nurse competencies to give more objective and transparent assignment decisions. The increased productivity, manifesting as fewer hours of overtime and better patient results due to shorter response times was also shown by a number of pilot projects. However, it was also limited. The success of such systems would be dependent on data collection, which is demanding in clinical settings where pressures might be high and the data collection has to be in real-time. Furthermore, the obstacle to adoption like nurse resistance, which was related to the fear of loss of control, trust, and transparency in AI-based decisions, was also observed.

In terms of the outcomes and efficiency, the review highlights the CDSS as an emergent tool to enhance the equity in the workload, reduce the level of nurse fatigue, and enhance continuity of care. The lessons learned are that it is necessary to engage frontline nurses in the customization of assignment algorithms, that it is necessary to have override functions that acknowledge clinical judgment, and that it is necessary to train people properly to develop confidence in system suggestions. In the absence of such, possible gains may be sabotaged, as resistance to adoption may continue to hinder trust in automated systems. To the nursing practice, this article highlights the revolutionizing nature of informatics in the operational decision making process. Conventionally, NPA has been subjective and discretionary to managers, and this has in most situations caused inconsistency and dissatisfaction. CDSS represents a transparent, evidence-based solution and can maximize the use of the staff and patient safety at the same time. Moreover, as proposed in this review, incorporating CDSS into the staffing processes is consistent with the wider organization objectives of digital transformation and can form the basis of innovative applications like predictive workload modeling in the future. Through technology integration with frontline knowledge, nurse administrators can use CDSS not only to promote equity and efficiency but also promote professional health and achievement of patient outcomes.

Conclusion

The critical role of clinical systems in the future of nursing practice and enhancing healthcare delivery, as pointed out in this annotated bibliography is very crucial. In all five reviewed articles, there is one similarity: thoughtfully used, technologies (including electronic health records (EHRs), artificial intelligence (AI), telehealth, and clinical decision support system (CDSS)) may improve patient safety, increase efficiency, and empower clinicians and patients alike. All the studies follow distinct pathways, with patient portals enhancing engagement and self-management to improve care, AI facilitating the prediction of care and detection with assistance at an earlier stage, nurse-led telehealth enhancing continuity of care, CDSS improving clinical decision-making, and assignment systems optimizing workloads of nurses. Taken altogether, these results indicate that informatics-driven systems are not single entities, but they are interrelated components of a wide-scale digital health transformation.

Simultaneously, the literature explains that technology is not the panacea to success. Limitations, many of which are presented by usability concerns, alert fatigue, lack of equitable access, data quality issues, and non-acceptance, need to be mitigated through strong governance, training and involvement of clinicians in system design. As the greatest number of front line providers, nurses can be an invaluable part of closing the divide between technological innovation and patient use. Their involvement also makes these systems be able to not only enhance operational efficiency but also safeguard the humanistic elements of care.

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References for TN004 Assignment Technologies Supporting Applied Practice and Optimal Patient Outcomes

Brown-Johnson, C. G., Lessios, A. S., Thomas, S., Kim, M., Fukaya, E., Wu, S., Kling, S. M. R., Brown, G., & Winget, M. (2023). JMIR Formative Research, 7(1), e43258. https://doi.org/10.2196/43258 

Grechuta, K., Shokouh, P., Alhussein, A., Müller-Wieland, D., Meyerhoff, J., Gilbert, J., Purushotham, S., & Rolland, C. (2024). Interactive Journal of Medical Research, 13, e58036–e58036. https://doi.org/10.2196/58036 

Kwon, H., & Lee, D. (2024). Clinical decision support system for clinical nurses’ decision-making on nurse-to-patient assignment: a scoping review protocol. BMJ Open, 14(1), e080208–e080208. https://doi.org/10.1136/bmjopen-2023-080208 

Nashwan, A. J., Cabrega, J. A., Othman, M. I., Khedr, M. A., Osman, Y. M., El‐Ashry, A. M., Naif, R., & Mousa, A. A. (2025). The evolving role of nursing informatics in the era of artificial intelligence. International Nursing Review, 72(1), e13084. https://doi.org/10.1111/inr.13084  

Rony, M. K. K., Parvin, Mst. R., & Ferdousi, S. (2023). Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nursing Open, 11(1), 1–9. https://doi.org/10.1002/nop2.2070

Tapuria, A., Porat, T., Kalra, D., Dsouza, G., Xiaohui, S., & Curcin, V. (2021). Impact of patient access to their electronic health record: systematic review. Informatics for Health and Social Care, 46(2), 194–206. https://doi.org/10.1080/17538157.2021.1879810