Assignment: Literature Review: The Use of Clinical Systems to Improve Outcomes and Efficiencies
Clinical systems, such as electronic health records (EHRs), can be used to improve outcomes and efficiencies in healthcare by providing clinicians with real-time access to patient information, allowing for more accurate and efficient diagnoses, treatment planning, and follow-up care. Additionally, these systems can facilitate communication and collaboration among healthcare providers, which can lead to improved coordination of care and better patient outcomes. Other features of clinical systems, such as decision support tools and population health management capabilities, can also help to improve the quality and safety of care while reducing costs. However, the implementation of clinical systems can be complex and requires a significant investment of time, money and resources.

New technology—and the application of existing technology—only appears in healthcare settings after careful and significant research. The stakes are high, and new clinical systems need to offer evidence of positive impact on outcomes or efficiencies.

Nurse informaticists and healthcare leaders formulate clinical system strategies. As these strategies are often based on technology trends, informaticists and others have then benefited from consulting existing research to inform their thinking.

In this Assignment, you will review existing research focused on the application of clinical systems. After reviewing, you will summarize your findings.

To Prepare:

Review the Resources and reflect on the impact of clinical systems on outcomes and efficiencies within the context of nursing practice and healthcare delivery.
Conduct a search for recent (within the last 5 years) research focused on the application of clinical systems. The research should provide evidence to support the use of one type of clinical system to improve outcomes and/or efficiencies, such as “the use of personal health records or portals to support patients newly diagnosed with diabetes.”
Identify and select 5 peer-reviewed articles from your research.
The Assignment: (4-5 pages)

In a 4- to 5-page paper, synthesize the peer-reviewed research you reviewed. Be sure to address the following:

Identify the 5 peer-reviewed articles you reviewed, citing each in APA format.
Summarize each study, explaining the improvement to outcomes, efficiencies, and lessons learned from the application of the clinical system each peer-reviewed article described. Be specific and provide examples.

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Chapter 14, “The Electronic Health Record and Clinical Informatics” (pp. 267–287)
Chapter 15, “Informatics Tools to Promote Patient Safety and Quality Outcomes” (pp. 293–317)
Chapter 16, “Patient Engagement and Connected Health” (pp. 323–338)
Chapter 17, “Using Informatics to Promote Community/Population Health” (pp. 341–355)
Chapter 18, “Telenursing and Remote Access Telehealth” (pp. 359–388)

Dykes, P. C., Rozenblum, R., Dalal, A., Massaro, A., Chang, F., Clements, M., Collins, S. …Bates, D. W. (2017). Prospective evaluation of a multifaceted intervention to improve outcomes in intensive care: The Promoting Respect and Ongoing Safety Through Patient Engagement Communication and Technology Study. Critical Care Medicine, 45(8), e806–e813. doi:10.1097/CCM.0000000000002449 (2018c). What is an electronic health record (EHR)? Retrieved from

Rao-Gupta, S., Kruger, D. Leak, L. D., Tieman, L. A., & Manworren, R. C. B. (2018). Leveraging interactive patient care technology to Improve pain management engagement. Pain Management Nursing, 19(3), 212–221. doi:10.1016/j.pmn.2017.11.002

Note: You will access this article from the Walden Library databases.

Skiba, D. (2017). Evaluation tools to appraise social media and mobile applications. Informatics, 4(3), 32–40. doi:10.3390/informatics4030032

Note: You will access this article from the Walden Library databases.
Sample Answer Guide:
Clinical Information Systems to Improve Outcomes
Clinical information systems are key in enhancing patient outcomes by utilizing artificial intelligence (AI). These systems go beyond the capacity of human diagnosis and analysis. The implementation of AI in healthcare will improve the quality of care. Four peer-reviewed studies were analyzed to assess the impact of AI in the healthcare sector. Rabbani et al. (2018) found that computer-aided systems can improve early diagnosis of lung cancer. Ahuja (2019) suggests that with advancements in healthcare technology, AI can assist radiologists in their work. Schonberger et al. (2019) discovered that AI has improved decision-making abilities in healthcare. Dankwa-Mullan et al. (2019) found that AI is vital in transforming care for diabetic patients. The aim of the essay is to examine the impact of AI on healthcare using these peer-reviewed studies

In order to improve patient outcomes, clinical information systems are important. The information systems surpass the capacity of humans to diagnose diseases and analyze data. Adoption of information systems with artificial intelligence in healthcare will increase the quality of care. The essay analyzes four scholarly journals on the deployment of artificial intelligence in the healthcare industry. Rabbani et al. (2018) claim that computer-aided techniques can improve lung cancer early detection. Ahuja (2019) proposes that as healthcare technology continues to advance, artificial technology can enhance radiologists. Schonberger et al. (2019) acknowledge that innovation has contributed to the technology’s decision-making capabilities. Dankwa-Mullan et al. (2019) acknowledge that artificial intelligence is essential for changing diabetic patient care. Using peer-reviewed papers, the objective of this essay is to investigate artificial intelligence and its impact on the provision of care.
Summary of Each Study, Improvement to Outcomes, and Lessons Learned
Rabbani et al. (2018) conducted a study on the role of artificial intelligence in the treatment of lung cancer patients. While lung cancer is one of the major causes of death worldwide, the study indicates that artificial intelligence can improve the disease’s diagnosis, treatment, and management. Rabbani et al. (2018) claim that computer-aided techniques can improve lung cancer early detection. A late diagnosis, which limits therapy and management, is identified as a barrier in the fight against lung cancer by the study. The technique can enhance the effectiveness of early disease diagnosis before malignant cells spread, advance to chronic phases, and jeopardize the patient’s life.
I’ve discovered that artificial technology can enhance the diagnosis, therapy, and management of non-small cell lung cancer. According to Rabbani et al. (2018), computer systems are capable of generating personalized diagnoses and treatments. Physicians tailor the therapy procedure to the patient’s genetics, molecular characteristics, and histology characteristics. In the fight against cancer, if the diagnosis and therapy are tailored, greater success can be achieved. As a result of tailoring treatment programs, healthcare personnel may provide patients with care more efficiently. The results will result in earlier identification and diagnosis, improved treatment, and lower mortality rates (Rabbani et al., 2018). Despite the limitations of technology in the healthcare industry, it can increase the quality of care and safety for patients.
Ahuja (2019) investigated the effect of artificial intelligence in medicine on the future function of physicians. This study investigates the future impact of technology on the function of healthcare professionals. Ahuja (2019) thinks that if healthcare technology continues to advance, artificial technology can replace radiologists. Despite the impossibility of a total replacement of healthcare staff, the systems would boost healthcare operations, according to the conclusions of the study. The technology will supplement professionals, including pathologists, cardiologists, radiologists, and ophthalmologists, according to Ahuja (2019). Increasing the number of healthcare positions will increase the efficacy with which a huge population may be treated.
Ahuja (2019) acknowledges that technology will not replace healthcare professionals. The necessity of a physician-patient or nurse-patient connection is one of the causes. Patients must encounter a genuine person when they visit a healthcare provider for a checkup or treatment. I have realized that it is difficult to replace the human element in the healthcare industry. The importance of human emotional and social interactions in the provision of care Patients seek not only equipment that can heal their ill bodies, but also human connections. Another lesson is that humans are required to offer care in order to avoid the possibility of medical errors that can erode patient confidence.
The current state of artificial intelligence in the healthcare industry is described by Schonberger et al. (2019). According to the findings, recent advancements in the healthcare industry have increased the precision of imaging and signal detection. Schonberger et al. (2019) acknowledge that innovation has contributed to the technology’s decision-making capabilities. The technology will improve the lives of patients, but it will also create a number of ethical difficulties. According to Schonberger et al. (2019), some ethical concerns include justice and discrimination, moral accountability, and autonomy. Despite the fact that it assumes human capabilities, artificial intelligence cannot monitor ethical issues such as justice and prejudice. The findings support the conclusions of other researchers that technology cannot erase human participation.
I’ve discovered that the capabilities of artificial intelligence can enhance the quality of care. Despite its virtues, the healthcare industry must recognize the technology’s limitations. For instance, artificial intelligence is biased since its judgements are supported by many options and algorithms. Inconclusive connections are another danger posed by the technology. Schonberger et al. (2019) remark that various and demanding law enforcement sectors have utilized artificial intelligence. Adoption of technology in the healthcare industry offers obstacles that can reduce the quality of services. Human participation can mitigate the dangers of artificial intelligence.
Dankwa-Mullan et al. (2019) acknowledge that artificial intelligence is essential for changing diabetic patient care. The study focuses on creative methods for enhancing care quality. Clinical decision assistance, automated retinal screening, and patient self-management technologies can be enhanced by a higher standard of care. Enhancing data analysis with predictive population risk stratification is another area of focus. Dankwa-Mullan et al. (2019) demonstrate that the technological aspects of diabetic care can enhance the disease’s diagnosis, treatment, and management. Other outcomes include a reduction in pediatric death rates and the treatment of diabetes. The technology will increase the efficiency with which diabetic patients are treated.
I’ve learnt that artificial intelligence offers in-depth health data learning. The data analysis enhances population risk stratification predictions. The strategy is crucial for enhancing the response to diabetes, which is responsible for tens of thousands of annual deaths. Informaticians and knowledge workers in the healthcare industry can employ artificial intelligence to build techniques for combating the world’s chronic diseases (Dankwa-Mullan et al., 2019). Training the nurses, physicians, and technical clinicians will be a component of the response processes. Patient education will be vital for improving the self-management of the disease from the time of diagnosis until death or complete recovery.
Since its acceptance in disease diagnosis, treatment, disease management, and data analysis, artificial intelligence has a favorable impact on the healthcare sector. Adoption of information systems with artificial intelligence in healthcare will increase the quality of care. The four articles acknowledge that computer-assisted solutions can enhance the early diagnosis of lung cancer and diabetes. Innovation has led to the enhancement of technology’s decision-making capabilities and the number of specialists. The technology has the potential to revolutionize healthcare delivery. Transformation entails early identification of chronic diseases, decision support for healthcare professionals, and data analysis to discover significant health trends.

Ahuja, A. S. (2019). The impact of artificial intelligence in medicine on the future role of the physician. PEERJ, 7, e7702.
Dankwa-Mullan, I., Rivo, M., Sepulveda, M., Park, Y., Snowdon, J., & Rhee, K. (2019). Transforming diabetes care through artificial intelligence: the future is here. Population Health Management, 22(3), 229-242.
Rabbani, M., Kanevsky, J., Kafi, K., Chandelier, F., & Giles, F. J. (2018). Role of artificial intelligence in the care of patients with nonsmall cell lung cancer. European Journal of Clinical Investigation, 48(4), e12901.
Schonberger, D. (2019). Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. International Journal of Law and Information Technology, 27(2), 171-203.