NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

Sample Answer for NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies Included After Question

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 4 peer-reviewed research articles from your research.
For information about annotated bibliographies, visit https://academicguides.waldenu.edu/writingcenter/assignments/annotatedbibliographies

The Assignment: (4-5 pages not including the title and reference page)

In a 4- to 5-page paper, synthesize the peer-reviewed research you reviewed. Format your Assignment as an Annotated Bibliography. Be sure to address the following:

Identify the 4 peer-reviewed research articles you reviewed, citing each in APA format.
Include an introduction explaining the purpose of the paper.
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.
In your conclusion, synthesize the findings from the 4 peer-reviewed research articles.
Use APA format and include a title page.
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By Day 7 of Week 8

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A Sample Answer For the Assignment: NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

Title: NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

Mobile technologies have largely been used to improve the care given to patients in the modern world. Mobile technologies provide patients and care givers the opportunity to interact on issues related to health. Mobile health technologies have been shown to provide options for low-cost and effective care for patient populations with chronic diseases such as diabetes, heart failure and obesity. mHealth technology is one of the mobile health technologies that is used for the management of health problems such as smoking, obesity, heart disease and tuberculosis. mHealth uses technologies such as applications that provide the needed health education messages for positive lifestyle and behavioral change in populations at risk of health problems. The use of mHealth technology has been shown to result in outcomes such as patient satisfaction, increased access to care and reduction in cost of care incurred by patients and healthcare providers. Therefore, this research paper examines the outcomes of using mHealth technologies in health.

Wang, Y., Xue, H., Huang, Y., Huang, L., & Zhang, D. (2017). A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management. Advances in Nutrition, 8(3), 449–462. https://doi.org/10.3945/an.116.014100

NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

mHealth technologies are effective when used in the management of diabetes and obesity. The above study investigated the effectiveness of mhealth interventions for diabetes and obesity treatment as well as self-management. The study was a systematic review of studies conducted in the past on the topic. The authors performed a comprehensive analysis of the interventional studies on mhealth use in treatment of obesity and diabetes and developed recommendations for future practice and research. The articles used in the study were obtained from PubMed database where the inclusion criteria included those that focused on the topic of the study and published between 2000 and 2016. The application of the developed inclusion and exclusion criteria led to 24 articles, which mhealth interventions that included text messaging, monitoring devices and applications running on smartphones. The primary outcomes of the investigation included weight loss and reduction or maintenance of blood glucose level. The secondary outcomes of the investigation included behavioral changes, self-efficacy and acceptability of the use of mhealth programs. The analysis of data revealed that the use of mhealth technologies was associated with more than 50% improvement in weight, blood glucose, behavioral change, self-efficacy, and acceptability of use of the technology. The effects of the mhealth interventions were sustained over a long-term period, translating into the effective management of diabetes and obesity. The lesson learned from this article is that mhealth technologies are associated with significant benefits in use in chronic diseases such as obesity and diabetes. The technology also promotes self-management of these conditions as seen in the improvement in the self-efficacy and behavioral change of the participants. Therefore, mhealth should be incorporated into the management interventions for chronic illnesses in health.

Changizi, M., & Kaveh, M. H. (2017). Effectiveness of the mHealth technology in improvement of healthy behaviors in an elderly population—A systematic review. MHealth, 3. https://doi.org/10.21037/mhealth.2017.08.06

mHealth technologies can also be used to promote positive behavioral and lifestyle changes in the elderly population. The above study investigated the effectiveness of using mhealth technology to improve healthy behaviors in the elderly population. The authors conducted a systematic review using previously published studies. The articles that were used in the review were obtained from databases that included Web of Science, PubMed, Scopus, Embase and Science Direct. The authors used a pre-developed inclusion and exclusion criteria to select studies that were to be used in the investigation. The search performed on the above databases led to 12 studies that met the inclusion and exclusion criteria for the investigation. The analysis of data showed that the use of mhealth technology is associated with numerous benefits to the elderly populations. The benefits included improvement in care, self-efficacy, self-management, and behavior promotion and medication adherence.

The authors further found that the use of mhealth technology is effective for disease prevention, management of diseases such as diabetes and cardiovascular disease and promoting lifestyle changes in the elderly populations. The above study is associated with the strength that it used a bigger number of articles to determine the effect of mhealth on the elderly populations. The authors also investigated the use of the technology in the vulnerable populations. It can be learnt from the study that the use of mhealth technology is effective for individuals of all ages. The technology improves the treatment outcomes, adherence and adoption of healthy lifestyles in the elderly populations. Consequently, healthcare providers, including nurses should educate the elderly populations on the use of different mhealth technologies in the management of their health problems.

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Liu, H., Xiao, X., Lu, C.-M., Ling, D.-L., & Wei, R.-H. (2018). A systematic review of the effect of mobile health on cardiac rehabilitation among coronary heart disease patients. Frontiers of Nursing, 5(3), 217–226. https://doi.org/10.1515/fon-2018-0029

As noted in the above annotations, mhealth technology can be used to improve the treatment outcomes of patients with chronic conditions. The above study investigated the effect of using mhealth technologies on cardiac rehabilitation in patients with heart disease. The study was a systematic review of previous studies conducted to determine the effectiveness of mhealth technologies in patients with cardiac problems. The authors used articles that were obtained from performing a systematic search on databases that included NICE, Embase, CINAHL, Google Scholar, Medline, and Cochrane library. The researchers used mainly randomized controlled studies that were published between 2002 and 2017. The search led to eight articles that were used in the systematic review. The analysis of data showed that the use of mhealth has positive impact on behaviors that included medicine adherence, engagement in physical activity and quality of life.

However, the effect of mhealth on the level of anxiety and smoking cessation was inconsistent in studies. The authors therefore recommended studies that use large sample sizes to be conducted to provide conclusive evidence on the effect of mhealth technologies on patients on cardiac rehabilitation. It can be learned from this article that mhealth technologies have some benefits to patients with cardiac problems. The technology promotes healthy lifestyle and behavioral change that improves the outcomes of treatment in patients with cardiac health problems. Therefore, nurses and other healthcare providers should explore the possibilities of incorporating mhealth technologies into the treatment of cardiac-related health problems.

Xiong, S., Berkhouse, H., Schooler, M., Pu, W., Sun, A., Gong, E., & Yan, L. L. (2018). Effectiveness of mHealth interventions in improving medication adherence among people with hypertension: a systematic review. Current Hypertension Reports, 20(10), 86. https://doi.org/10.1007/s11906-018-0886-7

The above study investigated the effectiveness of using mhealth interventions to improve adherence to medication in people with hypertension. The authors conducted a systematic review of the studies that have examined the effect of mhealth technologies on medication adherence in people with hypertension. The authors performed search on professional databases that included Web of Science, PubMed and Embase. The search yielded 21 studies that were included following the application of the developed inclusion and exclusion criteria. The studies used in the investigation were published between 2000 and 2017. The results of the analysis showed that the use of mhealth technologies was associated with significant improvement in treatment adherence alongside blood pressure control in people with hypertension. The authors projected that the use of mhealth technologies had sustained benefits to patients with hypertension. Therefore, it can be learned from this study that mhealth can improve the treatment outcomes due to adherence in patients with hypertension. The improvement also enhances the control of blood pressure in these patients. Therefore, the use of mhealth should be incorporated into the self-management interventions used in the management of hypertension.

Conclusion

The above annotation has shown that mHealth technology is effective when used in healthcare. mHealth technologies provide the opportunities to reduce the cost of care incurred by the patients and health organizations. The analysis has also shown that mhealth technologies promote behavioral changes. The behavioral changes can be seen from the improved adherence to treatment and engagement in physical activity among patients with obesity, hypertension and diabetes. The analysis also showed that mhealth promotes the self-management of chronic health problems that include diabetes, hypertension and obesity. mHealth has also be shown to improve the self-efficacy of patients with different health problems. The improvement in self-efficacy implies that the use of this technology in health has a high possibility of sustainability. In addition, the acceptability level of mhealth technology is significantly high. The high rate of acceptability implies that its utilization in health will result in enhanced outcomes of treatment for the patients. Healthcare providers including nurses should therefore consider incorporating mhealth technology into their plans of care. The technology will optimize the treatment outcomes for value-based care in health.

References

Wang, Y., Xue, H., Huang, Y., Huang, L., & Zhang, D. (2017). A systematic review of application and effectiveness of mHealth interventions for obesity and diabetes treatment and self-management. Advances in Nutrition, 8(3), 449–462. https://doi.org/10.3945/an.116.014100

A Sample Answer 2 For the Assignment: NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

Title: NURS 6051 Literature Review The Use of Clinical Systems to Improve Outcomes and Efficiencies

Introduction

This paper presents an annotated bibliography summarizing recent research on the application of clinical systems and their impact on healthcare outcomes and efficiencies. The purpose is to explore how various clinical systems have been used to improve patient outcomes and streamline healthcare delivery.

Annotated Bibliography

Research Article 1

Lu Wenjie, Zhang Jiaming, & Jiang Weiyu. (2023). The difference and clinical application of modified thoracolumbar fracture classification scoring system in guiding clinical treatment. Journal of Orthopaedic Surgery and Research, 18(1), 1–8. https://doi.org/10.1186/s13018-023-03958-4

In this article, Wenjie et al. discusses the clinical application of a modified thoracolumbar injury classification and severity score system (modified TLICS system) in guiding clinical treatment for patients with thoracolumbar fractures. The system was developed as an improvement to the existing TLICS system to address its limitations and enhance its effectiveness.

The study found that the use of the modified TLICS system significantly improved patient outcomes. Over an average follow-up duration of 19.2 months, patients demonstrated significant improvement in various outcome measures, including visual analog scale (VAS) score, modified Japanese Orthopaedic Association (JOA) score, anterior vertebral height ratio, sagittal index, and Cobb angle. Additionally, neurological status also showed varying degrees of improvement. The systematic application of the modified TLICS system allowed clinicians to identify the severity of thoracolumbar fractures accurately and tailor treatment plans, leading to improved patient recovery and functional outcomes.

By implementing the modified TLICS system, the research showed that clinicians achieved more streamlined and efficient decision-making in clinical treatment. The modified TLICS system facilitated a comprehensive evaluation of various injury parameters, aiding in the accurate classification of thoracolumbar fractures. The system’s modifications addressed the limitations of the original TLICS system, enabling healthcare providers to make more informed decisions regarding the need for surgery and the appropriate treatment approach. As a result, the operation rate for the modified TLICS system was slightly lower than that of the traditional TLICS system. This suggests that the modified system contributed to the more efficient allocation of surgical resources while still achieving favorable patient outcomes.

The study provides valuable insights into the application of clinical systems in orthopedic settings. The development and implementation of the modified TLICS system offer a valuable lesson on how continuous improvement and refinement of existing clinical systems can enhance their practicality and effectiveness. By addressing the limitations of the original TLICS system, the modified version demonstrated its potential as a reliable tool for thoracolumbar fracture classification and assessment. The study emphasizes the importance of iterative research and continuous feedback from clinicians to optimize clinical systems for better patient care and healthcare efficiency.

Research Article 2

Parva Paydar, Shole Ebrahimpour, Hanieh Zehtab Hashemi, Mehdi Mohamadi, & Soha Namazi. (2023). Design, Development, and Evaluation of an Application based on Clinical Decision Support Systems (CDSS) for Over-The-Counter (OTC) Therapy: An Educational Interventions in Community Pharmacists. Journal of Advances in Medical Education and Professionalism, 11(2), 95–104. https://doi.org/10.30476/jamp.2022.95843.1661

Paydar et al, shows the implementation of a Clinical Decision Support System (CDSS) in the form of an over-the-counter (OTC) therapy application for community pharmacists resulted in several improvements in outcomes. Firstly, the application significantly enhanced the knowledge and pharmaceutical skills of pharmacists in managing OTC therapy. By providing decision support and relevant information, pharmacists were better equipped to take comprehensive patient histories, make appropriate pharmacological and non-pharmacological recommendations, and identify when to refer patients to physicians. This ultimately led to more effective patient counseling and improved patient outcomes. Moreover, the application also contributed to a reduction in unnecessary referrals to physicians. Before using the CDSS-based application, a considerable percentage of patients were wrongly referred to physicians.

While the application increased the time taken to manage scenarios, it had a positive impact on overall efficiencies in patient care. Pharmacists spent more time collecting complete patient histories, resulting in more comprehensive evaluations and appropriate recommendations. Although the initial increase in time may seem inefficient, the overall outcome of improved decision-making and patient care justified this trade-off. Additionally, the mobile-based nature of the application offered ease of access and use for pharmacists in busy pharmacy settings. It allowed them to promptly access OTC therapy information and decision support, thereby enhancing their ability to counsel patients effectively and manage OTC-related situations efficiently.

The study yielded valuable lessons for the future application of CDSS-based tools in pharmacy practice. It highlighted the significant impact of such tools on enhancing patient care and pharmacist performance. The application acted as a valuable clinical support system, guiding pharmacists through patient evaluations and treatment decisions. This underscored the importance of integrating CDSS-based applications to improve patient outcomes and streamline decision-making processes in pharmacy practice. Additionally, user feedback from the evaluation using the user version of the mobile application rating scale (uMARS) questionnaire was essential in understanding user experience and application quality. The feedback provided valuable insights into the importance of user-centric design and continuous improvement to enhance user satisfaction and application performance.

Research Article 3

Shujuan Cao, Rongpei Zhang, Aixin Jiang, Mayila Kuerban, Aizezi Wumaier, Jianhua Wu, Kaihua Xie, Mireayi Aizezi, Abudurexiti Tuersun, Xuanwei Liang, & Rongxin Chen. (2023). Application effect of an artificial intelligence-based fundus screening system: evaluation in a clinical setting and population screening. BioMedical Engineering OnLine, 22(1), 1–13. https://doi.org/10.1186/s12938-023-01097-9

Cao et al. explored the application of artificial intelligence (AI)-based fundus screening systems in the clinical environment has shown promising results in improving outcomes and efficiencies in the early detection and management of ocular fundus abnormalities. This study investigated the performance of an AI-based fundus screening system, focusing on diabetic retinopathy (DR), retinal vein occlusion (RVO), and pathological myopia (PM), in a real-world clinical setting. The study aimed to evaluate the system’s diagnostic effectiveness, and its application in population screening, and identify areas for further improvement and integration of systemic indicators.

Enhanced Diagnostic Accuracy: The AI-based fundus screening system demonstrated superior diagnostic effectiveness for diabetic retinopathy (DR), retinal vein occlusion (RVO), and pathological myopia (PM), with sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) all exceeding 80%. This improved accuracy leads to more precise and reliable diagnoses, enabling early detection and timely treatment, ultimately improving patient outcomes and preventing irreversible vision loss.

Resource Saving and Efficiency: By automating the screening process, the AI-based system analyzes many fundus images quickly and accurately, reducing the burden on healthcare professionals. This increased efficiency translates to faster diagnoses, allowing for more patients to be screened and diagnosed promptly. The system’s efficiency enhances the overall workflow in clinical settings, leading to more effective patient management and treatment.

Scalability and Population Screening: The AI-based fundus screening system’s diagnostic capabilities in the clinical environment were comparable to those in population screening. This scalability allows the system to be applied in primary healthcare facilities for large-scale screenings.

Identification of Areas for Improvement: The study identified areas for improvement in the AI system’s performance, particularly in its sensitivity to age-related macular degeneration (ARMD) and referable glaucoma. Lessons learned from the study provide valuable insights for future developments and updates to the AI algorithm. Focusing on enhancing accuracy and precision for these conditions will further optimize the system’s diagnostic capabilities.

Integration of Systemic Indicators: The study highlighted the potential to integrate the AI algorithm with systemic indicators, such as HbA1c levels for diabetic retinopathy diagnosis. This integration could significantly improve the system’s diagnostic capabilities, providing more comprehensive assessments of patients’ overall health.

Research Article 4

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, 2023, 8550905. https://doi.org/10.1155/2023/8550905

Gholamzadeh et al. discussed the application of clinical decision support systems (CDSSs) in chronic disease management has shown significant improvements in patient outcomes. By providing evidence-based recommendations and up-to-date information, CDSSs empower healthcare providers to make more accurate diagnoses and develop tailored treatment plans. This leads to better disease management, reduced complications, and improved patient health. CDSSs also help in identifying potential medical errors and providing timely alerts, contributing to enhanced patient safety and healthcare quality. With personalized patient care and targeted interventions, CDSSs play a vital role in improving clinical outcomes and patient well-being.

CDSSs have brought about substantial efficiencies in healthcare delivery. By automating the processing of patient data and presenting relevant information, CDSSs save clinicians valuable time and effort that would otherwise be spent searching for relevant medical literature and guidelines. This streamlining of the decision-making process allows healthcare providers to focus more on direct patient care and less on administrative tasks. As a result, CDSSs contribute to a more efficient and streamlined healthcare workflow, leading to enhanced productivity and resource utilization.

The implementation of CDSSs in clinical settings has provided valuable lessons for healthcare providers and developers. Challenges related to system integration, user acceptance, data quality, and clinician resistance to change have been encountered. To address these challenges, effective training, engagement with end-users, and continuous monitoring and evaluation of system performance have been essential. Additionally, adapting CDSSs to diverse clinical settings and patient populations has been critical for maximizing their impact.

In conclusion, the application of clinical decision support systems in chronic disease management has led to significant improvements in patient outcomes, enhanced efficiencies in healthcare delivery, and valuable lessons learned. By addressing challenges, embracing continuous learning, and upholding ethical considerations, CDSSs can continue to play a pivotal role in advancing patient care and healthcare quality.

Conclusion

The four peer-reviewed research articles presented in this annotated bibliography collectively provide valuable insights into the application of clinical systems and their impact on healthcare outcomes and efficiencies. These studies cover various domains within healthcare, including orthopedics, pharmacy practice, ophthalmology, and chronic disease management. A cohesive conclusion can be drawn from these findings to highlight the overall benefits and lessons learned from using clinical systems in diverse healthcare settings.

Firstly, the studies consistently demonstrate that the implementation of clinical systems leads to significant improvements in patient outcomes. In the orthopedic setting, the modified thoracolumbar injury classification and severity score system (modified TLICS system) improved patient recovery and functional outcomes for thoracolumbar fractures. In pharmacy practice, the Clinical Decision Support System (CDSS) for over-the-counter (OTC) therapy resulted in more effective patient counseling and reduced unnecessary referrals to physicians. In ophthalmology, the AI-based fundus screening system showed enhanced diagnostic accuracy for various ocular abnormalities, leading to timely treatment and preventing irreversible vision loss. Moreover, the application of knowledge-based CDSSs in chronic disease management improved patient health, reduced complications, and enhanced adherence to evidence-based medicine.

Secondly, the research highlights the efficiencies gained by using clinical systems. In orthopedics, the modified TLICS system facilitated more streamlined and efficient decision-making, optimizing surgical resource allocation while achieving favorable patient outcomes. The CDSS-based application in pharmacy practice, despite increasing the time taken to manage scenarios, improved overall efficiencies in patient care by enabling more comprehensive evaluations and appropriate recommendations. The AI-based fundus screening system in ophthalmology automated the screening process, saving time for healthcare professionals and allowing for large-scale population screenings. In chronic disease management, CDSSs saved clinicians time and effort, leading to a more efficient healthcare workflow and enhanced productivity.

The lessons learned from these studies emphasize the importance of continuous improvement and refinement of clinical systems. The development of the modified TLICS system, the user-centric design of the CDSS-based application, and the identification of areas for improvement in the AI-based fundus screening system all highlight the value of iterative research and continuous feedback from healthcare professionals. Additionally, the studies underscore the significance of integrating clinical systems with systemic indicators and adapting them to diverse clinical settings and patient populations to maximize their impact.

In conclusion, the findings from these research articles collectively demonstrate that clinical systems play a crucial role in enhancing healthcare outcomes and efficiencies. By improving patient care, streamlining decision-making processes, and saving valuable time and resources, these systems contribute to overall healthcare quality and effectiveness. Moreover, the lessons learned from their implementation provide valuable guidance for future developments and improvements in clinical systems, ensuring continuous enhancement of patient care and healthcare delivery.