Sample Answer for NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES Included After Question<\/strong><\/em><\/span><\/h2>\nNew technology\u2014and the application of existing technology\u2014only appears in healthcare settings<\/a> after careful and significant research. The stakes are high, and new clinical systems need to offer evidence of positive impact on outcomes or efficiencies.<\/p>\nNurse informaticists and healthcare leaders formulate clinical system strategies. As these strategies are often based on technology trends<\/a>, informaticists and others have then benefited from consulting existing research to inform their thinking.<\/p>\nIn this Assignment, you will review existing research focused on the application of clinical systems. After reviewing, you will summarize your findings.<\/p>\n
RESOURCES<\/h2>\n
Be sure to review the Learning Resources before completing this activity.
\nClick the weekly resources link to access the resources.<\/p>\n
WEEKLY RESOURCES<\/strong><\/a><\/h2>\nTo Prepare:<\/strong><\/h3>\n\n- Review the Resources and reflect on the impact of clinical systems on outcomes and efficiencies within the context of nursing practice and healthcare delivery.<\/li>\n
- 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 \u201cthe use of personal health records or portals to support patients newly diagnosed with diabetes.\u201d<\/li>\n
- Identify and select 4 peer-reviewed research articles from your research.<\/li>\n
- For information about annotated bibliographies, visit\u00a0https:\/\/academicguides.waldenu.edu\/writingcenter\/assignments\/annotatedbibliographiesLinks to an external site.<\/a><\/li>\n<\/ul>\n
The Assignment: (4-5 pages not including the title and reference page)<\/strong><\/h2>\nIn a 4- to 5-page paper, synthesize the peer-reviewed research you reviewed.\u00a0Format your Assignment as an Annotated Bibliography. Be sure to address the following:<\/p>\n
\n- Identify the 4 peer-reviewed research articles you reviewed, citing each in APA format.<\/li>\n
- Include an introduction explaining the purpose of the paper.<\/li>\n
- 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.<\/li>\n
- In your conclusion, synthesize the findings from the 4 peer-reviewed research articles.<\/li>\n
- Use APA format and include a title page.<\/li>\n
- Use the Safe Assign Drafts to check your match percentage before submitting your work.<\/li>\n<\/ul>\n
BY DAY 7 OF WEEK 8<\/h2>\n
Submit your completed Assignment.<\/p>\n
SUBMISSION INFORMATION<\/h2>\n
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- Then, click on\u00a0Start Assignment<\/strong>near the top of the page.<\/li>\n
- Next, click on\u00a0Upload File<\/strong>and select\u00a0Submit Assignment<\/strong>\u00a0for review.<\/li>\n<\/ol>\n
A Sample Answer For the Assignment: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\nTitle: <\/strong> NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\nOver the past two decades, advancements in the use of technology have transformed the process of care provision. The days of manual<\/span><\/p>\nrecord filling and meticulous charting are dwindling. Clinical systems through electronic health records<\/a> (EHR) and telehealth have increased the accessibility of patients to their personal health information like never before (Islam, Poly, & Li, 2018). From a global perspective, evidence report that adoption of clinical information system by healthcare organizations has led to enhanced patient outcome, efficiency, safety, and financial performance. Clinical information system has also impacted the work of healthcare providers positively, such as nursing practice, by making it easier to retrieve patient information and even take patient history with reduced errors, hence promoting the accuracy and quality of care provided. The paper demonstrates a literature review on the impact of applying clinical systems to improve the quality and<\/span><\/p>\n![\"NURS](\"http:\/\/nursingassignmentcrackers.com\/wp-content\/uploads\/2023\/03\/NURS-6051-LITERATURE-REVIEW-THE-USE-OF-CLINICAL-SYSTEMS-TO-IMPROVE-OUTCOMES-AND-EFFICIENCIES-1-300x140.png\")
NURS 6051 LITERATURE REVIEW THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/figcaption><\/figure>\nefficiency of care provision.\u00a0<\/span>\u00a0<\/span><\/p>\nLiterature Review<\/span><\/b>\u00a0<\/span><\/h2>\nIslam, M. M., Poly, T. N., & Li, Y.-C. J. (2018).\u202fRecent Advancement of Clinical Information Systems: Opportunities and Challenges. <\/span><\/b>Yearbook of medical informatics<\/span><\/i><\/b>, 27(1), 083-090. DOI:\u202f<\/span><\/b>10.1055\/s-0038-1667075<\/span><\/b><\/a>\u00a0<\/span><\/p>\nIn this article, Islam, Poly, and Li (2018), discuss the opportunities generated by clinical information systems for the improvement of workflow and patient care. However, they still claim that the healthcare system is still far from perfection. For instance, healthcare providers still face challenges associated with data exchange, integration, and management as a result of a lack of functionality among new systems. Islam et al. (2018), carried out a literature review to determine the current stage in which clinical information systems have impacted healthcare practice, as displayed by the current state of knowledge. They selected 23 papers from EMBASE, and PubMed focusing on three major areas such as ancillary information systems, specialty information systems, and inpatients and ambulatory clinical information systems. Based on their results, Islam et al. (2018), concluded that clinical information systems provide significant opportunities in reducing clinical errors, such as diagnostic and medical errors, and offer support to clinicians by availing updated patient information. They also noted improved workflow, and efficiency of care as a result of electronic health records.\u00a0<\/span>\u00a0<\/span><\/p>\nFu, H., McMahon, S. K., Gross, C. R., Adam, T. J., & Wyman, J. F. (2017). Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: a systematic review.\u202f<\/span><\/b>Diabetes research and clinical practice<\/span><\/i><\/b>,\u202f<\/span><\/b>131<\/span><\/i><\/b>, 70-81. <\/span><\/b>https:\/\/doi.org\/10.1016\/j.diabres.2017.06.016<\/span><\/b><\/a>\u00a0<\/span><\/p>\nFu et al. (2017) carried out a study to evaluate the clinical effectiveness and usability of diabetes mobile applications among adults diagnosed with diabetes mellitus. The study utilized a systemic review of articles retrieved from IEEE XPLORE, COMPENDEX, EMBASE, and MEDLINE. Fu et al. (2017) narrowed it down to ten clinical effectiveness and seven usability studies for their research. The results derived from a measurement of the satisfaction rate from patients and experts revealed a usability percentage ranging from 38% to 80%. The clinical effectiveness was measured by the HgbAIc reduction, which displayed a range from 0.15% to 1.9%. Fu et al. concluded that despite the challenges that might be associated with diabetes mobile application, studies reveal an improved glycemic control among adults with diabetes type 2. The therapeutic impact of the diabetes app can however be improved in terms of usability and effectiveness through the incorporation of principles aimed at changing health behavior.\u00a0<\/span>\u00a0<\/span><\/p>\nArndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W. J., Sinsky, C. A., & Gilchrist, V. J. (2017). Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations.\u202f<\/span><\/b>The Annals of Family Medicine<\/span><\/i><\/b>,\u202f<\/span><\/b>15<\/span><\/i><\/b>(5), 419-426.<\/span><\/b> doi: https:\/\/doi.org\/10.1370\/afm.2121<\/a><\/span><\/b>\u00a0<\/span><\/p>\nArndt et al. (2017) conducted a study to assess the time spent by primary care physicians on electronic health records (EHR) and its impact on workflow and care delivery. They utilized a retrospective cohort study design with 42 family medicine physicians\u202fas the study participants. The study captured all Epic Systems Corporation EHR interactions from \u201cevent logging\u201d records for both non-face-to-face activities and direct patient care. According to their results, clinicians spend about 5.9 hours out of the 11.4 hour workday on EHR. Some of the tasks covered during this time, both clerical and administrative, include order entry, documentation, billing, and coding account for about half of the time they spend on EHR systems. About 85 minutes are spent on inbox management. They concluded that the EHR event logs can be utilized in spotting areas of EHR-related works which can be delegated, hence reducing workload, decrease burnout, and improve professional satisfaction which in turn boosts the quality and efficiency of care provision.\u00a0<\/span>\u00a0<\/span><\/p>\nKruse, C. S., & Beane, A. (2018). Health information technology continues to show a positive effect on medical outcomes: a systematic review.\u202f<\/span><\/b>Journal of medical Internet research<\/span><\/i><\/b>,\u202f<\/span><\/b>20<\/span><\/i><\/b>(2), e41.<\/span><\/b> doi:\u202f<\/span><\/b>10.2196\/jmir.8793<\/span><\/b><\/a>\u00a0<\/span><\/p>\n Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/a><\/span><\/span><\/p>\nIn this article, Kruse and Beane (2018) reviewed the positive impact of health information technology (HIT) on the medical outcome. Recent studies published between 2013 and 2018 were utilized in this research, retrieved from Medical Literature Analysis and Retrieval System Online (MEDLINE) and Cumulative Index of Nursing and Allied Health Literature (CINAHL)\u202fdatabases. The review was conducted in accordance with the Assessment for Multiple Systematic Reviews (AMSTAR). Out of the 3636 papers\u202fthat were arrived at, only 37 met the inclusion criteria for their literature review. The results displayed at least one improvement in medical outcomes concerning the adoption of HIT in 81% of the reviewed literature. Three categories of the outcome and twelve categories of HIT were consistent in the studies about 65 and 38 times respectively. As a result, Kruse and Beane concluded that there is substantial evidence supporting the positive impact of HIT on the effectiveness of medical outcomes.<\/span>\u00a0<\/span><\/p>\nConclusion<\/span><\/b><\/h2>\nThe current healthcare system has greatly transformed towards the adoption of advanced technology in promoting the quality, safety, effectiveness, and outcome of care provision. The current clinical system promotes the utilization of EHR and HIT by healthcare personnel in improving the efficiency of workflow and reduce incidences of burnouts. All the four studies summarized above reveal the positive impacts associated with technology in care provision for effectiveness and improved outcomes. For instance, Islam et al. (2018) and Arndt et al., (2017) revealed the impact of EHR in reducing medical errors and improving workflow and efficiency in the care delivery system. Fu et al. (2017) on the other hand provide evidence supporting the use of diabetes app in improving outcomes among diabetes mellitus patients. Lastly, Kruse and Beane, (2018) provides evidence associated with different aspects of improved medical outcome and effectiveness as a result of HIT. Further advancement in the clinical systems is however expected for further improved outcome and efficiency.<\/span>\u00a0<\/span><\/p>\nReferences\u00a0<\/span><\/b><\/h2>\nArndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W. J., Sinsky, C. A., & Gilchrist, V. J. (2017). Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations.\u202f<\/span>The Annals of Family Medicine<\/span><\/i>,\u202f<\/span>15<\/span><\/i>(5), 419-426.<\/span> DOI: <\/span>https:\/\/doi.org\/10.1370\/afm.2121<\/span><\/a>\u00a0<\/span>\u00a0<\/span><\/p>\nFu, H., McMahon, S. K., Gross, C. R., Adam, T. J., & Wyman, J. F. (2017). Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: a systematic review.\u202f<\/span>Diabetes research and clinical practice<\/span><\/i>,\u202f<\/span>131<\/span><\/i>, 70-81. <\/span>https:\/\/doi.org\/10.1016\/j.diabres.2017.06.016<\/span><\/a>\u00a0<\/span>\u00a0<\/span><\/p>\nIslam, M. M., Poly, T. N., & Li, Y.-C. J. (2018).\u202fRecent Advancement of Clinical Information Systems: Opportunities and Challenges. <\/span>Yearbook of medical informatics<\/span><\/i>, volume:27 number:01 year:2018 pages:083-090. DOI:\u202f<\/span>10.1055\/s-0038-1667075<\/span><\/a> Bottom of Form<\/span><\/b>\u00a0<\/span><\/p>\nKruse, C. S., & Beane, A. (2018). Health information technology continues to show a positive effect on medical outcomes: a systematic review.\u202f<\/span>Journal of medical Internet research<\/span><\/i>,\u202f<\/span>20<\/span><\/i>(2), e41.<\/span> DOI:\u202f<\/span>10.2196\/jmir.8793<\/span><\/a>\u00a0<\/span><\/p>\nI completely concur with your response. Telehealth represents one of the most promising technological innovations that has a beneficial impact on<\/p>\n
nursing practice. To meet the patients’ needs and with the current nursing shortage, many homecare agencies have to look at innovative ways to care for the<\/p>\n
increasing numbers of patients. Telehealth technology offers productivity improvement for nurses by reducing travel time to remote areas, through increasing<\/p>\n
the average daily caseload. Telenursing offers an access to care and the ability to export nursing care using technology. It is a powerful tool for overall<\/p>\n
improvement in healthcare. Several measures should be taken for telenursing implementation into practice for all nurses (Glinkowski et al., 2013). In terms<\/p>\n
of providing better patient outcomes, nurses are often a patient\u2019s first point of contact when seeking healthcare and a patient’s primary source of health<\/p>\n
education and long-term health monitoring. In many institutions, nurses have also taken the lead on integrating telehealth services into patient care (Southern<\/p>\n
New Hampshire University, 2020). In all, through telenursing, nurses can provide monitoring, education, follow-up, remote data collection and interventions,<\/p>\n
pain management, family support, and multidisciplinary care in an innovative way. It is a good tool to deliver care in remote regions and to facilitate practice<\/p>\n
(Glinkowski et al., 2013).<\/p>\n
There are several healthcare technology trends that have been observed in the healthcare industry in recent years. These include the use of electronic health records (EHRs), telemedicine, and wearable technology.<\/p>\n
One trend that has been widely adopted in healthcare organizations is the use of EHRs. These systems allow healthcare providers to access patient medical history, diagnoses, treatments, and test results in a single, digital location. While EHRs can improve the efficiency of care and coordination between healthcare providers, there are potential challenges and risks associated with their use. One challenge is the high cost of implementing EHR systems, which can be a barrier for smaller organizations. Another risk is the potential for data breaches, which can compromise patient privacy.<\/p>\n
One potential benefit of EHRs is the ability to improve patient care outcomes using data analytics. By analyzing patient data, healthcare providers can identify trends and patterns that can inform treatment decisions and help predict patient outcomes. However, there is also a risk that the use of data analytics could lead to biased decision-making if the data is not properly analyzed or if the algorithms used to analyze the data are biased.<\/p>\n
Telemedicine is another healthcare technology trend that has gained traction in recent years after the start of the pandemic. One potential benefit of telemedicine is the ability to improve access to care for patients in underserved or rural areas. However, there are also risks associated with telemedicine, such as the potential for data breaches or the possibility that patients may receive inadequate care if the technology is not used correctly.<\/p>\n
Wearable technology, such as fitness trackers and smart watches, is another trend that has gained popularity in healthcare. These devices allow patients to track their health and wellness data, such as steps taken and sleep patterns, and share that information with their healthcare providers<\/p>\n
\u201cMarketers should communicate the effectiveness of healthcare wearable technology in improving consumers\u2019 health, whilst addressing health concerns. This can contribute to improved user understanding of health, and potential usefulness of healthcare wearable technology.\u201d (Chau, et al, 2019). One potential benefit of wearable technology is the ability to improve patient engagement and self-management of chronic conditions. However, there are also risks associated with wearable technology, such as the possibility of data breaches or the potential for the data to be used for non-medical purposes.<\/p>\n
One healthcare technology trend that I believe has the most promise for impacting nursing practice is the use of artificial intelligence (AI) and machine learning. AI and machine learning have the potential to improve patient care outcomes by enabling healthcare providers to analyze large amounts of data and make more accurate diagnoses and treatment recommendations. For example, AI algorithms could be used to analyze medical images and detect abnormalities that may not be visible to the human eye. This could lead to earlier diagnoses and more targeted treatment plans, improving patient outcomes \u201cThese technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer and pharmaceutical organizations\u201d (Davenport, Kalakota, 2019). AI and machine learning could also be used to improve efficiencies in healthcare organizations by automating tasks such as data entry and scheduling.<\/p>\n
Overall, while there are potential risks and challenges associated with healthcare technology trends, there are also many potential benefits that can improve patient care outcomes, efficiencies, and data management. The healthcare technology trends that are most promising for impacting nursing practice are those that leverage data analytics, AI, and machine learning to improve patient care and increase efficiencies in healthcare organizations.<\/p>\n
<\/p>\n
References<\/h2>\n
Chau, K. Y., Lam, M. H. S., Cheung, M. L., Tso, E. K. H., Flint, S. W., Broom, D. R., Tse, G., & Lee, K. Y. (2019). Smart technology for healthcare: Exploring the<\/p>\n
antecedents of adoption intention of healthcare wearable technology.\u00a0Health psychology research<\/em>,\u00a07<\/em>(1), 8099.<\/p>\nhttps:\/\/doi.org\/10.4081\/hpr.2019.8099Links to an external site.<\/a><\/p>\nDavenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare.\u00a0Future healthcare journal<\/em>,\u00a06<\/em>(2), 94\u201398.<\/p>\nhttps:\/\/doi.org\/10.7861\/futurehosp.6-\u00a0Links to an external site.<\/a>2-94<\/p>\nA Sample Answer 2 For the Assignment: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\nTitle: <\/strong> NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\nIntroduction<\/strong><\/h2>\nThis 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.<\/p>\n
Annotated Bibliography<\/strong><\/h2>\nResearch Article 1<\/strong><\/h3>\nLu Wenjie, Zhang Jiaming, & Jiang Weiyu. (2023). The difference and clinical application of modified thoracolumbar fracture classification scoring system in guiding clinical treatment.\u00a0Journal of Orthopaedic Surgery and Research,\u00a018(1), 1\u20138. https:\/\/doi.org\/10.1186\/s13018-023-03958-4<\/a><\/p>\nIn 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Research Article 2<\/strong><\/h2>\nParva 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.\u00a0Journal of Advances in Medical Education and Professionalism,\u00a011(2), 95\u2013104. https:\/\/doi.org\/10.30476\/jamp.2022.95843.1661<\/a><\/p>\nPaydar 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Research Article 3<\/strong><\/h2>\nShujuan 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.\u00a0BioMedical Engineering OnLine,\u00a022(1), 1\u201313. https:\/\/doi.org\/10.1186\/s12938-023-01097-9<\/a><\/p>\nCao 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Research Article 4<\/strong><\/h2>\nGholamzadeh, 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.\u00a0Journal of Healthcare Engineering,\u00a02023, 8550905. https:\/\/doi.org\/10.1155\/2023\/8550905<\/a><\/p>\nGholamzadeh 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Conclusion<\/strong><\/h2>\nThe 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
\u00a0<\/strong><\/p>\n\u00a0<\/strong><\/p>\nReferences<\/strong><\/h2>\nGholamzadeh, 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.\u00a0Journal of Healthcare Engineering,\u00a02023, 8550905. https:\/\/doi.org\/10.1155\/2023\/8550905<\/a><\/p>\nLu Wenjie, Zhang Jiaming, & Jiang Weiyu. (2023). The difference and clinical application of modified thoracolumbar fracture classification scoring system in guiding clinical treatment.\u00a0Journal of Orthopaedic Surgery and Research,\u00a018(1), 1\u20138. https:\/\/doi.org\/10.1186\/s13018-023-03958-4<\/a><\/p>\nParva 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.\u00a0Journal of Advances in Medical Education and Professionalism,\u00a011(2), 95\u2013104. https:\/\/doi.org\/10.30476\/jamp.2022.95843.1661<\/a><\/p>\nShujuan 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.\u00a0BioMedical Engineering OnLine,\u00a022(1), 1\u201313. https:\/\/doi.org\/10.1186\/s12938-023-01097-9<\/a><\/p>\nAssignment_Rubric<\/strong><\/h2>\n\n\n\nNURS_5051_Module04_Week08_Assignment_Rubric<\/td>\n<\/tr>\n \nCriteria<\/strong><\/td>\nRatings<\/strong><\/td>\nPts<\/strong><\/td>\n<\/tr>\n<\/thead>\n\n\nThis criterion is linked to a Learning OutcomeIn 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:\u00b7 Properly identify 4 peer-reviewed research articles you reviewed.<\/td>\n \n
Nurse informaticists and healthcare leaders formulate clinical system strategies. As these strategies are often based on technology trends<\/a>, informaticists and others have then benefited from consulting existing research to inform their thinking.<\/p>\n In this Assignment, you will review existing research focused on the application of clinical systems. After reviewing, you will summarize your findings.<\/p>\n Be sure to review the Learning Resources before completing this activity. In a 4- to 5-page paper, synthesize the peer-reviewed research you reviewed.\u00a0Format your Assignment as an Annotated Bibliography. Be sure to address the following:<\/p>\n Submit your completed Assignment.<\/p>\n Before submitting your final assignment, you can check your draft for authenticity. To check your draft, access the\u00a0Turnitin Drafts<\/strong>\u00a0from the\u00a0Start Here<\/strong>\u00a0area.<\/p>\n Over the past two decades, advancements in the use of technology have transformed the process of care provision. The days of manual<\/span><\/p>\n record filling and meticulous charting are dwindling. Clinical systems through electronic health records<\/a> (EHR) and telehealth have increased the accessibility of patients to their personal health information like never before (Islam, Poly, & Li, 2018). From a global perspective, evidence report that adoption of clinical information system by healthcare organizations has led to enhanced patient outcome, efficiency, safety, and financial performance. Clinical information system has also impacted the work of healthcare providers positively, such as nursing practice, by making it easier to retrieve patient information and even take patient history with reduced errors, hence promoting the accuracy and quality of care provided. The paper demonstrates a literature review on the impact of applying clinical systems to improve the quality and<\/span><\/p>\n efficiency of care provision.\u00a0<\/span>\u00a0<\/span><\/p>\n Islam, M. M., Poly, T. N., & Li, Y.-C. J. (2018).\u202fRecent Advancement of Clinical Information Systems: Opportunities and Challenges. <\/span><\/b>Yearbook of medical informatics<\/span><\/i><\/b>, 27(1), 083-090. DOI:\u202f<\/span><\/b>10.1055\/s-0038-1667075<\/span><\/b><\/a>\u00a0<\/span><\/p>\n In this article, Islam, Poly, and Li (2018), discuss the opportunities generated by clinical information systems for the improvement of workflow and patient care. However, they still claim that the healthcare system is still far from perfection. For instance, healthcare providers still face challenges associated with data exchange, integration, and management as a result of a lack of functionality among new systems. Islam et al. (2018), carried out a literature review to determine the current stage in which clinical information systems have impacted healthcare practice, as displayed by the current state of knowledge. They selected 23 papers from EMBASE, and PubMed focusing on three major areas such as ancillary information systems, specialty information systems, and inpatients and ambulatory clinical information systems. Based on their results, Islam et al. (2018), concluded that clinical information systems provide significant opportunities in reducing clinical errors, such as diagnostic and medical errors, and offer support to clinicians by availing updated patient information. They also noted improved workflow, and efficiency of care as a result of electronic health records.\u00a0<\/span>\u00a0<\/span><\/p>\n Fu, H., McMahon, S. K., Gross, C. R., Adam, T. J., & Wyman, J. F. (2017). Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: a systematic review.\u202f<\/span><\/b>Diabetes research and clinical practice<\/span><\/i><\/b>,\u202f<\/span><\/b>131<\/span><\/i><\/b>, 70-81. <\/span><\/b>https:\/\/doi.org\/10.1016\/j.diabres.2017.06.016<\/span><\/b><\/a>\u00a0<\/span><\/p>\n Fu et al. (2017) carried out a study to evaluate the clinical effectiveness and usability of diabetes mobile applications among adults diagnosed with diabetes mellitus. The study utilized a systemic review of articles retrieved from IEEE XPLORE, COMPENDEX, EMBASE, and MEDLINE. Fu et al. (2017) narrowed it down to ten clinical effectiveness and seven usability studies for their research. The results derived from a measurement of the satisfaction rate from patients and experts revealed a usability percentage ranging from 38% to 80%. The clinical effectiveness was measured by the HgbAIc reduction, which displayed a range from 0.15% to 1.9%. Fu et al. concluded that despite the challenges that might be associated with diabetes mobile application, studies reveal an improved glycemic control among adults with diabetes type 2. The therapeutic impact of the diabetes app can however be improved in terms of usability and effectiveness through the incorporation of principles aimed at changing health behavior.\u00a0<\/span>\u00a0<\/span><\/p>\n Arndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W. J., Sinsky, C. A., & Gilchrist, V. J. (2017). Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations.\u202f<\/span><\/b>The Annals of Family Medicine<\/span><\/i><\/b>,\u202f<\/span><\/b>15<\/span><\/i><\/b>(5), 419-426.<\/span><\/b> doi: https:\/\/doi.org\/10.1370\/afm.2121<\/a><\/span><\/b>\u00a0<\/span><\/p>\n Arndt et al. (2017) conducted a study to assess the time spent by primary care physicians on electronic health records (EHR) and its impact on workflow and care delivery. They utilized a retrospective cohort study design with 42 family medicine physicians\u202fas the study participants. The study captured all Epic Systems Corporation EHR interactions from \u201cevent logging\u201d records for both non-face-to-face activities and direct patient care. According to their results, clinicians spend about 5.9 hours out of the 11.4 hour workday on EHR. Some of the tasks covered during this time, both clerical and administrative, include order entry, documentation, billing, and coding account for about half of the time they spend on EHR systems. About 85 minutes are spent on inbox management. They concluded that the EHR event logs can be utilized in spotting areas of EHR-related works which can be delegated, hence reducing workload, decrease burnout, and improve professional satisfaction which in turn boosts the quality and efficiency of care provision.\u00a0<\/span>\u00a0<\/span><\/p>\n Kruse, C. S., & Beane, A. (2018). Health information technology continues to show a positive effect on medical outcomes: a systematic review.\u202f<\/span><\/b>Journal of medical Internet research<\/span><\/i><\/b>,\u202f<\/span><\/b>20<\/span><\/i><\/b>(2), e41.<\/span><\/b> doi:\u202f<\/span><\/b>10.2196\/jmir.8793<\/span><\/b><\/a>\u00a0<\/span><\/p>\n Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/a><\/span><\/span><\/p>\n In this article, Kruse and Beane (2018) reviewed the positive impact of health information technology (HIT) on the medical outcome. Recent studies published between 2013 and 2018 were utilized in this research, retrieved from Medical Literature Analysis and Retrieval System Online (MEDLINE) and Cumulative Index of Nursing and Allied Health Literature (CINAHL)\u202fdatabases. The review was conducted in accordance with the Assessment for Multiple Systematic Reviews (AMSTAR). Out of the 3636 papers\u202fthat were arrived at, only 37 met the inclusion criteria for their literature review. The results displayed at least one improvement in medical outcomes concerning the adoption of HIT in 81% of the reviewed literature. Three categories of the outcome and twelve categories of HIT were consistent in the studies about 65 and 38 times respectively. As a result, Kruse and Beane concluded that there is substantial evidence supporting the positive impact of HIT on the effectiveness of medical outcomes.<\/span>\u00a0<\/span><\/p>\n The current healthcare system has greatly transformed towards the adoption of advanced technology in promoting the quality, safety, effectiveness, and outcome of care provision. The current clinical system promotes the utilization of EHR and HIT by healthcare personnel in improving the efficiency of workflow and reduce incidences of burnouts. All the four studies summarized above reveal the positive impacts associated with technology in care provision for effectiveness and improved outcomes. For instance, Islam et al. (2018) and Arndt et al., (2017) revealed the impact of EHR in reducing medical errors and improving workflow and efficiency in the care delivery system. Fu et al. (2017) on the other hand provide evidence supporting the use of diabetes app in improving outcomes among diabetes mellitus patients. Lastly, Kruse and Beane, (2018) provides evidence associated with different aspects of improved medical outcome and effectiveness as a result of HIT. Further advancement in the clinical systems is however expected for further improved outcome and efficiency.<\/span>\u00a0<\/span><\/p>\n Arndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W. J., Sinsky, C. A., & Gilchrist, V. J. (2017). Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations.\u202f<\/span>The Annals of Family Medicine<\/span><\/i>,\u202f<\/span>15<\/span><\/i>(5), 419-426.<\/span> DOI: <\/span>https:\/\/doi.org\/10.1370\/afm.2121<\/span><\/a>\u00a0<\/span>\u00a0<\/span><\/p>\n Fu, H., McMahon, S. K., Gross, C. R., Adam, T. J., & Wyman, J. F. (2017). Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: a systematic review.\u202f<\/span>Diabetes research and clinical practice<\/span><\/i>,\u202f<\/span>131<\/span><\/i>, 70-81. <\/span>https:\/\/doi.org\/10.1016\/j.diabres.2017.06.016<\/span><\/a>\u00a0<\/span>\u00a0<\/span><\/p>\n Islam, M. M., Poly, T. N., & Li, Y.-C. J. (2018).\u202fRecent Advancement of Clinical Information Systems: Opportunities and Challenges. <\/span>Yearbook of medical informatics<\/span><\/i>, volume:27 number:01 year:2018 pages:083-090. DOI:\u202f<\/span>10.1055\/s-0038-1667075<\/span><\/a> Bottom of Form<\/span><\/b>\u00a0<\/span><\/p>\n Kruse, C. S., & Beane, A. (2018). Health information technology continues to show a positive effect on medical outcomes: a systematic review.\u202f<\/span>Journal of medical Internet research<\/span><\/i>,\u202f<\/span>20<\/span><\/i>(2), e41.<\/span> DOI:\u202f<\/span>10.2196\/jmir.8793<\/span><\/a>\u00a0<\/span><\/p>\n I completely concur with your response. Telehealth represents one of the most promising technological innovations that has a beneficial impact on<\/p>\n nursing practice. To meet the patients’ needs and with the current nursing shortage, many homecare agencies have to look at innovative ways to care for the<\/p>\n increasing numbers of patients. Telehealth technology offers productivity improvement for nurses by reducing travel time to remote areas, through increasing<\/p>\n the average daily caseload. Telenursing offers an access to care and the ability to export nursing care using technology. It is a powerful tool for overall<\/p>\n improvement in healthcare. Several measures should be taken for telenursing implementation into practice for all nurses (Glinkowski et al., 2013). In terms<\/p>\n of providing better patient outcomes, nurses are often a patient\u2019s first point of contact when seeking healthcare and a patient’s primary source of health<\/p>\n education and long-term health monitoring. In many institutions, nurses have also taken the lead on integrating telehealth services into patient care (Southern<\/p>\n New Hampshire University, 2020). In all, through telenursing, nurses can provide monitoring, education, follow-up, remote data collection and interventions,<\/p>\n pain management, family support, and multidisciplinary care in an innovative way. It is a good tool to deliver care in remote regions and to facilitate practice<\/p>\n (Glinkowski et al., 2013).<\/p>\n There are several healthcare technology trends that have been observed in the healthcare industry in recent years. These include the use of electronic health records (EHRs), telemedicine, and wearable technology.<\/p>\n One trend that has been widely adopted in healthcare organizations is the use of EHRs. These systems allow healthcare providers to access patient medical history, diagnoses, treatments, and test results in a single, digital location. While EHRs can improve the efficiency of care and coordination between healthcare providers, there are potential challenges and risks associated with their use. One challenge is the high cost of implementing EHR systems, which can be a barrier for smaller organizations. Another risk is the potential for data breaches, which can compromise patient privacy.<\/p>\n One potential benefit of EHRs is the ability to improve patient care outcomes using data analytics. By analyzing patient data, healthcare providers can identify trends and patterns that can inform treatment decisions and help predict patient outcomes. However, there is also a risk that the use of data analytics could lead to biased decision-making if the data is not properly analyzed or if the algorithms used to analyze the data are biased.<\/p>\n Telemedicine is another healthcare technology trend that has gained traction in recent years after the start of the pandemic. One potential benefit of telemedicine is the ability to improve access to care for patients in underserved or rural areas. However, there are also risks associated with telemedicine, such as the potential for data breaches or the possibility that patients may receive inadequate care if the technology is not used correctly.<\/p>\n Wearable technology, such as fitness trackers and smart watches, is another trend that has gained popularity in healthcare. These devices allow patients to track their health and wellness data, such as steps taken and sleep patterns, and share that information with their healthcare providers<\/p>\n \u201cMarketers should communicate the effectiveness of healthcare wearable technology in improving consumers\u2019 health, whilst addressing health concerns. This can contribute to improved user understanding of health, and potential usefulness of healthcare wearable technology.\u201d (Chau, et al, 2019). One potential benefit of wearable technology is the ability to improve patient engagement and self-management of chronic conditions. However, there are also risks associated with wearable technology, such as the possibility of data breaches or the potential for the data to be used for non-medical purposes.<\/p>\n One healthcare technology trend that I believe has the most promise for impacting nursing practice is the use of artificial intelligence (AI) and machine learning. AI and machine learning have the potential to improve patient care outcomes by enabling healthcare providers to analyze large amounts of data and make more accurate diagnoses and treatment recommendations. For example, AI algorithms could be used to analyze medical images and detect abnormalities that may not be visible to the human eye. This could lead to earlier diagnoses and more targeted treatment plans, improving patient outcomes \u201cThese technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer and pharmaceutical organizations\u201d (Davenport, Kalakota, 2019). AI and machine learning could also be used to improve efficiencies in healthcare organizations by automating tasks such as data entry and scheduling.<\/p>\n Overall, while there are potential risks and challenges associated with healthcare technology trends, there are also many potential benefits that can improve patient care outcomes, efficiencies, and data management. The healthcare technology trends that are most promising for impacting nursing practice are those that leverage data analytics, AI, and machine learning to improve patient care and increase efficiencies in healthcare organizations.<\/p>\n <\/p>\n Chau, K. Y., Lam, M. H. S., Cheung, M. L., Tso, E. K. H., Flint, S. W., Broom, D. R., Tse, G., & Lee, K. Y. (2019). Smart technology for healthcare: Exploring the<\/p>\n antecedents of adoption intention of healthcare wearable technology.\u00a0Health psychology research<\/em>,\u00a07<\/em>(1), 8099.<\/p>\n https:\/\/doi.org\/10.4081\/hpr.2019.8099Links to an external site.<\/a><\/p>\n Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare.\u00a0Future healthcare journal<\/em>,\u00a06<\/em>(2), 94\u201398.<\/p>\n https:\/\/doi.org\/10.7861\/futurehosp.6-\u00a0Links to an external site.<\/a>2-94<\/p>\n 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.<\/p>\n Lu Wenjie, Zhang Jiaming, & Jiang Weiyu. (2023). The difference and clinical application of modified thoracolumbar fracture classification scoring system in guiding clinical treatment.\u00a0Journal of Orthopaedic Surgery and Research,\u00a018(1), 1\u20138. https:\/\/doi.org\/10.1186\/s13018-023-03958-4<\/a><\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.\u00a0Journal of Advances in Medical Education and Professionalism,\u00a011(2), 95\u2013104. https:\/\/doi.org\/10.30476\/jamp.2022.95843.1661<\/a><\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.\u00a0BioMedical Engineering OnLine,\u00a022(1), 1\u201313. https:\/\/doi.org\/10.1186\/s12938-023-01097-9<\/a><\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.\u00a0Journal of Healthcare Engineering,\u00a02023, 8550905. https:\/\/doi.org\/10.1155\/2023\/8550905<\/a><\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n \u00a0<\/strong><\/p>\n \u00a0<\/strong><\/p>\n 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.\u00a0Journal of Healthcare Engineering,\u00a02023, 8550905. https:\/\/doi.org\/10.1155\/2023\/8550905<\/a><\/p>\n Lu Wenjie, Zhang Jiaming, & Jiang Weiyu. (2023). The difference and clinical application of modified thoracolumbar fracture classification scoring system in guiding clinical treatment.\u00a0Journal of Orthopaedic Surgery and Research,\u00a018(1), 1\u20138. https:\/\/doi.org\/10.1186\/s13018-023-03958-4<\/a><\/p>\n 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.\u00a0Journal of Advances in Medical Education and Professionalism,\u00a011(2), 95\u2013104. https:\/\/doi.org\/10.30476\/jamp.2022.95843.1661<\/a><\/p>\n 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.\u00a0BioMedical Engineering OnLine,\u00a022(1), 1\u201313. https:\/\/doi.org\/10.1186\/s12938-023-01097-9<\/a><\/p>\nRESOURCES<\/h2>\n
\nClick the weekly resources link to access the resources.<\/p>\nWEEKLY RESOURCES<\/strong><\/a><\/h2>\n
To Prepare:<\/strong><\/h3>\n
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The Assignment: (4-5 pages not including the title and reference page)<\/strong><\/h2>\n
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BY DAY 7 OF WEEK 8<\/h2>\n
SUBMISSION INFORMATION<\/h2>\n
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A Sample Answer For the Assignment: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\n
Title: <\/strong> NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\n
Literature Review<\/span><\/b>\u00a0<\/span><\/h2>\n
Conclusion<\/span><\/b><\/h2>\n
References\u00a0<\/span><\/b><\/h2>\n
References<\/h2>\n
A Sample Answer 2 For the Assignment: NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\n
Title: <\/strong> NURS 6051 LITERATURE REVIEW: THE USE OF CLINICAL SYSTEMS TO IMPROVE OUTCOMES AND EFFICIENCIES<\/strong><\/h2>\n
Introduction<\/strong><\/h2>\n
Annotated Bibliography<\/strong><\/h2>\n
Research Article 1<\/strong><\/h3>\n
Research Article 2<\/strong><\/h2>\n
Research Article 3<\/strong><\/h2>\n
Research Article 4<\/strong><\/h2>\n
Conclusion<\/strong><\/h2>\n
References<\/strong><\/h2>\n
Assignment_Rubric<\/strong><\/h2>\n
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\n NURS_5051_Module04_Week08_Assignment_Rubric<\/td>\n<\/tr>\n \n Criteria<\/strong><\/td>\n Ratings<\/strong><\/td>\n Pts<\/strong><\/td>\n<\/tr>\n<\/thead>\n\n \n This criterion is linked to a Learning OutcomeIn 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:\u00b7 Properly identify 4 peer-reviewed research articles you reviewed.<\/td>\n \n