Sample Answer for NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS Included After Question<\/strong><\/em><\/span><\/h2>\nThroughout history, technological advancements have appeared for one purpose before finding applications elsewhere that lead to spikes in its usage and development. The internet, for example, was originally developed to share research before becoming a staple of work and entertainment. But technology\u2014new and repurposed\u2014will undoubtedly continue to be a driver of healthcare information. Informatics often stay tuned to trends to monitor what the next new technology will be or how the next new idea for applying existing technology can benefit outcomes.<\/span>\u00a0<\/span><\/p>\nIn this Discussion, you will reflect on your healthcare organization\u2019s use of technology and offer a technology trend you observe in your environment.<\/span>\u00a0<\/span><\/p>\nRESOURCES<\/span>\u00a0<\/span><\/h2>\nBe sure to review the Learning Resources before completing this activity.<\/span>
\nClick the weekly resources link to access the resources.\u202f<\/span>\u00a0<\/span><\/p>\nWEEKLY RESOURCES<\/span><\/b><\/a>\u00a0<\/span><\/h2>\nTo Prepare:<\/span><\/b>\u00a0<\/span><\/h3>\n\n- Reflect on the Resources related to digital information tools and technologies.<\/span>\u00a0<\/span><\/li>\n
- Consider your healthcare organization\u2019s use of healthcare technologies to manage and distribute information.<\/span>\u00a0<\/span><\/li>\n
- Reflect on current and potential future trends, such as use of social media and mobile applications\/telehealth, Internet of Things (IoT)-enabled asset tracking, or expert systems\/artificial intelligence, and how they may impact nursing practice and healthcare delivery<\/a>.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
BY DAY 3 OF WEEK 6<\/span>\u00a0<\/span><\/h2>\nPost<\/span><\/b>\u202fa brief description of general healthcare technology trends, particularly related to data\/information you have observed in use in your healthcare organization or nursing practice<\/a>. Describe any potential challenges or risks that may be inherent in the technologies associated with these trends you described. Then, describe at least one potential benefit and one potential risk associated with data safety, legislation, and patient care for the technologies you described. Next, explain which healthcare technology trends you believe are most promising for impacting healthcare technology in nursing practice and explain why. Describe whether this promise will contribute to improvements in patient care outcomes, efficiencies, or data management. Be specific and provide examples.<\/span><\/p>\n![\"NURS](\"http:\/\/nursingassignmentcrackers.com\/wp-content\/uploads\/2024\/01\/NURS-6051-HEALTHCARE-INFORMATION-TECHNOLOGY-TRENDS-300x121.png\")
NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/figcaption><\/figure>\nBY DAY 6 OF WEEK 6<\/span>\u00a0<\/span><\/h2>\nRespond<\/span><\/b>\u202fto at least\u202f<\/span>two<\/span><\/b>\u202fof your colleagues<\/span>* on two different days<\/span><\/b>, offering additional\/alternative ideas regarding opportunities and risks related to the observations shared.<\/span>\u00a0<\/span><\/p>\n*Note:<\/span><\/i><\/b>\u202fThroughout this program, your fellow students are referred to as colleagues.<\/span><\/i>\u00a0<\/span><\/p>\n\u00a0<\/span><\/p>\nSearch entries or author\u202fFilter replies by unread<\/span>[Control]Unread\u202f\u202f \u202f\u202fCollapse replies\u202fExpand replies<\/span>\u00a0<\/span><\/p>\nA Sample Answer For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nTitle: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nA general healthcare technology trend related to information that I have observed in my nursing practice is the increasing use of electronic health records (EHRs). EHRs allow multiple healthcare providers to access and update a patient\u2019s information digitally, as opposed to relying on locating or faxing over paper records (HealthIT.gov, 2018). When I worked in an outpatient office that did not use an EHR, I saw how this slowed down patient care. We wanted to avoid repeating tests a patient had already gotten and wanted to fully understand the patient\u2019s history, but it could mean hours of waiting for the patient\u2019s record to be faxed over from the other office. Sometimes we would finally get a record, but a crucial page would be missing, or an important page would have handwriting from the provider that was barely legible, which further delayed patient care and could have caused patient harm. This shows how a benefit of EHRs is the improvement in patient care outcomes by giving providers complete and up-to-date information about their patients immediately. This allows more accurate diagnosis, quicker treatment, and the ability to communicate with other healthcare providers in the team.<\/span>\u00a0<\/span><\/p>\nEHRs help avoid many of the problems of paper records, but also come with their own set of risks. For example, security and confidentiality of patient information that is now visible by possibly hundreds of healthcare providers is a concern, as well as the risk of data loss or system outages. My current hospital uses an EHR, and the system shut down during shift change one Sunday morning. This caused a lot of confusion and risk for patient harm, as we could not access the patient\u2019s information needed to give report to the oncoming nurse, hand off critical medications, give medication, and more. \u202fThere is also a risk of data breaches with EHRs, which could lead to patient information being disclosed without their consent to unauthorized parties. This risk can be mitigated by having strong security measures, such as two-factor authentication that my hospital uses, and regularly training staff on how to protect patient data (Abouelmehdi et al., 2018).<\/span>\u00a0<\/span><\/p>\n\u202f<\/span>\u00a0<\/span>A healthcare technology trend that I believe is promising for impacting healthcare technology in nursing practice is telehealth. I believe it will help patient care outcomes and efficiencies. Telehealth allows healthcare providers to deliver care remotely, using video conferencing and other digital tools (Skiba, 2017). This is especially useful in areas that do not have nearby access to healthcare providers, such as rural or underserved areas. For patients that have chronic conditions or who cannot easily travel to a healthcare facility, telehealth is also valuable. During the beginning of the covid pandemic when social distancing was paramount for everyone\u2019s safety, I met with my healthcare provider through telehealth.<\/span>\u00a0<\/span><\/p>\n\u202f<\/span>\u00a0<\/span>A potential risk of telehealth is thinking that it is suitable for all types of care, as a physical exam is a key to diagnosing and treating most conditions; a provider may not be able to safely diagnose a condition with only a history and your description of your symptoms. Another risk is the quality of the technology being used, as a zoom meeting with choppy audio or internet outages will not allow you to have a productive telehealth visit. There is also a risk of a lack of confidentiality of patient data. However, overall, both EHRs and telehealth can improve patient care outcomes, efficiencies, and data management for nursing practice, as long as we consider the risks associated with these technologies and take steps to mitigate them.<\/span>\u00a0<\/span><\/p>\n\u202f<\/span>\u00a0<\/span><\/p>\nReferences:<\/span>\u00a0<\/span><\/h2>\nHealthIT.gov. (2018c).\u202f<\/span>What is an electronic health record (EHR)<\/span><\/i>?\u202f<\/span>\u202fRetrieved from\u202f<\/span>
\nhttps:\/\/www.healthit.gov\/faq\/what-electronic-health-record-ehr<\/span>Links to an external site.<\/span><\/a>\u00a0<\/span><\/p>\nAbouelmehdi, K., Beni-Hessane, A. & Khaloufi, H. (2018) Big healthcare data: preserving security and privacy.\u202f<\/span>J Big Data<\/span><\/i>\u202f<\/span>5<\/span><\/b>, 1.\u202f<\/span>https:\/\/doi.org\/10.1186\/s40537-017-0110-7<\/span>Links to an external site.<\/span><\/a>\u00a0<\/span><\/p>\nSkiba, D. (2017).\u202f<\/span>Evaluation tools to appraise social media and mobile applications\u202f<\/span>Links to an external site.<\/span><\/a>.\u202f<\/span>Informatics, 4<\/span><\/i>(3), 32\u201340.\u202f<\/span>\u00a0<\/span><\/p>\nA Sample Answer 2 For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nTitle: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nIndeed most healthcare organizations are shifting from paperwork to electronic health records and electronic medical records. Electronic medical records to document medication dosages, administration, and other treatments help nurses avoid medical errors and confusion during practice. The electronic systems keep the patient information safe and confidential. Patient safety is also increased due to minimal errors during treatment and care management. I am sure there are organizations using cradle for recording patient information and this has improved nursing care and reduced medical errors because there is no misleading information about drug administration and care planning (Agbo et al., 2019). Communication has also been enhanced by applying new technology. Clinicians are not being trained fast enough to keep pace with the rate of service demand. In addition, given the rising cost of care, new models for reimbursing hospitals and other providers have begun to emphasize quality and efficiency rather than units of delivered services.<\/span>\u00a0<\/span><\/p>\nReference<\/span>\u00a0<\/span><\/h2>\nAgbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019). Blockchain technology in healthcare: a systematic review. In\u202f<\/span>Healthcare<\/span><\/i>\u202f(Vol. 7, No. 2, p. 56). Multidisciplinary Digital Publishing Institute.<\/span>\u00a0<\/span><\/p>\nA Sample Answer 3 For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nTitle: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\nClinical Decision-Making<\/span><\/b>\u00a0<\/span><\/h3>\nThe burden of a wrong diagnosis can be significant for the patient and the healthcare system. If misdiagnosed, patients may experience unnecessary suffering, prolonged treatment, and even death (Elliott et al., 2020). The healthcare system also bears the burden of these mistakes, as they can lead to increased healthcare costs, legal consequences, and damage to the healthcare provider’s reputation (Elliott et al., 2020). In addition, wrong diagnoses can have far-reaching consequences, as they can delay the correct diagnosis and treatment of the patient’s condition. This can hurt the patient’s prognosis and overall health. In clinical decision-making, it is crucial to consider the potential consequences of a wrong diagnosis and to take steps to minimize the risk of misdiagnosis (Elliott et al., 2020). This may involve seeking additional opinions, using diagnostic tools, and collaborating with other healthcare professionals.<\/span>\u00a0<\/span><\/p>\nThe healthcare industry has used technology to attempt to breach the gap between excellent clinical outcomes. Advances in artificial intelligence and machine learning utilization in many clinical settings needing healthcare data analysis have indicated the stages towards achieving the goal. We have also seen big data paving its way into consolidating the large data sets generated by healthcare processes (Pramanik et al., 2020). Electronic health records are probably the oldest steps in the right direction, combined with adjacent supportive digital tools to improve the accuracy and completeness of patient information, which can help prevent errors in diagnosis (Wass & Vimarlund, 2018). Increased collaboration and information sharing among healthcare providers have the potential to help reduce the risk of the wrong diagnosis, and efforts towards the same have been made. Clinical decision support technologies, which give doctors real-time notifications about potential diagnostic errors or other potential safety hazards, have been a major step toward clearer clinical diagnosis.<\/span>\u00a0<\/span><\/p>\nClinical Decision Support Systems<\/span><\/b>\u00a0<\/span><\/h2>\nClinical decision support systems (CDSS) are computerized tools that provide healthcare professionals with evidence-based information and support for clinical decision-making (Souza-Pereira et al., 2021). They are designed to help healthcare providers make more informed and accurate decisions about patients’ diagnoses, treatment, and management. CDSS can be implemented in various forms, such as electronic health records (EHRs), alerts, and clinical guidelines, and can be accessed through various platforms, such as computers, tablets, and mobile devices. Some common features of CDSS include evidence-based recommendations for diagnosing, treating, and managing patients, which can help improve the quality and safety of care (Taheri Moghadam et al., 2021). They also provide personalized recommendations based on the patient’s needs and medical history. Sometimes, they can provide alerts and reminders to healthcare providers about important clinical information, such as test results, drug interactions, and follow-up care (Taheri Moghadam et al., 2021). The systems avail access to clinical guidelines and best practices to help healthcare providers make informed decisions. CDSS can also provide decision support to help healthcare providers weigh the risks and benefits of different treatment options and make informed decisions about the most appropriate course of action.<\/span>\u00a0<\/span><\/p>\nBenefits And Risks<\/span><\/b>\u00a0<\/span><\/h2>\nOne potential benefit of CDSS in data safety, legislation, and patient care is that it can help reduce the risk of medical errors and improve patient outcomes (Souza-Pereira et al., 2021). By providing healthcare providers with real-time access to relevant patient information and clinical guidelines, the systems can help facilitate more accurate diagnoses and treatment decisions. A wrong diagnosis can lead to misdirected treatment, unnecessary testing and procedures, and increased healthcare costs (Souza-Pereira et al., 2021). The systems can help mitigate these issues by providing healthcare providers with access to the latest evidence-based guidelines and recommendations and patient-specific information (Taheri Moghadam et al., 2021). This can ultimately lead to improved patient safety and satisfaction and cost savings for the healthcare system.<\/span>\u00a0<\/span><\/p>\nHowever, there are also potential risks associated with the use of CDSS. One risk is that the system may not accurately interpret or incorporate all relevant patient information, leading to incorrect or incomplete clinical recommendations, especially when not programmed intently (Wang et al., 2021). In addition, there is a risk that CDSS may be misused or relied upon too heavily, leading to over- or under-treatment of patients (Wang et al., 2021). There is also the potential for data privacy and security breaches, as CDSS typically involves collecting and sharing sensitive patient information. It is important for healthcare providers to carefully consider these potential risks and take appropriate measures to mitigate them when implementing CDSS in their practice.<\/span>\u00a0<\/span><\/p>\nImpact on Nursing Practice<\/span><\/b>\u00a0<\/span><\/h2>\nMost trends hold promise in driving technological advancements to bridge inefficiency gaps. Of all the trends, there is a common endpoint: ensuring the process of making a diagnosis to intervening is as seamless, accurate and cost-effective as possible. The drawbacks levied against artificial intelligence and machine learning in patient data analysis, big data in handling large amounts of data, and electronic health records centre around whether the correct data is being used, the technology can handle it correctly and effectively, and whether the output is accurate and useful (Wass & Vimarlund, 2018). Improving on these drawbacks means CDSS has the most potential to ensure efficiencies in the delivery of healthcare, as all of them arrive at immensely sharpening the systems supporting healthcare providers in decision-making.<\/span>\u00a0<\/span><\/p>\nExcellent decision-making in healthcare can have a significant impact on patient care outcomes. Well-informed decisions can lead to more accurate diagnoses and more targeted and effective treatment plans (Taheri Moghadam et al., 2021). This can lead to improved patient outcomes and a reduction in the length of hospital stays. In terms of efficiency, good decision-making can help healthcare providers to prioritize tasks and allocate resources effectively, leading to a more streamlined and efficient healthcare system. Excellent decision-making can also lead to better data management, as accurate and thorough documentation is crucial for making informed decisions and tracking patient progress (Souza-Pereira et al., 2021). By constantly improving on the trends, capitalizing on mistakes made and streamlining them, the technological tools will be more focused in their data collection process, taking care to pick up on relevant information only in the shortest time, banking on the least resources as possible. For example, diabetes care can be mapped out from the health-seeking behaviour trends, diagnosis to follow-up, with the least resources utilized (Jeffrey et al., 2019). Data synthesis will also be robust, and the output will more likely abide by evidence-based guidelines coupled with the potential for the data to guide other research endeavours.<\/span>\u00a0<\/span><\/p>\nReferences<\/span><\/b>\u00a0<\/span><\/h2>\nElliott, R. A., Camacho, E., Jankovic, D., Sculpher, M. J., & Faria, R. (2020). Economic Analysis of the Prevalence and Clinical and Economic Burden of Medication Error in England.\u202f<\/span>BMJ Quality & Safety<\/span><\/i>,\u202f<\/span>30<\/span><\/i>(2), bmjqs-2019-010206. https:\/\/doi.org\/10.1136\/bmjqs-2019-010206<\/a><\/span>\u00a0<\/span><\/p>\nJeffrey, B., Bagala, M., Creighton, A., Leavey, T., Nicholls, S., Wood, C., Longman, J., Barker, J., & Pit, S. (2019). Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users.\u202f<\/span>Diabetology & Metabolic Syndrome<\/span><\/i>,\u202f<\/span>11<\/span><\/i>(1), 1\u201317. https:\/\/doi.org\/10.1186\/s13098-019-0480-4<\/a><\/span>\u00a0<\/span><\/p>\nPramanik, I., Lau, R. Y. K., Azad, A. K., Hossain, S., Hossain, K., & Karmaker, B. K. (2020). Healthcare Informatics and Analytics in Big Data.\u202f<\/span>Expert Systems with Applications<\/span><\/i>,\u202f<\/span>152<\/span><\/i>, 113388. https:\/\/doi.org\/10.1016\/j.eswa.2020.113388<\/a><\/span>\u00a0<\/span><\/p>\nSouza-Pereira, L., Ouhbi, S., & Pombo, N. (2021). Quality-in-use characteristics for clinical decision support system assessment.\u202f<\/span>Computer Methods and Programs in Biomedicine<\/span><\/i>,\u202f<\/span>207<\/span><\/i>, 106169. https:\/\/doi.org\/10.1016\/j.cmpb.2021.106169<\/a><\/span>\u00a0<\/span><\/p>\nTaheri Moghadam, S., Sadoughi, F., Velayati, F., Ehsanzadeh, S. J., & Poursharif, S. (2021). The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis.\u202f<\/span>BMC Medical Informatics and Decision Making<\/span><\/i>,\u202f<\/span>21<\/span><\/i>(1). https:\/\/doi.org\/10.1186\/s12911-020-01376-8<\/a><\/span>\u00a0<\/span><\/p>\nWang, D., Wang, L., Zhang, Z., Wang, D., Zhu, H., Gao, Y., Fan, X., & Tian, F. (2021). \u201cBrilliant AI Doctor\u201d in Rural Clinics: Challenges in AI-Powered Clinical Decision Support System Deployment.\u202f<\/span>Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems<\/span><\/i>. https:\/\/doi.org\/10.1145\/3411764.3445432<\/a><\/span>\u00a0<\/span><\/p>\nWass, S., & Vimarlund, V. (2018). Same, same but different: Perceptions of patients\u2019 online access to electronic health records among healthcare professionals.\u202f<\/span>
In this Discussion, you will reflect on your healthcare organization\u2019s use of technology and offer a technology trend you observe in your environment.<\/span>\u00a0<\/span><\/p>\n Be sure to review the Learning Resources before completing this activity.<\/span> Post<\/span><\/b>\u202fa brief description of general healthcare technology trends, particularly related to data\/information you have observed in use in your healthcare organization or nursing practice<\/a>. Describe any potential challenges or risks that may be inherent in the technologies associated with these trends you described. Then, describe at least one potential benefit and one potential risk associated with data safety, legislation, and patient care for the technologies you described. Next, explain which healthcare technology trends you believe are most promising for impacting healthcare technology in nursing practice and explain why. Describe whether this promise will contribute to improvements in patient care outcomes, efficiencies, or data management. Be specific and provide examples.<\/span><\/p>\n Respond<\/span><\/b>\u202fto at least\u202f<\/span>two<\/span><\/b>\u202fof your colleagues<\/span>* on two different days<\/span><\/b>, offering additional\/alternative ideas regarding opportunities and risks related to the observations shared.<\/span>\u00a0<\/span><\/p>\n *Note:<\/span><\/i><\/b>\u202fThroughout this program, your fellow students are referred to as colleagues.<\/span><\/i>\u00a0<\/span><\/p>\n \u00a0<\/span><\/p>\n Search entries or author\u202fFilter replies by unread<\/span>[Control]Unread\u202f\u202f \u202f\u202fCollapse replies\u202fExpand replies<\/span>\u00a0<\/span><\/p>\n A general healthcare technology trend related to information that I have observed in my nursing practice is the increasing use of electronic health records (EHRs). EHRs allow multiple healthcare providers to access and update a patient\u2019s information digitally, as opposed to relying on locating or faxing over paper records (HealthIT.gov, 2018). When I worked in an outpatient office that did not use an EHR, I saw how this slowed down patient care. We wanted to avoid repeating tests a patient had already gotten and wanted to fully understand the patient\u2019s history, but it could mean hours of waiting for the patient\u2019s record to be faxed over from the other office. Sometimes we would finally get a record, but a crucial page would be missing, or an important page would have handwriting from the provider that was barely legible, which further delayed patient care and could have caused patient harm. This shows how a benefit of EHRs is the improvement in patient care outcomes by giving providers complete and up-to-date information about their patients immediately. This allows more accurate diagnosis, quicker treatment, and the ability to communicate with other healthcare providers in the team.<\/span>\u00a0<\/span><\/p>\n EHRs help avoid many of the problems of paper records, but also come with their own set of risks. For example, security and confidentiality of patient information that is now visible by possibly hundreds of healthcare providers is a concern, as well as the risk of data loss or system outages. My current hospital uses an EHR, and the system shut down during shift change one Sunday morning. This caused a lot of confusion and risk for patient harm, as we could not access the patient\u2019s information needed to give report to the oncoming nurse, hand off critical medications, give medication, and more. \u202fThere is also a risk of data breaches with EHRs, which could lead to patient information being disclosed without their consent to unauthorized parties. This risk can be mitigated by having strong security measures, such as two-factor authentication that my hospital uses, and regularly training staff on how to protect patient data (Abouelmehdi et al., 2018).<\/span>\u00a0<\/span><\/p>\n \u202f<\/span>\u00a0<\/span>A healthcare technology trend that I believe is promising for impacting healthcare technology in nursing practice is telehealth. I believe it will help patient care outcomes and efficiencies. Telehealth allows healthcare providers to deliver care remotely, using video conferencing and other digital tools (Skiba, 2017). This is especially useful in areas that do not have nearby access to healthcare providers, such as rural or underserved areas. For patients that have chronic conditions or who cannot easily travel to a healthcare facility, telehealth is also valuable. During the beginning of the covid pandemic when social distancing was paramount for everyone\u2019s safety, I met with my healthcare provider through telehealth.<\/span>\u00a0<\/span><\/p>\n \u202f<\/span>\u00a0<\/span>A potential risk of telehealth is thinking that it is suitable for all types of care, as a physical exam is a key to diagnosing and treating most conditions; a provider may not be able to safely diagnose a condition with only a history and your description of your symptoms. Another risk is the quality of the technology being used, as a zoom meeting with choppy audio or internet outages will not allow you to have a productive telehealth visit. There is also a risk of a lack of confidentiality of patient data. However, overall, both EHRs and telehealth can improve patient care outcomes, efficiencies, and data management for nursing practice, as long as we consider the risks associated with these technologies and take steps to mitigate them.<\/span>\u00a0<\/span><\/p>\n \u202f<\/span>\u00a0<\/span><\/p>\n HealthIT.gov. (2018c).\u202f<\/span>What is an electronic health record (EHR)<\/span><\/i>?\u202f<\/span>\u202fRetrieved from\u202f<\/span> Abouelmehdi, K., Beni-Hessane, A. & Khaloufi, H. (2018) Big healthcare data: preserving security and privacy.\u202f<\/span>J Big Data<\/span><\/i>\u202f<\/span>5<\/span><\/b>, 1.\u202f<\/span>https:\/\/doi.org\/10.1186\/s40537-017-0110-7<\/span>Links to an external site.<\/span><\/a>\u00a0<\/span><\/p>\n Skiba, D. (2017).\u202f<\/span>Evaluation tools to appraise social media and mobile applications\u202f<\/span>Links to an external site.<\/span><\/a>.\u202f<\/span>Informatics, 4<\/span><\/i>(3), 32\u201340.\u202f<\/span>\u00a0<\/span><\/p>\n Indeed most healthcare organizations are shifting from paperwork to electronic health records and electronic medical records. Electronic medical records to document medication dosages, administration, and other treatments help nurses avoid medical errors and confusion during practice. The electronic systems keep the patient information safe and confidential. Patient safety is also increased due to minimal errors during treatment and care management. I am sure there are organizations using cradle for recording patient information and this has improved nursing care and reduced medical errors because there is no misleading information about drug administration and care planning (Agbo et al., 2019). Communication has also been enhanced by applying new technology. Clinicians are not being trained fast enough to keep pace with the rate of service demand. In addition, given the rising cost of care, new models for reimbursing hospitals and other providers have begun to emphasize quality and efficiency rather than units of delivered services.<\/span>\u00a0<\/span><\/p>\n Agbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019). Blockchain technology in healthcare: a systematic review. In\u202f<\/span>Healthcare<\/span><\/i>\u202f(Vol. 7, No. 2, p. 56). Multidisciplinary Digital Publishing Institute.<\/span>\u00a0<\/span><\/p>\n The burden of a wrong diagnosis can be significant for the patient and the healthcare system. If misdiagnosed, patients may experience unnecessary suffering, prolonged treatment, and even death (Elliott et al., 2020). The healthcare system also bears the burden of these mistakes, as they can lead to increased healthcare costs, legal consequences, and damage to the healthcare provider’s reputation (Elliott et al., 2020). In addition, wrong diagnoses can have far-reaching consequences, as they can delay the correct diagnosis and treatment of the patient’s condition. This can hurt the patient’s prognosis and overall health. In clinical decision-making, it is crucial to consider the potential consequences of a wrong diagnosis and to take steps to minimize the risk of misdiagnosis (Elliott et al., 2020). This may involve seeking additional opinions, using diagnostic tools, and collaborating with other healthcare professionals.<\/span>\u00a0<\/span><\/p>\n The healthcare industry has used technology to attempt to breach the gap between excellent clinical outcomes. Advances in artificial intelligence and machine learning utilization in many clinical settings needing healthcare data analysis have indicated the stages towards achieving the goal. We have also seen big data paving its way into consolidating the large data sets generated by healthcare processes (Pramanik et al., 2020). Electronic health records are probably the oldest steps in the right direction, combined with adjacent supportive digital tools to improve the accuracy and completeness of patient information, which can help prevent errors in diagnosis (Wass & Vimarlund, 2018). Increased collaboration and information sharing among healthcare providers have the potential to help reduce the risk of the wrong diagnosis, and efforts towards the same have been made. Clinical decision support technologies, which give doctors real-time notifications about potential diagnostic errors or other potential safety hazards, have been a major step toward clearer clinical diagnosis.<\/span>\u00a0<\/span><\/p>\n Clinical decision support systems (CDSS) are computerized tools that provide healthcare professionals with evidence-based information and support for clinical decision-making (Souza-Pereira et al., 2021). They are designed to help healthcare providers make more informed and accurate decisions about patients’ diagnoses, treatment, and management. CDSS can be implemented in various forms, such as electronic health records (EHRs), alerts, and clinical guidelines, and can be accessed through various platforms, such as computers, tablets, and mobile devices. Some common features of CDSS include evidence-based recommendations for diagnosing, treating, and managing patients, which can help improve the quality and safety of care (Taheri Moghadam et al., 2021). They also provide personalized recommendations based on the patient’s needs and medical history. Sometimes, they can provide alerts and reminders to healthcare providers about important clinical information, such as test results, drug interactions, and follow-up care (Taheri Moghadam et al., 2021). The systems avail access to clinical guidelines and best practices to help healthcare providers make informed decisions. CDSS can also provide decision support to help healthcare providers weigh the risks and benefits of different treatment options and make informed decisions about the most appropriate course of action.<\/span>\u00a0<\/span><\/p>\n One potential benefit of CDSS in data safety, legislation, and patient care is that it can help reduce the risk of medical errors and improve patient outcomes (Souza-Pereira et al., 2021). By providing healthcare providers with real-time access to relevant patient information and clinical guidelines, the systems can help facilitate more accurate diagnoses and treatment decisions. A wrong diagnosis can lead to misdirected treatment, unnecessary testing and procedures, and increased healthcare costs (Souza-Pereira et al., 2021). The systems can help mitigate these issues by providing healthcare providers with access to the latest evidence-based guidelines and recommendations and patient-specific information (Taheri Moghadam et al., 2021). This can ultimately lead to improved patient safety and satisfaction and cost savings for the healthcare system.<\/span>\u00a0<\/span><\/p>\n However, there are also potential risks associated with the use of CDSS. One risk is that the system may not accurately interpret or incorporate all relevant patient information, leading to incorrect or incomplete clinical recommendations, especially when not programmed intently (Wang et al., 2021). In addition, there is a risk that CDSS may be misused or relied upon too heavily, leading to over- or under-treatment of patients (Wang et al., 2021). There is also the potential for data privacy and security breaches, as CDSS typically involves collecting and sharing sensitive patient information. It is important for healthcare providers to carefully consider these potential risks and take appropriate measures to mitigate them when implementing CDSS in their practice.<\/span>\u00a0<\/span><\/p>\n Most trends hold promise in driving technological advancements to bridge inefficiency gaps. Of all the trends, there is a common endpoint: ensuring the process of making a diagnosis to intervening is as seamless, accurate and cost-effective as possible. The drawbacks levied against artificial intelligence and machine learning in patient data analysis, big data in handling large amounts of data, and electronic health records centre around whether the correct data is being used, the technology can handle it correctly and effectively, and whether the output is accurate and useful (Wass & Vimarlund, 2018). Improving on these drawbacks means CDSS has the most potential to ensure efficiencies in the delivery of healthcare, as all of them arrive at immensely sharpening the systems supporting healthcare providers in decision-making.<\/span>\u00a0<\/span><\/p>\n Excellent decision-making in healthcare can have a significant impact on patient care outcomes. Well-informed decisions can lead to more accurate diagnoses and more targeted and effective treatment plans (Taheri Moghadam et al., 2021). This can lead to improved patient outcomes and a reduction in the length of hospital stays. In terms of efficiency, good decision-making can help healthcare providers to prioritize tasks and allocate resources effectively, leading to a more streamlined and efficient healthcare system. Excellent decision-making can also lead to better data management, as accurate and thorough documentation is crucial for making informed decisions and tracking patient progress (Souza-Pereira et al., 2021). By constantly improving on the trends, capitalizing on mistakes made and streamlining them, the technological tools will be more focused in their data collection process, taking care to pick up on relevant information only in the shortest time, banking on the least resources as possible. For example, diabetes care can be mapped out from the health-seeking behaviour trends, diagnosis to follow-up, with the least resources utilized (Jeffrey et al., 2019). Data synthesis will also be robust, and the output will more likely abide by evidence-based guidelines coupled with the potential for the data to guide other research endeavours.<\/span>\u00a0<\/span><\/p>\n Elliott, R. A., Camacho, E., Jankovic, D., Sculpher, M. J., & Faria, R. (2020). Economic Analysis of the Prevalence and Clinical and Economic Burden of Medication Error in England.\u202f<\/span>BMJ Quality & Safety<\/span><\/i>,\u202f<\/span>30<\/span><\/i>(2), bmjqs-2019-010206. https:\/\/doi.org\/10.1136\/bmjqs-2019-010206<\/a><\/span>\u00a0<\/span><\/p>\n Jeffrey, B., Bagala, M., Creighton, A., Leavey, T., Nicholls, S., Wood, C., Longman, J., Barker, J., & Pit, S. (2019). Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users.\u202f<\/span>Diabetology & Metabolic Syndrome<\/span><\/i>,\u202f<\/span>11<\/span><\/i>(1), 1\u201317. https:\/\/doi.org\/10.1186\/s13098-019-0480-4<\/a><\/span>\u00a0<\/span><\/p>\n Pramanik, I., Lau, R. Y. K., Azad, A. K., Hossain, S., Hossain, K., & Karmaker, B. K. (2020). Healthcare Informatics and Analytics in Big Data.\u202f<\/span>Expert Systems with Applications<\/span><\/i>,\u202f<\/span>152<\/span><\/i>, 113388. https:\/\/doi.org\/10.1016\/j.eswa.2020.113388<\/a><\/span>\u00a0<\/span><\/p>\n Souza-Pereira, L., Ouhbi, S., & Pombo, N. (2021). Quality-in-use characteristics for clinical decision support system assessment.\u202f<\/span>Computer Methods and Programs in Biomedicine<\/span><\/i>,\u202f<\/span>207<\/span><\/i>, 106169. https:\/\/doi.org\/10.1016\/j.cmpb.2021.106169<\/a><\/span>\u00a0<\/span><\/p>\n Taheri Moghadam, S., Sadoughi, F., Velayati, F., Ehsanzadeh, S. J., & Poursharif, S. (2021). The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis.\u202f<\/span>BMC Medical Informatics and Decision Making<\/span><\/i>,\u202f<\/span>21<\/span><\/i>(1). https:\/\/doi.org\/10.1186\/s12911-020-01376-8<\/a><\/span>\u00a0<\/span><\/p>\n Wang, D., Wang, L., Zhang, Z., Wang, D., Zhu, H., Gao, Y., Fan, X., & Tian, F. (2021). \u201cBrilliant AI Doctor\u201d in Rural Clinics: Challenges in AI-Powered Clinical Decision Support System Deployment.\u202f<\/span>Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems<\/span><\/i>. https:\/\/doi.org\/10.1145\/3411764.3445432<\/a><\/span>\u00a0<\/span><\/p>\n Wass, S., & Vimarlund, V. (2018). Same, same but different: Perceptions of patients\u2019 online access to electronic health records among healthcare professionals.\u202f<\/span>RESOURCES<\/span>\u00a0<\/span><\/h2>\n
\nClick the weekly resources link to access the resources.\u202f<\/span>\u00a0<\/span><\/p>\nWEEKLY RESOURCES<\/span><\/b><\/a>\u00a0<\/span><\/h2>\n
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BY DAY 3 OF WEEK 6<\/span>\u00a0<\/span><\/h2>\n
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A Sample Answer For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
Title: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
References:<\/span>\u00a0<\/span><\/h2>\n
\nhttps:\/\/www.healthit.gov\/faq\/what-electronic-health-record-ehr<\/span>Links to an external site.<\/span><\/a>\u00a0<\/span><\/p>\nA Sample Answer 2 For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
Title: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
Reference<\/span>\u00a0<\/span><\/h2>\n
A Sample Answer 3 For the Assignment: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
Title: NURS 6051 HEALTHCARE INFORMATION TECHNOLOGY TRENDS<\/strong><\/h2>\n
Clinical Decision-Making<\/span><\/b>\u00a0<\/span><\/h3>\n
Clinical Decision Support Systems<\/span><\/b>\u00a0<\/span><\/h2>\n
Benefits And Risks<\/span><\/b>\u00a0<\/span><\/h2>\n
Impact on Nursing Practice<\/span><\/b>\u00a0<\/span><\/h2>\n
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