Name
Capella University
FPX6414
Instructor’s Name
October 04, 2024
Tool Kit for Bioinformatics
Since the appearance of COVID-19, many people faced insecurity of their health especially those who visited the hospitals during the COVID-19 outbreak and feared getting infected with the virus in the hospital setting (Wu et al., 2020). Some measures that are related to the COVID-19 infection involve early assessment and management, and such measures may enhance people’s sense of safety. This aim is possible through the use of Health Information Technology, including the Clinical Decision Support System (CDSS) and Best Practice Advisory (BPA) alerts. Consequently, this paper will offer a tool kit for CDSS and BPA alert implementation.
Evidence-Based Policy
This pandemic has affected healthcare workers, through increased workload, and has made the cost of healthcare tremendously high. Therefore, patients, care providers, as well as health systems would have substantial concerns due to insufficiency of medical practitioners, and medical equipment if the spread of this illness is not averted and addressed as early as possible. Moulaei (2022) claims that to treat and prevent the transmission of the disease, healthcare providers must focus on the first symptoms of COVID-19. They claimed that enhancing the utilization of the CDS system would allow physicians to arrive at sound decisions on patients’ overdiagnosis, treatment, and follow-up quickly. Consequently, physicians are allowed to make the correct diagnosis in less time and contain the spread.
In Notification, messaging, report-patient, and trial tools interfaces, the CDS system provides knowledge and information in addition to advice to the Patients, and Health Care Staff (Moulaei, 2022). Advanced technology specifically in health has made it easy to deliver quality and time-bound care in the medical field. All healthcare providers have to implement and meaningfully use health IT as per the requirements of the Affordable Care Act to boost the quality of care, enhance outcomes, and reduce costs. In the words of the author, when it comes to the learning health system ready to navigate the growing healthcare landscape, one option is not enough; a well-established electronic health record with clinical decision support ( Peters et al., 2020). Clinicians at the point of care can benefit from a broad array of embedded clinical decision-support tools within health information technology such as EHRs, which facilitate decision-making by providing information. Many clinicians may use the preferred working CDS tool inherent in the EHR known as the Best Practice Advisory (BPA) alert to enhance patient benefits and the effectiveness of the healthcare system.
Guidelines
Simply having policies is insufficient; it is required to work on those policies and transform them into practice to attain the goal. It is an important factor to obtain support from the distinct stakeholders to successfully implement the plans. Defining and maintaining the communicable framework of referring ideas, principles, and measures at the interface of the whole healthcare workforce is crucial (Kitson et al., 2021). Based on the case, the healthcare institution must biweekly meet physicians and nurses hospital administrators, nurse informatics, and information technology specialists to design an effective CDS system and BPA alerts. Every week the team will sit down with customers to share ideas on how they can enhance the technology used by adding components that ease its operation, and at the same time, minimize errors that may arise along the process. In turn, the weekly meetings will also serve training purposes concerning the appropriate and rational utilization of technology.
Some lights on planning for the implementation may be created when meetings and training sessions have taken place with the development team sitting down and discussing the objectives of the project (Bartmess et al., 2021). When the strategy is ready, the development team will sit with a system vendor to determine how the technology could be implemented to address the goals. Business people who develop these systems will release a first version or a basic version of the system to be tried out by healthcare organizations and get their feedback. Therefore it will help the vendors to know the demands of healthcare teams and may take some alteration to it. The use of an effective CDS appropriate for the features of the patients and the clinicians is suggested as necessary to optimize their health.
Practical Recommendations
Stakeholders Education
For the technology to be deployed effectively, the management should gain support from every bona fide person. Once the healthcare organization understands what it wants to achieve with the help of innovative technology, it is time to educate its workers on how to get the most out of that technological tool (Heinen et al., 2019). Weekly training sessions, seminars, or webinars may be conducted at healthcare organizations with support from information technology teams to teach professionals about the efficient applications and use of technology, engage with staff concerns, and offer solutions.
Classroom-based team training intervention and simulation have been found several times to have benefits when implemented in the classroom setting (Wang et al., 2023). The mode where professionals are tested on their technical skills as well as the gaps in the training of healthcare technology may involve simulation or traditional classroom training.
Monitor Data to Evaluate Outcomes
Once the CDS system and Best practice advisory (BPA) alert are successfully designed and integrated, the effectiveness of the system in improving patient outcomes for COVID-19 can be compared to the control group (McCauley et al., 2020). The CDS system can improve health because it helps in the identification of diseases and timely treatment, thereby preventing transmission of the disease, and offers directed advice, and information in the form of alerts to the patient and the clinician. There will be the enhancement of health, reduction of health costs, increased security among patients, and overall gain among the participating patients. This may lead to reduced costs for healthcare organizations..
Study demonstrated that applying the CDS system helped to identify patients with COVID-19 quickly. The authors argue that infectious disease-19 (COVID-19) has caused huge devastation and acute respiratory failure; and has increased patient flow in ED at a time when diagnostic labs are in short supply (Laugaland et al., 2023). Supporting the so-called triage patients as well as supplying the required information to those requiring it the most, the creation of clinical decision support systems for the immediate clinical diagnosis of COVID-19 has become one of the tools used in this pandemic.
A Specific Example of Bioinformatics
By using a clinical decision support tool that assists in clinical evaluation, clinicians could potentially be spending a great deal of time examining patients with COVID-19 presenting symptoms. Thus, to avoid spreading the COVID-19 virus in a healthcare facility or an emergency department a patient exhibiting COVID symptoms should be isolated (Alberti et al., 2023). On the flip side, unnecessary loneliness prolongs treatment, occupies spaces that could be occupied by other patients, and wastes protective gear. Once the Checklist is generated, and the doctor has answered a few questions regarding the patient’s risk factors and complaints, and imaging data, the CDS system guides the practitioners through a full set of algorithmic COVID-19 diagnostic recommendations, based on the most recent guidelines.
CDS integration with Best Practice Advisory Alerts has the following benefits. (Alberti et al., 2023) proves that the use of CDS systems increases the safety of clients and even medical personnel. It is rapid and accurate for identifying the viruses and rules out the ‘normal’ patient sample that might endanger other patients’ and staff members’ lives. The CDS system has two benefits in terms of diagnosis and quarantine: time-saving.
| Process | Before the implementation of the CDS system | After the implementation of the CDS system |
| Time to make an accurate diagnosis of COVID-19 | 1-2 days | 5-6 hours |
| Healthcare costs | $9500 | $2000 |
| Unidentified patients in quarantine | 10-20 patients | 5 patients |
| False Negative Results | 7-8 false negative results | 3-4 false negative results |
NURS FPX 6414 Assessment 3 Conclusion
Some of the subjects of focus in this study included the administration and management of COVID-19, and other areas that could be used to evaluate the possibility of employing CDS systems. Since the CDS system can quickly identify a COVID-19 patient, it helps doctors and other care providers slow its transmission (Opsahl et al., 2019). This minimizes the incidence of irreversible complications as well as many deaths, at the same time it minimizes added expenses for unessential treatments and diagnostic tests, shortens the amount of time that might be spent on diagnostic processes, and increases clinical effectiveness and patient-related results.
NURS FPX 6414 Assessment 3 References
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Bartmess, M., Myers, C. R., & Thomas, S. P. (2021). Nurse staffing legislation: Empirical evidence and policy analysis. Nursing Forum, 56(3), 660–675. https://doi.org/10.1111/nuf.12594
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McCauley, L. A., Broome, M. E., Frazier, L., Hayes, R., Kurth, A., Musil, C. M., Norman, L. D., Rideout, K. H., & Villarruel, A. M. (2020). Doctor of nursing practice (DNP) degree in the United States: Reflecting, readjusting, and getting back on track. Nursing outlook, 68(4), 494–503. https://doi.org/10.1016/j.outlook.2020.03.008
Moulaei, K. (2022). Diagnosing, managing, and controlling COVID-19 using Clinical Decision Support systems: A study to introduce CDSS applications. Journal of Biomedical Physics and Engineering, 12(02). https://doi.org/10.31661/jbpe.v0i0.2105-1336
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Peters, M. D. J., Marnie, C., Tricco, A. C., Pollock, D., Munn, Z., Alexander, L., McInerney, P., Godfrey, C. M., & Khalil, H. (2020). Updated methodological guidance for the conduct of scoping reviews. JBI Evidence Synthesis, 18(10), 2119–2126. https://doi.org/10.11124/JBIES-20-00167
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