Nothing is more concerning in today’s society than the number of fatalities that occur daily due to so-called lifestyle disorders. Every day, several new patients are diagnosed where many of them are uninformed that they suffer from these silent killer ailments. Diabetic, hypertensive, and overweight are among the most common diseases (Ku et al., 2019). As per the Centers for Disease Control and Prevention (2021), one out of each four Americans has hypertensive or is diabetic. These data are concerning, and they have ranked the two criteria among the top ten main factors associated with mortality throughout the United States. Diabetes is a leading cause and linked to crucial conditions like stroke, kidney disease, and heart attack across the planet (Centers for Disease Control and Prevention, 2020). The above scenario necessitates more efforts in combating this scourge of lifestyle illness, including increased public awareness, effective follow-up, and better health treatment to minimize the number of instances of diagnosis and fatalities connected with the condition via good information and data handling (Sousa et al., 2019). The article suggests a nursing informatics initiative that examines the technological use in campaigning to enhance patient-care effectiveness in health institutions across the United States.
Project Description
The recommended project will be an alert system in health facilities. The project will give alert capabilities to the participating nurses for them to recognize or obtain details on clinic follow-ups, notably for clients who have formerly been afflicted with conditions such as hypertension, obesity, or even diabetes. Upon the client’s first or successive appointment to a healthcare facility and following the clinical assessment in triage, the patient gets a regular checkup, including the three critical exams of diabetic, hypertensive, and body mass index. If the diagnosis is made with one or more of the problems, the physician would access the alert system in clinics and investigate using the client’s medical code.
Suppose the client’s information is not discovered. In that case, it signifies that the client is either attending the institution for the first moment or that they have not been identified with either of the illnesses in previous visits. The physician would enter the checkup findings and propose a follow-up doctor evaluation and a prospective clinic appointment for the new client (Otokiti, 2019). The alert system will inform the clinician throughout the client session, and when the practitioner proposes a clinic or psychotherapy session schedule, it will choose a specific day and time predicated on the physician’s accessibility as well as the extent of medical necessity. The practitioner ought to be capable of obtaining updates on prior clinic follow-ups, whether the specific client previously showed regular visits for treatment, and therapy advancement for a typical individual who has in the past been recognized. It is an essential advantage of implementing the alert system in a clinic as the majority of diagnosed clients’ conditions deteriorate owing to a challenge to follow, particularly with the physician’s advice. With the support of the proposed alert system, the healthcare practitioners may illustrate the client’s growth, as all facility appointments or treatment sessions are registered and improved inside the system.
Stakeholders Influence by the Proposed Project
The clinic alert system will have an influence on a variety of stakeholders, including patients, caregivers, physicians, therapists, consultants, the IT department team, and nurse informaticists. The primary goal of implementing an alert system is to determine the pattern of the three indicated lifestyle disorders via diagnostic, clinical, and therapeutic meetings, follow-up, and medication progress (Shafqat et al., 2020). Many clients diagnosed with obesity, diabetes, or hypertension would not receive sufficient follow-up care, mainly if their initial appointment were for a separate condition away from the tree. This circumstance has resulted in a rise in the prevalence of these conditions and other opportunist ailments like heart attack, kidney failure, and lower loss of limbs, all of which are linked to uncontrolled high blood pressure, diabetes, or obesity. This problem is intended to be resolved by the alert system.
Patient-Care Efficiencies or Patient Outcome(S) to be Improved
The clinical alert system is intended to make follow-up notably from the baseline examination of a patient who has undergone diagnosis and guarantees that they stick to the prescribed activities and medication path whenever feasible to improve patient care efficiency. Guidance would also be provided when it comes to obtaining required medications and therapy sessions for people who would be in demand. The system would make the follow-up procedure available to the nurses, and different informaticists inside the systems would be notified on specific activities to perform along the client’s care path (Cook et al., 2015). Besides, it would be simple to calculate the rate of evaluation across individuals over a designated period, like per annum, quarterly, or monthly (Otokiti, 2019). During follow-up treatment, the client would get more information, try to take care of themselves in regards to nutrition and fitness, and adhere to the treatment. It will result in total positive improvement and a change in the status of the assessed sufferers.
Required Technologies to Execute the Project Proposal
To interface with the remainder of the healthcare facilities system, the proposed alert system would require a specific server. The existing machines would be utilized in the same system but would require an update to the most recent operating system. The clinical alert system would be interoperable with both OS and windows in terms of compatibility. The IT professionals would conduct some training to acquaint the different stakeholders with the system’s capabilities and the numerous activities that would be necessary throughout each phase.
The Project Team and Ways to Integrate the Nurse Informaticist
Nurse management, nurse informaticists, Information Technology experts, systems engineers, a psychiatrist, counselor, and nutritional consultant are all expected to be part of the project team. The goal of having all the above team members on the panel is mainly to bring together overall aspects that connect the various phases and domains, starting with the client visit and ending with the final step of treatment procedures. The delegates were carefully selected from sectors dealing with the three primary conditions, including obesity, diabetes, and hypertension. The nurse informaticist is critical as they are expected to remain in control of gathering and interpreting complex patient data and disseminating it to all stakeholders involved in the proposed alert system (McGonigle & Mastrian, 2021). Further, the nurse informaticist is vital in the project since they are required to initiate system upgrades and modifications in partnership with information technology department staff to provide better services.
Conclusion
Clinicians are straining to deliver enough client follow-up treatment as patient “no-show” levels are expected to rise. Overlooked consultations and clients’ inability to follow up generate liability issues for their doctors. By enhancing treatment involvement, information technology that supports client self-management has the capacity to build common accountability for care experiences. There seems to be increased interest in giving patients with notifications and alerts to promote medical self-management. Alerts and Notifications are beneficial in several approaches; they may be utilized to contact clients beyond the conventional clinical environments, they could be tailored, and the effectiveness of automated alerts delivered to clients has a low age restriction. The usage and transmission of patient alerts and notifications will alter as technology and patients’ abilities advance.
References
Centers for Disease Control and Prevention. (2020, August 28). National diabetes statistics report, 2020. https://www.cdc.gov/diabetes/data/statistics-report/index.html
Centers for Disease Control and Prevention. (2021, September 27). Facts about hypertension.https://www.cdc.gov/bloodpressure/facts.htm
Cook, D. A., Enders, F., Caraballo, P. J., Nishimura, R. A., & Lloyd, F. J. (2015). An automated clinical alert system for newly-diagnosed atrial fibrillation. PLoS One, 10(4), e0122153. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388495/
Ku, E., Sarnak, M. J., Toto, R., McCulloch, C. E., Lin, F., Smogorzewski, M., & Hsu, C. Y. (2019). Effect of blood pressure control on long‐term risk of end‐stage renal disease and death among subgroups of patients with chronic kidney disease. Journal of the American Heart Association, 8(16), e012749. https://doi.org/10.1161/JAHA.119.012749
McGonigle, D., & Mastrian, K. (2021). Nursing informatics and the foundation of knowledge. Jones & Bartlett Publishers. https://jats.com.jo/sites/default/files/webform/pdf-nursing-informatics-and-the-foundation-of-knowledge-dee-mcgonigle-kathleen-mastrian-pdf-download-free-book-aedf010.pdf
Otokiti, A. (2019). Using informatics to improve healthcare quality. International Journal of Health Care Quality Assurance. https://doi.org/10.1108/IJHCQA-03-2018-0062
Shafqat, S., Kishwer, S., Rasool, R. U., Qadir, J., Amjad, T., & Ahmad, H. F. (2020). Big data analytics enhanced healthcare systems: a review. The Journal of Supercomputing, 76(3), 1754-1799. https://doi.org/10.1007/s11227-017-2222-4
Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-making based on big data analytics for people management in healthcare organizations. Journal of Medical Systems, 43(9), 1-10. https://doi.org/10.1007/s10916-019-1419-x
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