Impact of Clinical Systems and efficiencies in nursing practice Paper
Impact of Clinical Systems and efficiencies in nursing practice Paper
Introduction
Clinical Systems
Clinical systems are the information systems designed for use in a healthcare setting. These systems record clinical information such as patient health records, rapidly changing medical evidence base, and provider orders. In nursing care, clinical systems help to improve the systems of care in collaboration with families and other care providers. Examples of health information systems in healthcare are electronic medical records, practice management software, master patient index, patient portals, remote patient monitoring, and clinical decision support. They collect, store, manipulate, and make available clinical information to the healthcare delivery process. Impact of Clinical Systems and efficiencies in nursing practice Paper
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This article describes clinical systems, their outcome, efficiency, and lessons learned in form of annotated bibliography. The selected clinical system is an electronic medication administration record (eMAR). eMAR is a technology that automatically documents medicine administration in the electronic health record (EHR). It allows professionals and patients to view the exact medication used, safeguards and backs up patients’ data. Its creation has led to the provision of accurate results, reduced medication errors, and time used in documentation. eMAR is effective in managing patients with chronic illnesses such as diabetes mellitus, hypertension, asthma, and COPD because it alerts the professional when the medication is due. It tracks patients’ progress through reports of the previous visits and improves the efficiency of the drug administration.
Lancaster, K., Abuzour, A., Khaira, M., Mathers, A., Chan, A., Bui, V., … & Dolovich, L. (2018). The use and effects of electronic health tools for patient self-monitoring and reporting of outcomes following medication use: a systematic review. Journal of medical Internet research, 20(12), e294. doi: 10.2196/jmir.9284
This article describes the use of electronic health tools for patient self-monitoring and reporting of outcomes following medication use. Self-monitoring is the art of routinely following described instructions by a care provider watching out for the danger signs. Patients of self-monitoring and reporting systems are usually suffering from chronic illnesses such as diabetes mellitus, hypertension, or chronic obstructive pulmonary diseases. Chronic diseases are usually in a stable state. Therefore, they have a set of instructions that helps them monitor basic vitals like random blood sugar, blood pressure, and oxygen saturation. They use electronic health tools to monitor their daily vitals, any complaints, the time they took their medication, and the side effects they experience. The care provider monitors the patient’s illnesses at the comfort of their home. They change the medication and send new instructions to the patient through the electronic health record tool. The patient may only show up at the hospital for an annual checkup. Electronic health tools for patient self-monitoring and reporting outcomes following medication helps save on time the patient use to travel to the hospital and wait on their turn. They store patients’ health information since the day they started their treatment. Impact of Clinical Systems and efficiencies in nursing practice Paper
In this article, randomized controlled studies on patients with chronic illnesses use electronic health tools for self-monitoring and reporting outcomes. The study shows positive medication changes, improved symptoms, drug adherence, improved self-efficiency, and improved self-management of chronic diseases. Therefore, electronic health tools help the patient improve the quality of life, patient satisfaction, and health service utilization.
Seidling, H. M., Mahler, C., Strauß, B., Weis, A., Stützle, M., Krisam, J., … & INFOPAT P4/P5 Study Team. (2020). An Electronic Medication Module to Improve Health Literacy in Patients With Type 2 Diabetes Mellitus: Pilot Randomized Controlled Trial. JMIR formative research, 4(4), e13746. doi: 10.2196/13746
This article describes the use of eMAR in improving health literacy among diabetic patients. The author reports that diabetes mellitus is a chronic illness that depends on a long-life intake of drugs that needs continuous unremitting efforts to self-manage the medication process. Therefore, the patient has to actively take medicine, fill, and pick up prescriptions, understand the drug regimen, monitor adverse effects, and sustain it over the long term. Electronic medication modules have improved patient literacy in four dimensions; access to relevant health information, understanding information to health, applying and using the information to health, and appraisal and process information. Health literacy aims at supporting patients to achieve their roles in the management of diabetes.
A research study through random controlled trials among patients with diabetes type 2. There were two groups of patients; one group had access to electronic medication information and a medication schedule. The other group had a medication brochure. There was an increased dropout because of underpowered participants. However, the intervention is effective in managing patients with diabetes type 2 if implemented amongst the participants.
Bertsimas, D., Kallus, N., Weinstein, A. M., & Zhuo, Y. D. (2017). Personalized diabetes management using electronic medical records. Diabetes care, 40(2), 210-217. https://doi.org/10.2337/dc16-0826
This article describes the impact of electronic medication administration records in personalized diabetes. The author describes that diabetes mellitus type 2 treatments are through lifestyle modifications like healthy eating, physical exercise, oral medication, or insulin administration. Through clinical evidence-based research, glycemic control is the main achievement during the management of diabetic patients. The choice of pharmacological therapy to maximize the effectiveness is not yet understood. Therefore, electronic medication administration records help in monitoring the effectiveness of the medicine administered through its alerts and reports.
A research study that determined the outcome of diabetes type 2 patients using eMAR was conducted. The participants were patients with diabetes type 2, had at least three recorded HbA1c laboratory measurements, had a prescription of at least one blood glucose regulation agent, and are present in the system for an observation period of 100 days. The patient’s data was recorded in the eMAR during every hospital visit. From the study, the eMAR personalized each patient’s treatment plan based on their medical history records which improve significantly on the standard of care. eMAR is effective in managing diabetes type 2 because it has shown improved outcomes. Impact of Clinical Systems and efficiencies in nursing practice Paper
Lee, C. S., Tan, J. H. M., Sankari, U., Koh, Y. L. E., & Tan, N. C. (2017). Assessing oral medication adherence among patients with type 2 diabetes mellitus treated with polytherapy in a developed Asian community: a cross-sectional study. BMJ Open, 7(9), e016317. http://dx.doi.org/10.1136/bmjopen-2017-016317
This article describes the medication adherence among patients with diabetes mellitus on oral polytherapy. The author reports that the disease burden of diabetes mellitus type 2 is on the rise due to optimal glycemic control leading to vascular complications. The use of electronic medication records has a direct impact on glycemic control and clinical impact. Other factors associated with medication adherence are the interaction between patients, physicians, healthcare teams, and medication factors.
A research study was done at a primary care outpatient clinic in Singapore involving adult patients with diabetes type two. The study design was data analysis from the cross-sectional survey and electronic medical records. The study aimed to determine medication adherence to oral therapy. The total participants were 382c patients with a slight female dominance. Younger patients doing self-administration of medicine had poor adherence and glycemic control while those who used electronic medication administration records had a good adherence and outcomes.
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Ruan, Y., Bellot, A., Moysova, Z., Tan, G. D., Lumb, A., Davies, J., … & Rea, R. (2020). Predicting the risk of inpatient hypoglycemia with machine learning using electronic health records. Diabetes care, 43(7), 1504-1511. https://doi.org/10.2337/dc19-1743
This article describes electronic health records in predicting the risks of impatient hypoglycemia. Hypoglycemia is a common complication of diabetes characterized by inappropriately low glucose levels. Hypoglycemia can cause permanent neurologic damage if not treated promptly. With the use of electronic medical devices in the United States, hypoglycemia is very common in inpatients with a severe incidence of 7%. The strategies that reduce the risk of hypoglycemia at the inpatient are analyzing patients’ historical data and developing a prediction tool by the use of the electronic medical device.
A research was conducted from a hospital electronic medical record. It showed blood glucose levels, administering medication, and demographics. The data analyzed that the causes of hypoglycemia were dependent on the medicine used, procedures performed, weight, and type of diabetes. Hence, the use of electronic medical devices is accurate in managing critical health conditions. Impact of Clinical Systems and efficiencies in nursing practice Paper
Conclusion
A clinical system is an information system that networks with many computers designed to enhance communication in a hospital or an emergency department. They help to improve communication among healthcare professionals, help in making the right clinical decisions, encourage quality improvement, allow for better clinical research and make it easier for patients to have diagnostic tests when necessary. Clinical systems are also used to monitor extremely sick patients. Diabetes mellitus is a chronic illness that needs regular monitoring of blood sugar levels to prevent its fatal complications.
Review the resources and reflect on the impact of clinical systems on outcomes and efficiencies within the context of nursing practice and healthcare delivery Conduct a search for recent (within the last 5 years ) research focused on the application of clinical systems. The research should provide evidence to support the use of one type of clinical systems to improve outcome and/ or efficiencies in a 4-5 page paper Synthesize the peer reviewed research you reviewed . format as annotated bibliography be sure to address the following Identify the 4 peer -reviewed research article you reviewed citing each in APA format include an introduction explaining the purpose of the paper Summarize each study explaining the improvement to outcomes, efficiencies and lessons learned from the application of the clinical systems each peer reviewed article described . Be specific and provide examples in your conclusion synthesize the findings from the 4 peer reviewed research article use APA format and include a title page Impact of Clinical Systems and efficiencies in nursing practice Paper
References
Bertsimas, D., Kallus, N., Weinstein, A. M., & Zhuo, Y. D. (2017). Personalized diabetes management using electronic medical records. Diabetes care, 40(2), 210-217. https://doi.org/10.2337/dc16-0826
Lancaster, K., Abuzour, A., Khaira, M., Mathers, A., Chan, A., Bui, V., … & Dolovich, L. (2018). The use and effects of electronic health tools for patient self-monitoring and reporting of outcomes following medication use: a systematic review. Journal of medical Internet research, 20(12), e294. doi: 10.2196/jmir.9284
Lee, C. S., Tan, J. H. M., Sankari, U., Koh, Y. L. E., & Tan, N. C. (2017). Assessing oral medication adherence among patients with type 2 diabetes mellitus treated with polytherapy in a developed Asian community: a cross-sectional study. BMJ Open, 7(9), e016317. http://dx.doi.org/10.1136/bmjopen-2017-016317
Ruan, Y., Bellot, A., Moysova, Z., Tan, G. D., Lumb, A., Davies, J., … & Rea, R. (2020). Predicting the risk of inpatient hypoglycemia with machine learning using electronic health records. Diabetes care, 43(7), 1504-1511. https://doi.org/10.2337/dc19-1743
Seidling, H. M., Mahler, C., Strauß, B., Weis, A., Stützle, M., Krisam, J., … & INFOPAT P4/P5 Study Team. (2020). An Electronic Medication Module to Improve Health Literacy in Patients With Type 2 Diabetes Mellitus: Pilot Randomized Controlled Trial. JMIR formative research, 4(4), e13746. doi: 10.2196/13746 Impact of Clinical Systems and efficiencies in nursing practice Paper
