Use Of Data Analytics On Diabetes Control And Detection Essay

The most significant difference between the regular insulin and the rapid acting insulin is the onset. The onset for rapid-acting or lispro is 10-15 minutes, and for the regular it is ½-1 hour.

“Working in a Hospital everyday is a new situation, so it keeps you on your feet.You don’t know what type of patient you may come across everyday.You interact with patients daily and give them their medication a certain time according to the medication. Other tasks involve you giving the patient's chart to the doctors. Sometimes when I go with the doctors on their rounds, i have the opportunity to counsel the patients about recommended course of

There were five CDC expectations that Ms. Jones used as a guideline for the Diabetes Recognition Program. The expectations included the following throughout the program, diabetes knowledge, session attendance during the core phase, weight loss achieved during the core phase and lastly documentation of body weights during the post-core phase. According to the results found in category 1-5 of the appendix ZZ, Ms. Jones class did meet the CDC expectations. Category 1 which was the pre and posttest including a control group of ten students averaged 44% for the pretest and posttest average 71%. The control group exceeded the CDC expectations because the average was to be at least 50%, which in the results was achieved 20% more. Category 2 which

Shared decision making should involve both health professionals and patients in discussions about their care. “While health professionals hold the expert clinical and technical knowledge, patients are experts about their own lives and treatment objectives, and also what is important to them when making decisions. (Lally, Macphail, Palmer, Blair and Thomsom, 2011).

This is a diabetes case study of Mr. Charles D., a 45-year old male who is experiencing classic symptoms of hyperglycaemia. Recently divorced and living alone in a new home, Charles has complained of recent weight loss, excessive thirst, and frequent urination. He is a busy CEO for a major technological company. This case study for Charles will educate him as to what are the causes of diabetes: explain the presenting signs and symptoms emphasize the psycho-social impact to his amended life, and instruct him in the economic impact that he and millions share.

The use of data is essential for nursing professionals to care for patients. Clinical data is used to support clinical decision making. With the introduction of technology and the electronic health record (EHR) and the amount of available data is insurmountable. It is estimated that nurses spend up to 50% of their work day recording, seeking, processing, and managing data, Access to clinical data has the potential to be very powerful for nurses, however data must be accurate, complete, reliable, and accessible to be of value (Hebda & Czar, 2013). Through the use of standard nursing language and the alignment of nursing sensitive quality measures the nursing profession will define the work of nursing through data and improved outcomes (Dykes

There are many types of data collected, such as, Demographic, financial, socioeconomic, and clinical data are collected from patients so that the healthcare providers of services to the patient are able to assess the history of whatever disease the patients is suffering from and how is to be treated. Data collection in the facility is well organized in a way that promotes shared assessment, treatment and communication. Nurses and front row staffs collects raw data’s from the patient, and. The Heath Information Manager and team are the facility are responsible in analyzing and presenting the data collected in a meaning and easily understandable way to served the specific purposes for which it was collected. Examples of such data are, patient’s name, height, weight, gender, allergies, and third party

The value of Clinical Decision Support Systems is having additional avenues monitoring patient’s data input. The Clinical Decision Support Systems are offering notifications of patient’s record data to specified department or medical personal.

A health assessment is an important part of the nursing process. The components of a comprehensive health assessment include the collection of both subjective and objective data from the patient to establish their overall level of health. It is important to develop a trusting nurse-patient relationship when interacting with all patients, especially with patients that have not had prior health care provider interactions. A patient who had never been seen by a healthcare provider may be nervous and apprehensive of what to expect in the situation. The nurse should use effective communications skills including eye contact and active listening and try to gain the trust of the patient. Systems used in the collection of data include, “active listening, restatement, reflection, elaboration, silence, focusing, clarification, and summarizing” in my verbal communication with this patient (Jensen, 2015, p. 19). The nurse needs to make clear any part of the history where there are questions.

Once data is collected it can be used by numerous health care providers and decision makers to monitor the health and needs of individuals and populations, as well as contribute to the analysis of the health system. Users including hospitals, health care practitioners, government, professional associations, researchers, media, students, and the general public. Having the correct and up-to-date coded data is critical, not only for the delivery of high-quality clinical care, but also for continuing health care, maintaining health care at an optimum level, for clinical and health service research, and planning and management of

Diabetes is a chronic illness that requires continuous medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications[ ].

Clinical decision making is a complicated process that depends on human capability to provide full attention to memorize, and create enormous amounts of data to all areas. IT systems are able to access information, arrange them, and recognize links between them. Clinicians often ‘know’ information such as a patient’s allergies, drug interaction and if that drug is on recall.

According to American Diabetes Association (2013), diabetes and diabetes management has caused a burden to be placed on the United States economic status do with indirect and direct cost associated with Diabetes. Consequently, it is essential that health care providers stay up to date on new research and polices regarding this disease so that they can more effectively educate their patients on ways to manage and prevent/delay the disease. This paper will discuses systems models with organization, improvement goals stakeholders expectations, quality oversights, sources for comparative performance data, and improvement tools that can be used to help reach the obtainable goal of translating research and evidence base practice for prevention of diabetes into clinical practice.

Several nationwide programs and incentives were administered in the last couple of decades to promote awareness of diabetes and hopefully help prevent millions of Americans from developing diabetes. Health Agencies, such as World Health Organization (WHO) and Center of Disease Control and Prevention (CDC), have developed objectives to tackle diabetes. Some of these objectives include conducting surveillance and obtaining diabetes data to identify trends in the population, spreading awareness about the condition, and developing programs that will enhance diabetes care and ensure the longevity of the patients. Various programs have been developed but while some excel, others fail to benefit the lives of the patient.

Given that diabetes is ranked as the 7th leading cause of death in the United States (U.S.) and given that total diabetes costs were over $245B in the US in 2012 (American Diabetes Association, 2013) Sanofi is investing heavily into analytics to understand the disease