Standardized Care Map Type 2 Diabetes and ObesityType 2 DiabetesA 47

Standardized Care Map: Type 2 Diabetes and ObesityType 2 DiabetesA 47 year old male patient presents to the clinic with a hyperglycemia diagnosis. The patient’s HbA1c level is 10.5 mm/L on fasting. The patient is on an insulin ggt to help reduce insulin resistance. The goal is to reduce blood sugar levels to 7.8mm/L or lower. The patient shows alertness. However, the patient’s dietary habits are poor since the patient consumes all food types with no portion control. Furthermore, the patient rarely monitors his blood sugar levels at home. Upon an evaluation, it is evident that the patient’s knowledge about diabetes is scanty and is not aware of how to take blood sugar measurements and interpret the findings (Cárdenas-Valladolid, Salinero-Fort, Gómez-Campelo & López-Andrés, 2015). In addition, knowledge about dietary habits and portion control is lacking. Furthermore the patient does not understand the repercussions of uncontrolled blood sugar. After patient education on diabetes and the need to adhere to behavior change the patient is willing to adjust in order to control his blood sugar. Nursing DiagnosisRisk for uncontrolled blood sugar related to ineffective health maintenance and lack of diabetes type 2 education as evidenced by high blood sugar and knowledge deficiency about diabetes control.Subjective DataThe patient asserts that he does not understand about type 2 diabetes and how to monitor blood sugar levels. He shows unawareness of the consequences of uncontrolled blood sugar on his health. Additionally, his dietary habits are poor and lacking in food consumption regimens, patterns discretion consistent with a type 2 diabetes patient. Objective data 47 year old male patient presents to the clinic with an actual diagnosis of hyperglycemia of 10.5mm/L. The patient is on an insulin ggt per protocol for blood sugar lowering. The patient remains alert but demonstrates lack of education on blood sugar control (Cárdenas-Valladolid et al., 2015). Besides, the patient is unaware of dietary behavior and how they impact blood sugar levels. He lacks blood sugar monitoring knowledge. Nursing OutcomesThe patient will know when how to monitor blood sugar and how to interpret findings. He will be able to take insulin medication and adhere to regimes, as well as develop a diet plan to meet unique diabetes needs. The patient will be provided with testing materials such as glucometers, syringes, strips and a lancet and demonstrate how to correctly dispose of sensitive materials such as syringes. InterventionsThe Patient requires education on diet and meal planning, blood sugar monitoring, proper use of blood sugar checking items. Patient education will also focus on administration of self-injections. The patient will be referred to a dietician for further education on dietary behavior. The nurse will educate the patient how to mix NPH and regular insulin and the need to embark on an exercise regimen of 150 minutes each week to promote blood sugar control. Data Element SetsNursing intervention Classification (NIC)Nursing Interventions Classifications is a data set element approved by the American Nurses’ Association that delineates the activities performed by nurses during the planning stage of the nursing process in order to develop a standardized care plan Nursing Outcome Classification (NOC)Nursing outcomes classification describes the outcomes that result from the nursing intervention or the nursing sensitive outcomes. It also examines nursing care’s impact as an element of the nursing process. ObesityA 34 year old female presents to the clinic with an obesity diagnosis. the patient has a BMI of 32, lives a sedentary lifestyle and over eats high fat meals. The patient does not have other health conditions but explains that she has problems with stress related and uncontrolled over consumption of food. Nursing diagnosisRisk for imbalanced nutrition related to overconsumption of calories as evidenced by sedentary lifestyle psychosocial problems and obesity.Objective Data34 year old female patient presents to the clinic with an obesity diagnosis. Has a BMI of 32 and lacks meal planning and understanding of the risks for calorie overconsumption. The patient explains that she has psychosocial problems that result in overeating. Subjective Data• Patient says she has uncontrolled eating• Lack of physical activity• Has no obesity comorbidity. Outcomes• The patient should be able t identify appropriate behavior, problems of overeating, and excessive weight gain.• Demonstrate alterations in feeding patterns and engagement in physical exercise.• Weight loss to achieve a BMI of 25 or lower Nursing InterventionsEducate the patient on the need to enroll for a physical exercise program for weight loss and to help relieve stress symptoms. Additionally, patient counseling will to help cope with stress and effects of a poor body image. Educate the patient on how to prepare a balanced meal plan for adequate nutrition. Nursing Minimum Data Set (NMDS)This terminology is applicable to obesity describes a classification system that facilitates standardized data collection. The data collected should reveal a correct description of the nursing process employed during nursing care delivery (Tastan, Linch, Keenan, Stifter, McKinney, Fahey,… & Willkie, 2014). It facilitates data analysis and comparison across practice settings geographical regions, time and populations settingsNursing Outcome Classification (NOC)Nursing outcomes classification describes the outcomes that result from the nursing intervention or the nursing sensitive outcomes. In addition, it examines nursing care’s impact as an element of the nursing process. ReflectionA nursing diagnosis is a vital component of the nursing process. I formulate it based on data obtained from a patient’s assessment. It is critical to personal nursing practice because it seeks to incorporate a patient’s involvement into the nursing process to advance positive patient outcomes. The North American Nursing Diagnosis Association-International (NANDA-I) defines, disburses, and integrates standardized nursing diagnoses. In addition, ANA approved data element sets are vital for my nursing practice since they provide standardized nomenclature and taxonomies that ensure nursing diagnoses are backed with evidence (Tastan et al., 2014). In my practice, I frequently use data set elements to convey knowledge and standardized nursing care language. For instance, I frequently apply the Logical Observation Identifiers Names and Codes to identify laboratory and clinical test results in regard to aspects such as vital signs, EKG, electrocardiogram, and urologic imaging. I apply them to delineate laboratory and clinical test results during storage in computer-based databases and transmission in electronic messages ReferencesCárdenas-Valladolid, J., Salinero-Fort, M. A., Gómez-Campelo, P., & López-Andrés, A. (2015). Standardized nursing care plans in patients with type 2 diabetes mellitus: Are they effective in the long-term? Atención Primaria, 47(3), 186-189. doi:10.1016/j.aprim.2014.05.014Tastan, S., Linch, G. C. F., Keenan, G. M., Stifter, J., McKinney, D., Fahey, L., . . . Wilkie, D. J. (2014). Evidence for the existing American Nurses Association-recognized standardized nursing terminologies: A systematic review. International Journal of Nursing Studies, 51(8), 1160-1170. doi:10.1016/j.ijnurstu.2013.12.004