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Readiness for System Change
Depression is one of the main debilitating health effects that affects the elderly. In fact, the number of deaths related to depression has been on the increase, especially among the elderly. Therefore, it is appropriate for health officers to come up with policies on prognosis, diagnosis, as well as for treating depression, especially among the elderly. In the United States 2010 census, it was found that among the 40.3 million adults who were aged above 65 years, between 5 and 10 percent of them had depression. Worse still, of those who were depressed, 10-20 percent of them had chronic medical conditions. The number of those depressed is estimated to rise to 20.2% in 2050 (Aziz & Steffens, 2013). With this high numbers of depression among the elderly, there is need to implement appropriate medical methods of detecting and treating depression. Among the elderly, less than 20% of the individuals who are diagnosed with depression qualify for diagnostic criteria (Rice & Thombs, 2016). Therefore, the ability to identify the risk early on its onset is crucial. Yesavage et al. posits that GDS has a 95% sensitivity and 100% specificity in identifying depression among the elderly (Chiang, Green, & Cox, 2009).
The causes of depression are many, stretching from economic, social, and even an individual’s health condition. Doody and Doody, (2012), submit that an IOWA model allows health practitioners to focus on the causes of depression. Melnyk and Fineot-Overholt, (2011), demonstrate the effectiveness of IOWA in the design of programs and in the evaluation of depression. Nonetheless, despite the transformative ability caused by using evidence-based practices, it is essential to integrate these theories with the healthcare system in order for them to be more effective and efficient in the treatment of patients.
The Dorothy Johnson’s behavioral model, which aims at restoring behavioral system balance in the biological and behavioral system, will be used in influencing change (Johnson, 1980). The main components of Johnson’s behavioral system are health, environment, nursing, system, and man. This model is able to interact with the psychological, social, biological, and physiological aspects of a patient. Since this model is able to integrate the biological and behavioral systems of an individual, it is effective in the diagnosis and treatment of depression (Rycroft-Malone & Bucknall, 2011).
The adequate integration of this theoretical framework in the provision of healthcare with practical demonstrations will lead to an effective delivery of health care service. More specifically, methods such early screening of elderly individuals will result in quicker detection time, which will lead to a decrease in health care cost (Burns & Groove, 2010). Similarly, the use of evidence-based methods, such as IOWA in the examination of high-risk individuals such as those suffering from illnesses, bereavement, those with a familial history of depression, as well as those with Parkinson’s disease, dementia, and hypothyroidism may result in early detection (Jones, 2009). Therefore, the integration of EBP with health care will improve the treatment of depressed patients since it will consider both behavioral and biological aspects of a patient.
To conclude, the integration of EBP methods, such as IOWA will result in early detection, guided treatment, quick recovery, as well as affordable health care for the patient. The use of GDS will result in high detection rates of patients with depression since this method considers both the behavioral and biological aspects of a patient. Therefore, all stakeholders in the health care system, from nurses, the policy makers such as the government and health unions, as well as patients should be active in ensuring that they use a guided health care system.
References
Aziz, R., & Steffens, D. (2013). What are The Causes of Late Depression? Psychiatr ClinNorth AM. 36(4); 497-516.
Chiang, K., Green, K., & Cox, E. (2009). Rasch analysis of the geriatric depression scale-short form. The Gerontologist, 49(2), 262-275.
Doody, C. M., & Doody, O. (2011). Introducing evidence into nursing practice: Using the IOWA model. New York, NY: John Wiley & Sons.
Johnson, D. E. (1980). The behavioral system model for nursing. In J. P. Riehl & C. Roy (Eds.), Conceptual models for nursing practice (2nd ed., pp. 207-216). New York, NY: Appleton-Century-Crofts.
Jones M (2009) Using screening tools to identify the risk or presence of depression in older people. Nursing Times, 105 (1), 49-50
Melnyk, B. M., & Fineout-Overholt, E. (Eds.). (2011). Evidence-based practice in nursing & healthcare: A guide to best practice. New York, NY: Lippincott Williams & Wilkins.
Rice, D., & Thombs, B. (2016). Risk of bias from inclusion of currently diagnosed or treated patients in studies of depression screening tool accuracy: A cross-sectional analysis of recently published primary studies and meta-analyses. PLoS ONE, 11(2), 1-9.
Rycroft-Malone, J., & Bucknall, T. (Eds.). (2011). Models and frameworks for implementing evidence-based practice: Linking evidence to action (Vol. 2). New York, NY: John Wiley & Sons.
Yesavage, J., Brink, T., Lum, O., Huang, V., et al. (1983) Development and validation a geriatric depression screening scale. A preliminary report. Journal of PsychiatryResearch, 17, 37-39.