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Data collection is the ongoing systematic process of gathering, analyzing and interpreting various types of information from various sources. In general, data collection is done for research purposes in order to understand the full picture of an area of interest and to build a foundation for decision-making (Sakovich, N., n.d.). In the healthcare setting, data collection is imperative to the diagnosis and treatment of those who have fallen ill, as well as the prevention of illness. Monitoring of patient conditions and data collection allows for the prevention of deteriorating health, and facilitates improved health outcomes. Also, data collection “may lead to annual reductions of over $300 billion in the US health-care sector; most of that would be in the form of decreased health-care expenditure” (Zeng, X., Liu, J., Ma, L. & Fu, P., 2018).
One scenario that would not only require, but also benefit from the collection and application of data is when attempting to diagnose a patient that has kidney failure. Obtaining a serum creatinine and assessing the outcome of the test is crucial to establishing whether a patient has adequate renal functioning. In addition, the glomerular filtration rate (GFR) allows us to assess the degree of kidney involvement and track the course of kidney disease (Koyner, J. 2012). Next, urine production and the components of urine play an important role in evaluating kidney function. In the setting of chronic kidney disease, protein can be present in the urine, so it is important to collect data to determine its presence. Bringing each individual component together to look at it on a broader scope can give a physician a clearer picture that helps to determine the course of treatment.
Koyner, J. (2012). Assessment and Diagnosis of Renal Dysfunction in the ICU. Retrieved from
Sakovich, N. (n.d.). Collection in Healthcare. Retrieved from
Zeng, X., Liu, J., Ma, L., Fu, P. (2018). Big Data Research in Chronic Kidney Disease.

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