Hemodialysis and Its Impact to End Stage Renal Disease Patients

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Hemodialysis and Its Impact to end Stage Renal Disease Patients Student’s Name University Contents 1.0 Background to the Study.........................................................................................3 2.0 Introduction.............................................................................................................3 3.0 Problem Statement..................................................................................................4 4.0 Data Collection........................................................................................................4 5.0 Data Management and Analysis..............................................................................5 6.0 The Protection of Human…show more content…
These patients were identified from the data available from medical coding systems at Royal Victoria Hospital. The sampling methodology used to determine these 35 patients was stratified sampling. According to, (Yin, 2003), with stratified sampling, the population is categorized in different layers known as strata. Each level consists of individuals with homogeneous characteristics. Once the layers are created, either simple random sampling or systematic random sampling is used to make a sample from each stratum (Yin, 2003). Quantitative studies involve generation of data in numerical form or data that can be expressed in figures or quantity (Yin, 2003). To come up with a sample of 35 patients, the patients who were suffering from classified kidney disease were classified into layers or strata. The criterion used to create these levels was the cause of kidney disease in these patients. The level with patients who had patients’ kidney disease caused by cardiovascular disease and were undergoing hemodialysis was selected for this study. The 35 patients were interviewed, as the study used standardized interviews to generate and classify data (Yin, 2003). Use of small sample in this study minimized the standard error and bias while analyzing the data, as the sample size was 35 patients. This size of the
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