# c813 1. R2.docx - Crystal Bishop C813 ETHICS IN RESEARCH...

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Crystal Bishop C813: ETHICS IN RESEARCH AND HEALTHCARE STATISTICS Task #1 In healthcare research, there are two major types of numerical data: discrete and continuous. Discrete data can be viewed as counting whole numbers. For example, if our quality team were to look at how many patient variances occurred throughout a year, they would be able to count an exact number of patient charts with issues. Continuous data is data that can be presented as fractionated data. Using the example of the quality team identifying patient variances, if they wanted to know on average how many errors per chart were found that could be leading to these variances, that value would be continuous as it’s a measurement rather than a count. If the quality team found 10 patients with variances and a total of 55 chart errors, that the discrete data would be the 10 patient variances, and the continuous data would be average errors per chart, 55/10, or 5.5 errors per chart. To measure various healthcare data there are four types of categorization: nominal, ordinal, interval, and ratio. Nominal data is a simple categorization of data. An example of nominal data collected in healthcare might be someone’s gender. Ordinal data places things in order, as its name suggests. The most commonly recognized ordinal data points is the question On a scale of 0-10, how bad is your pain? The question asks the patient to place their current pain in order of all other pain they have experienced. Another common example of this can be found on patient surveys, i.e., how would you rate your care today, 1) highly satisfied, 2) mostly satisfied, etc.
Interval data is a measurement between two points, i.e., the difference or interval. In healthcare interval, data may be used to track temperature ranges for medication, OR rooms, etc. Having temperatures can help track other data such as operating room temperatures within a specific range help provide post-operative infections. Whereas interval data can be a range from any given starting point to any ending point, ratio data is the measurement of information from a known starting point of zero. A ratio data point in any healthcare setting would be collecting a patient’s weight while a common data point for hospitals would be the length of a patient stay. Both a patient weight and the length of stay start at a value of 0 and measure up from there providing consistent data for every range to be able to establish mean, mode, and median. Using the scenario provided calculations for the average length of stay at Felder hospital for May and June are: May 13,965 total days 3,846 discharges = Average length of stay 3.6 June 16,224 total days 4,018 discharges = Average length of stay 4
Using the scenario provided, calculations for the death rate of patients discharged for May and