# Nursing and Statistics

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Nursing and Statistics

When most people think of nursing the last thing they usually think of is statistics. However the use of statistics has become a very important part of nursing today. Consider the following quote: “Systematically collecting, analyzing, interpreting, disseminating, and using health data is essential to understanding the health status of a population, to assessing progress, and to planning effective prevention programs. Therefore, data are the foundation of Healthy People objectives” CITATION USD00 l 1033 (U.S. Department of Health and Human Services, 2000). Health data is a massively growing field. The pure number of statistics that are collected today is quite breathtaking. It is now nurses’ job to utilize this vast array of data to better patients out comes. The data is particularly important for nurses to understand the spread of diseases, to understand the prevalence of certain diseases and to correlate symptoms with probably causes. Taken as a whole, health data and statistical analysis is a valuable tool for nurses today.

The data is usually always discrete in nature. That is a finite point or measurement, like for example the average blood pressure by state in the United States. The data is often aggregated, like the data type just mentioned; that is the data is averaged and not necessarily just individual data. Thought individual raw data can also be used. The data is usually discrete and in the form of cardinal, nominal, ordinal, interval or ratio.

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The difference between cardinal and ordinal data is that nominal data is taken to mean a certain level of measurement. For example a cardinal data point that could be used is simply heart rate. Heart rate is not a rank it is an actual number that exists on a scale and measures a quantity; the scale can be interpreted as having certain ranges like normal to high. The scale of normal to high on the other hand is an example of an ordinal piece of data. Ordinal data ranks qualitative differences. The classic ordinal data is survey data such as “how do you feel”; the answers could be 1 = bad, 2= ok, 3= good. Thus the numbers 1, 2, 3 are not taken to really reflect any measure; they are taken to reflect relative rank. 1 is worse than 2. Nominal data refers to things that don’t have a natural rank. An example of a nominal piece of data is the name of the hospital a patient was last at. Interval data is ordinal data where each unit is equally split. For example the temperature of a patient can be 29-30 which represents the same difference as say 5-6. Finally there I ratio data, this is data like any other form but has a natural normalization. Normalized data has a natural 0 point that is meaningful. Ratio data contains all the elements of the above data and has a natural start and end point. Thus ratio data is the best type of data to have. An example of ratio data is the weight of some one.

A nurse will often encounter what is called summary statistics; stats like mean, median, mode and standard deviation. An example of a mean that is important is the mean blood sugar level that a patient has. The median is often important when there are major outliers in the data. So for example the median is often more important when judging out healthy the patient usually is. Often they are in the hospital for the very reason that an outlier event occurred. Thus you many want to look at the median to understand the usual health of a person. Mode is the data point that occurs most frequently; an example of this in nursing is what the most common response to a survey is. It can often measure the most favored treatment, for example most patients prefer testing in the morning vs other times; thus the mode response would be in the morning. Standard deviation is a very important statistic that measures the spread of a data set. This can very important, for example two patients could both have a blood sugar level that averages 6, however one patient could have a standard deviation of 1 meaning they are usually always between 4 and 8 which is normal, while another could have a standard deviation of 7. Meaning they are often very low and sometimes very high. A high standard deviation in this case could reflect a serious illness. Other common summary statistics are count data; an example of count data would simply be the number of times a patient got up to go to the washroom during the night. Finally percentiles and quantiles are also valuable summary statistics. Both give a nurse an understanding of what range certain data is. An example would be that a patient’s blood pressure is in the highest quantile or 20th percentile. This lets the nurse know, without having to know what the raw data means, that the level of say blood pressure is very high.

An important aspect of nursing is the use of inferential statistics. Inferential statistics is the practice inferring population statistics from a sample from that population CITATION byF13 l 1033 (by Frederick J Gravetter (Author), 2013). These are incredibly important as inferential statistics is the main tool of research. Research in turn influences the practices of a nurse on a day to day basis. Most things a nurse does at one point or another have been influenced by inferential statistics. The basic practice is to take a sample set of data and try and control for the variables that you wish to understand. The data could be generated in a controlled experimental environment or just taken from the real world outside of any experimental set up. An example of experimental data would be conducting a controlled experiment on a group of participants. You give one set a placebo drub and the other set the real drug. You then see if there is any difference between the groups. An example of statistics taken from the real world might be the survival rate of patients that suffer cardiac arrest. This type of data is always harder to infer true relationships because the data was collected outside of an experimental setting. None the less inferences can often be gathered if the data was collected in a way that mimics a real experiment.

The use of statistics in nursing is incredibly important. It allows the nurse to use data to serve patients much more effectively. With the huge accumulation of health data it has become very important for nurses to have a very good understanding of basic statistical techniques.

References

BIBLIOGRAPHY by Frederick J Gravetter (Author), L. B. (2013). Essentials of Statistics for the Behavioral Sciences. Wadsworth Publishing.

U.S. Department of Health and Human Services. (2000). Tracking Healthy People 2010. Washington DC: U.S. Government Printing Office.

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