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Statistics in the Workplace

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Statistics in the Workplace
HCS/438
May 6, 2014

Statistics in the Workplace
The healthcare setting has used research and statistics to aid in standardized care by implementing best practice measures. This is also known as evidence based practice. Statistical information that is gathered is then used to help compare present and past performance, as a guide for planning future development, appraisal of work performed by healthcare staff, hospital or clinic funding, and research (International Federation of Health Information Management Associations, 2012). The purpose of the following paper is to discuss the use of statistics within Mercy Medical Center located in Des Moines, Iowa by using examples and explanations of terms used in statistics such as descriptive and inferential statistics and the four levels of measurement.
Within Mercy Medical Center, nursing care is centered around the use of evidence based research thus making it important to understand the basic use of statistics in evaluating research. Hospitals must monitor for the amount of infections which occur in various units continuously since an infection can adversly afffect a patients treatment and may possibly lead to death. One of the infections which can occur is central line acquired blood stream infections (CLABSI).
The raw data that is gathered from CLABSI is an example of descriptive statistics. The term descriptive statistics is given to the analysis of data which helps to describe, show, or summarize data in a meaningful way so that patterns may emerge from the data making it easier to visualize the information (Lund Research, 2013). There are two types of statistics which are used to describe data, measures of central tendency and measures of spread. With measures of central tendency, this is a way of describing the central position of a frequency distribution for a collection of data (Lund Research, 2013). The measures of spread is a way to summarize a group of data by describing how spread out the scores are (Lund Research, 2013). In the collection of CLABSI for descriptive statistics, information may be narrowed down into type of infection and how many infections may have been present in different units for a particular time period. The information is then presented in a visual display.
Inferential statistics is a techniques which allows one to use a sample of a population to make a generalization about the population from which the sample had been drawn (Lund Research, 2013). This may also be referred to as an estimation. An example of inferential statistics within Mercy Medical Center may be used to predict the number of infections which may occur within a certain time period. Another example of inferential statistics within Mercy Medical Center would be through satisfaction surveys from employees or even patients. Numerous individuals from the population would provide data which would then represent the population as a whole.
The four levels of measurement which are used in statistics are nominal, ordinal, interval, and ratio. There are times when not all of the levels of measurement are used within a study. The first level of measurement is the nominal level. In the nominal level, numbers, letters, or words are used to classify data. The nominal level is the least sophisticated and lowest form. An example of a nominal measurement may by the quality of pain a patient may experience rated as “sharp”, “burning”, “aching” (Melnyk & Fineout-Overholt, 2011). The ordinal level of measurement represents categorical data. The numbers that are assigned to categories with ordinal measures allow ranking from lowest to highest allowing the magnitude of the variable to be captured (Melnyk & Fineout-Overholt, 2011). The use of Likert scales provide information at the ordinal level by using selections such as “satisfied”, “very satisfied”, “neither”, “dissatisfied”, or “very dissatisfied” when conducting surveys (Melnyk & Fineout-Overholt, 2011). The interval level is the next highest level and results from numeric data with equal and consistent mathematical values seperating each measurement point (Melnyk & Fineout-Overholt, 2011). Though the ration level has the characteristics, the difference between interval and ratio is that the interval level does not posses an absolute zero (Melnyk & Fineout-Overholt, 2011). An example of an interval level of measurement would be when needing to indicate whether data has an increase or decrease. An example of a ratio measurement would be when describing levels of pay.
The advantages of using statistics in the workplace is that the healthcare facility is able to improve the decision making capability within the organization. In order to do this, members of the healthcare team must fully understand and accurately interpret the data gathered within the statistical study. With the use of the gathered data, members can improve the rates of infection or even the satisfaction of patients as well as employees.
It is important for healthcare organizations to utilize the use of statistics within the workplace to enhance evidence based practice. Without the use of statistics, an organization may not be able to have to required data to be a productive facility and better patient care. The information which is gathered to be analyzed may focus on the entire population as a whole or a sample of the population represented as a whole.

References
International Federation of Health Information Management Associations. (2012). Education

module for health record practice. Retrieved from

http://www.ifhima.org/ed_modules/Updated%202012/Module%204%20Healthcare%20S

tatistics.pdf

Lund Research. (2013). Descriptive and Inferential Statistics. Retrieved from

https://statistics.laerd.com/statistical-guides/descriptive-inferential-statistics.php

Melnyk, B., & Fineout-Overholt, E. (2011). Evidence-based Practice in Nursing & Healthcare:

A Guide to Best Practice (2nd ed.). Lippincott Williams & Wilkins.

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