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Use of Statistical Information

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Submitted By Stokes2014
Words 1100
Pages 5
Uses of Statistical Information
Donna Ballard, RN
University of Phoenix
HCS/438
Statistics
Betty Jones, RN
July 7, 2015

Statistics is defined as “the science of collecting, organizing, and interpreting data” (Bennett, Briggs, & Triola, 2009). Statistics can be utilized in many ways within an organization such as acute care also referred to as hospitals. Each facility has a specific department identified as infection prevention or infection control. Infection control/prevention uses research and statistics to facilitate standardized care by implementing best practice measures through evidenced 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 finding, and research ( International Federation of Health Information Management Associations, 2012).
The purpose of this assignment is to identify how statistics are utilized within the infection control and prevention department at Sierra View Medical Center, identify one example of descriptive statistics, identify one example of inferential statistics, explain data at each of the four levels of measurement and describe the advantages of accurate interpretation of statistical information to improve decision making. The purpose of infection prevention and control is to put into place policies and procedures that minimize the spread of infections, especially in the hospital setting. The primary function of infection prevention and control surveillance is to reduce the occurrence of infections by using risk factors and implementation of risk-risk reduction measures and the effectiveness of interventions (Centers for Disease Control, 2012).
Central line associated blood stream infections, (CLABSI) and catheter related urinary tract infections, (CAUTI) are two examples of how statistics are utilized in the acute care setting. CLABSI and CAUTI are reported monthly to senior leadership. If an increase in the rate of infection is noted then specific interventions are implemented to reduce the rates and assists with identification of problem areas. Staff as well as patient education, possible increasing the monitoring of hand hygiene compliance and isolation review are just a few interventions utilized to specifically identify problem areas.

The term descriptive statistics is given to analysis of data which helps to describe, show, or summarize data in the meaningful way so that patterns may emerge from the data making it easier to visualize the information (Lund Research, 2013). Two types of statistics which are used to describe data are measures of central tendency and measures of spread. Measures of central tendency are a way of describing the central position of a frequency distribution for a collection of data (Lund Research, 2013). The measures of spread are a way to summarize a group of data by describing how the spread out of the scores are (Lund Research, 2013). In collecting data for CLABSI or CAUTI, descriptive statistics information may be narrowed down into type of infection, such as Methicillin-resistant Staphylococcus Aureus, (MRSA) or Hospital Acquired Infection, (HAI). Identification of results of the number of infections that may have been present in various units in a particular time frame can then be presented in a visual display.
Bennett, Briggs, & Triola (2009) describe inferential statistics as dealing with inferring (or estimating) population parameters from sample data. Inferential statistics is a technique which allows the use of a population to make a generalization about the population from which the sample had been drawn (Lund Research, 2013). An example of inferential statistics within Sierra View Medical Center would be through patient satisfaction surveys as well as surveying the employees. This would provide data from numerous individuals and would represent the population as a whole. The results of this data would provide senior leadership a foundation to make a recommendation based upon the descriptive data.
Nominal, ordinal, interval and ratio are the four levels of measurement which are used in statistics. The nominal level of measurement is pieces of information that consists of name, labels, or categories and involves no ranking or ordering of data (Bennett, Briggs, & Triola, 2009). An example of this data would be use of medical record or account number as a form of patient identification. The data displayed id in no particular order and is completely random (Bennett, Briggs, & Triola, 2009). 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 captures (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 separating each measurement point (Melnyk & Fineout-Overholt, 2011). Ratio levels have the characteristics, the difference between interval and ratio is that interval level does not possess and absolute zero (Melnyk & Fineout-Overholt, 2011). When using interval level of measurement the data would need to indicate whether it has and increase or decrease. Example of ratio measurement would be the description of salaried levels.
Advantages of accurate interpretation of statistical information to improve decision making is essential to provide the highest quality of patient care as it relates to infection prevention and control. The primary responsibility of infection prevention and control is to use the data obtained and create proper policies and procedures that reduce the risk of patients acquiring an infection during their hospitalization. “At its most basic level, statistical quality control is rooted in the graphical and statistical analysis of process data for the purpose of understanding, monitoring, and improving process performance-general objectives that in essence are quite similar to those of epidemiology” (Benneyan, 1998).
In conclusion, statistics play a very important part for the success of any organization. Statistics assist the organization to show where improvements should or can be made and identify is the implementation working well or not.

References:
Bennett, J.O., Briggs, W.L., & Triola, M.F. (2009). Statistical Reasoning for Everyday Life (3rd Ed.). Boston, MA: Pearson Education Inc.
Benneyan, J.C. Statistical Quality Control Methods in Infection Control and Hospital Epidemiology, Part I: Introduction and Basic Theory. Infection Control and Hospital Epidemiology, 19(3), 194-214.
Centers for Disease Control.(2012) Retrieved from http://www.cdc.gov
Lund Research.(2013). Descriptive and Inferential Statistics. Retrieved from http://statistics.laerd.com/statistical-guides/descriptive-inferential-statistics.php
Melnyk,B.,& Fine-Overholt,E. (2011). Evidenced-based {Practiced in Nursing & Healthcare: A Guide to Best Practice (2nd Ed.) Lippincott Williams & Wilkins…...

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