Uses of Statistics in the Workplace Essay Example for Free

Uses of Statistics in the study EssayStatistics is defined by Bennett, Briggs, Triola (2009), as the science of collecting, organizing, and interpreting data (p. 1). Almost every job uses statistics in some way to guide in making good decisions based on menstruum research. The nursing profession relies heavily on current research to guide patient concern with the consolidation of evidenced-based practice. Statistics provide valuable selective information to c begivers to help them understand, plan, evaluate, and improve the quality of patient c atomic number 18.In the acute care infirmary setting there are ongoing bars of much(prenominal) things as patient satisfaction, spend washables residency rates, catheter acquired urinary tract infections, and central access infection rates, just to name a few. The assembly of this data involves descriptive statistics, inferential statistics, and takes of measurements. Acute care hospitals use descriptive statistics in many w ays. descriptive statistics describes raw data in the form of samples or graphs (Bennett, Briggs, Triola, 2009).One area in which they are apply in the hospital is to evaluate debate laundry compliance of wellness care providers. According to Vincent (2003), nosocomial infections occur in approximately 30% of patients in the intensive care setting and are associated with increase morbidity and death rate. Research shows that effective hand washing can prevent many hospital acquired infections (Vitez, 2010). In the hospital setting, hand washing compliance is monitored on an ongoing basis.Health care workers who come in contact with patients are observed by an unidentified member of the staff who monitors the subject upon entering and leaving a patient board. Hand hygiene can be performed by either by washing with soap and water or use of hand sanitizers. The expectation is that the subject will wash their turn over upon entering the room and upon leaving the room. The subje ct must be monitored both entering and leaving the room for the observation to be included in the data. Initial hand washing data showed poor staff compliance.Employees were lacking in hand hygiene and putting patients at risk (Vitez, 2010). Based on the results of wee observations, a plan was utilise to increase staff compliance. Education was provided to increase awareness of the importance of hand washing and frequent reminders are inclined in the form of screen saver messages and signs posted at the entrance of every room. Interventions have also been implemented such as conveniently placing hand sanitizer containers orthogonal of every room and throughout the hallways of the institution.Recent monthly hand hygiene compliance rates are generated and have improved to 85% -90% hospital wide. Use of these descriptive statistics using raw data on hand hygiene rates has been an important tool in increasing awareness of the importance of hand hygiene to the overall safety of our p atients. Hospitals are safety and quality driven. Several research studies have shown a direct relation to the skill and education of the nursing staff and a decrease in mortality (McHugh Lake, 2010). Inferential statistics involves making predictions based on information prevailed in a smaller sample (Bennett, Briggs, Triola, 2009).This information and the inference of better patient outcomes have prompted many hospitals to require nursing staff to attain a bachelors of science in nursing. The research suggests a positive correlation between overcritical thinking skills and nurses with a bachelors of science degree and positive patient outcomes (McHugh Lake, 2010). The institution where I am employed, and many institutions in our tri-state area, is using the findings of these inferential statistics to require that all nurses in their employ obtain a bachelors of science in nursing in an effort to provide patients with the surpass possible outcome.Those in the health care prof ession, and those involved in nursing research, have many uses for the quad levels of measurement in statistics. The four levels of measurement in statistics include nominal, ordinal, interval, and ratio (Bennett, Briggs, Triola, 2009). The nominal level of measurement is the simplest level of measurement that involves variables, or labels, to classify data in a qualitative way (Bennett, Briggs, Triola, 2009). token(a) variables include such things as categories of people, race, gender, or age.In the hospital setting, the nominal level of measurement is utilize most obviously when completing a patient history which asks the patients name, sex, marital status, and blood type. The ordinal level of measurement assesses data incrementally and puts data in order either from low to eminent or high to low in a ranking form (Bennett, Briggs, Triola, 2009). This level of measurement is used in the hospital setting to measure pain perception and in patient satisfaction surveys.There h as been increasing stress on the use of patient satisfactions surveys to assess the quality of health care and many facilities have implemented improvement projects in relation to such things as reception skills, food services, housekeeping, and reorganization of hospital take in procedures (Gray, Richmond, Ebbage, 2010). These scores reflect the patients subjective perception of their hospital experience and his or her likelihood to recommend the facility to family members and friends.Ordinal levels of measurement are also used to rank hospital exertion in several areas including hospital acquired infections and readmission rates (U. S. Department of Health and Human Services, n. d. ). These rankings are reported to the creation and may influence a health care consumer in their decision of where to seek their medical care. time interval levels of measurement apply quantitative data in meaningful intervals without reference to ratios and no set principal for zero variables wi thin this level of measurement are assessed at equal intervals (Bennett, Briggs, Triola, 2009).The obvious example in the health care field of an interval level of measurement would be that of a thermometer or a calendar. Using the hand hygiene information mentioned earlier, the information is presented to the staff using a grading system that is broken down into intervals. Each interval is identified by a color. The scale begins at 60%. Units with a compliance ranking of 60-79% are given the color red. Units with a compliance ranking of 80-89% are given the color yellow. Green is given to any unit that has a hand washing compliance ranking of 90% or greater.This interval level of measurement ranks each unit and allows them to compare their rankings with separate units in the facility. As incentive for improvement, departments with consistent compliance rankings of 90% or above have been given rewards such as gift cards and luncheons. Ratio levels of measurement are similar to int erval levels barely a zero point does exist (Bennett, Briggs, Triola, 2009). Ratio levels of measurement apply to quantitative data characterized by intervals that are assessed incrementally with equal distances between the increments (Bennett, Briggs, Triola, 2009).In the hospital setting, nurses routinely use ratio levels of measurement such as the patients weight, height, temperature, blood pressure, and respiratory rate. In conclusion, numerous statistics are collected and analyzed in the health care setting. Accurate statistics provide information regarding patient satisfaction, patient safety, and patient outcomes. Using this information to detect areas for improvement, planning, and implementing changes in care and practice will improve the quality of care, decrease morbidity, and improve patient outcomes.