Statistical Applications Paper
STATISTICAL APPLICATIONS
HCS/438
June 10, 2013
Instructor: BRENT THAYNE
As a registered nurse in the management role, I see the every day uses of statistics in my workplace. The healthcare industry use statistics to benefit from knowing consumer market characteristics such as age, sex, race, disabilities and utilize this data to provide affordable levels of care to the population it serves. An example, living in San Francisco, in the 1980’s at the height of the AIDS epidemic, many San Francisco hospitals designed medical units specifically dedicated to the patients diagnosed with this unknown illness, but knew from statistics who it was affecting and learning from research how to manage the patients based on data collected not only from the community itself, but from national statistics obtained from the Centers of Disease Control. Health administrator’s reference statistics on service utilization to apply for grant funding and to justify budget expenditures to their governing boards, as well as create department budgets that are realistic based on past data collected. Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analyzed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data. In my current position, I review the patient satisfaction data that has been collected and it is presented using specific descriptions when it breaks down each category to include the total number of patients, but also broken down even further to measure data based on specific data as race, age, etc. Inferential statistics are data which are used to make generalizations about a population based on a sample. They rely
HCS/438
June 10, 2013
Instructor: BRENT THAYNE
As a registered nurse in the management role, I see the every day uses of statistics in my workplace. The healthcare industry use statistics to benefit from knowing consumer market characteristics such as age, sex, race, disabilities and utilize this data to provide affordable levels of care to the population it serves. An example, living in San Francisco, in the 1980’s at the height of the AIDS epidemic, many San Francisco hospitals designed medical units specifically dedicated to the patients diagnosed with this unknown illness, but knew from statistics who it was affecting and learning from research how to manage the patients based on data collected not only from the community itself, but from national statistics obtained from the Centers of Disease Control. Health administrator’s reference statistics on service utilization to apply for grant funding and to justify budget expenditures to their governing boards, as well as create department budgets that are realistic based on past data collected. Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analyzed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data. In my current position, I review the patient satisfaction data that has been collected and it is presented using specific descriptions when it breaks down each category to include the total number of patients, but also broken down even further to measure data based on specific data as race, age, etc. Inferential statistics are data which are used to make generalizations about a population based on a sample. They rely
References: Carey RG, Lloyd RC. Measuring quality improvement in healthcare: a guide to statistical process control applications. Milwaukee, WI: American Society for Quality, Quality Press,2001. Benneyan JC. Use and interpretation of statistical quality control charts. Int J Qual Health Care1998;10:69–73.