# Topic 1: What Is Statistics and Why It Is Important to Health Sciences?

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### NRS 428 Topic 1: What Is Statistics and Why It Is Important to Health Sciences?

Topic 1: What Is Statistics and Why It Is Important to Health Sciences?

Objectives:

1. Describe an example of each type of measurement: nominal, ordinal, interval, ratio.
2. Define basic statistical terms.
3. Explain the historical application of statistics.
4. Describe the application of statistics in health care quality, safety, health promotion, and leadership

### Application of Statistics in Health Care

Statistical application and the interpretation of data is important in health care. Review the statistical concepts covered in this topic. In a 750-1,000 word paper, discuss the significance of statistical application in health care. Include the following:

1. Describe the application of statistics in health care. Specifically discuss its significance to quality, safety, health promotion, and leadership.
2. Consider your organization or specialty area and how you utilize statistical knowledge. Discuss how you obtain statistical data, how statistical knowledge is used in day-to-day operations and how you apply it or use it in decision making.

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Three peer-reviewed, scholarly or professional references are required.

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### Topic 1 DQ 2

Discuss why it is important for a person working in health care to understand statistical concepts. Provide an example of how statistical data is used in your organization or specialty area today and what you are expected to do with this information as a practitioner.

Re: Topic 1 DQ 2

The ability to understand the data about a special issue in the health care setting and apply it is an essential for positive patient outcome is extraordinarily crucial in our field today. The health care field is an ever changing environment with a constant need for improving the process. In the analysis of the data, trends or patterns are recognized, and those trends allow the assumption of predictability, which can create stronger models of care, resulting in increases quality of care and patient safety. Statistical analysis of the data is used to answer questions that improve population health. I am an ECT nurse and the program started 6 years ago with our success rate being 77% compare to state wide. The result is based on a questionnaire with specific questions after 12 acute treatment. This is how we promote the program. I think that there is many unanswered question in this data i.e. define “success rate” , “is it ECT with medication combination” etc…. I have seen individual success generally half way through simply by a smile, improved mood and affect, able to resume some simple daily functions, watching a movie etc…

### Topic 1 DQ 1

Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.

Re: Topic 1 DQ 1

Statistics have been utilized in healthcare since at least the 19th century. Florence Nightingale used a statistical approach to decrease the mortality rate of British troops in Crimea. Florence in 1854 with 38 nurses went to a military camp of British soldiers, located on the outskirts of Constantinople. Florence noticed that health status in these camps was devastating. Injured soldiers were left on the floor and the few doctors desperately were trying to manage patients with basic facilities, in a dirty environment. Florence used her mathematical knowledge and recorded the mortality rate in the hospital (Karimi & Masoudi Alavi, 2015). Statistics showed that in every thousand injured soldiers, the six hundred were dying because of communicable and infectious diseases. Sheingold & Hahn (2014) observed that Nightingale documented that if improvements had been implemented prior to admitting soldiers to the hospital, thousands of needless deaths would have been prevented. Her meticulous records were a key to present day statistical quality measurement, and she was an innovator in the collection, tabulation, interpretation, and graphical display of descriptive statistics. She named her graphical data to display a “Coxcomb” which is known today as a pie-chart.

It is a fact that healthcare is a pressing social, political, and economic issue in the United States. The American healthcare economy presents special problems for data collection, analysis, and dissemination. Therefore, health statistics systems have grown rapidly with the growth of the industry. Datamate Infosolutions (2018) observe that innovative medicine begins and ends with statistical analysis. Data are collected and reported in clinical trials of new technologies and treatments to weigh products benefits against their risks. During the 20th century, researchers developed vaccines that prevent smallpox, measles, polio, and other diseases. The safety and efficacy of these life-saving vaccines were tested by using statistically designed clinical trials and statistical quality control during manufacturing. Many of these studies were conducted out of the public’s eye, but in 1954 there was a massive public trial to test Jonas Salk’s polio vaccine. More than 1.8 million children participated in a randomized, double-blind trial. This is a statistical design in which subjects are randomly assigned to either the control group or the vaccine group. This famous experiment was a success. Today, pharmaceutical companies run similar statistical studies as they develop drugs for the treatment and management of a wide range of maladies (Wicklin, 2013).

Nowadays, health care organizations employ statistical analysis to measure their performance outcomes. Hospitals and other large provider service organizations implement data-driven, continuous quality improvement programs to maximize efficiency. For instance, staff at many hospitals use statistical process control (SPC) charts to monitor nurse sensitive indicators and adverse events such as rates of falls, central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator acquired pneumonia, pressure ulcers, surgical site infections, and readmission within 30 days (Hagan, 2018). Utilization of SPC charts can extend beyond monitoring events rates to other types of measures such as the average length of hospital stay or an average cost of treating patients with a certain diagnosis.

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