Research methods and statistical analysis

Statistical AnalysisBy June Helbig

Essential Questions

· What is the difference between experimental, quasi-experimental, and nonexperimental research?

· How does qualitative research differ from quantitative research?

· What is the difference between causation and correlation?

· What is the difference between research and quality improvement.

Introduction

Health care professionals must have knowledge regarding research methods and statistical analysis. Statistical analysis is associated with  evidence-based practices and is responsible for many of the new and innovative treatments and procedures performed by health care professionals every day; however, knowing about evidence-based practices and using them is not enough. One must know how the results were obtained and if the results are statistically sound (see Figure 4.1). Health care professionals are concerned with quality and providing those in their care with safe, patient-centered care.

Figure 4.1

The Road to Evidence-Based Practice

he steps to developing evidence-based practice: Ask a question, find the evidence, a

Using the results of research involves incorporating those results into care provided to patients. Using new drugs, treatments, or procedures is for the sake of quality patient care. A very simple way to look at it is to consider the three Rs that make up evidence-based practice—Research, Results, and Review. The research is completed, the results are obtained, and then experts review the results of the study. If the review is found to be positive, the drug, treatment, or procedure can now considered evidence-based and can be put into practice (see Figures 4.1 and 4.2).

Figure 4.2

The Three Rs of Evidence-Based Practice

igure demonstrating that research, results, and review creates evidenc

· https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-care/v1.1/chapter-images/hlt362.blue.safety-icon.png

Many hospitals have professional practice committees that examine the results of research and quality improvement projects. The purpose of these committees is to find new and innovative ways to provide quality health care. Implemented changes are supported by results or evidence obtained through research. The following questions are some examples that may be asked when reviewing results connected with a research study.

· Can the same results be duplicated?

· What data were obtained and how were the data analyzed?

· What type of research was performed?

· Was it experimental, quasi-experimental, or nonexperimental research?

· Was it a qualitative study or a quantitative study?

· Were the research findings the result of cause and effect or were the findings the result of correlation?

These and many other questions will be answered as statistics for health care professionals is learned. After reading this chapter, the health care professional will be able to understand and answer those questions.

Conceptual Framework

· https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-care/v1.1/chapter-images/hlt362.blue.conceptual-icon.png

 conceptual framework  is an analytical tool used to build a research study. All research studies begin with a hypothesis. The researcher takes that hypothesis and formulates a theory. The researcher is able to take that theory and build a conceptual framework to investigate the theory. In order to answer the hypothesis, the research process must be followed, which will lead to a result. The hope is that the result aligns with the researcher’s theory; however, the conclusion may or may not support the hypothesis. The steps taken to prove a theory are considered the building materials of a conceptual framework. The conceptual framework explains what will be investigated, how it will be investigated, and what will be needed to arrive at a conclusion. The conceptual framework defines the tools needed to answer the hypothesis and the  variables  the researcher or investigator will encounter along the way.


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