Research and prepare a literature review with statistical analytics pertaining to the prevalence and treatment of diabetes.
Your topic in healthcare, which has ample data analyses available, is Diabetes.
Use Data.gov, or Statista.com, or Kaggle.com to help you find the data set for the research.
Your submission should include six or more resources (articles, websites, databases).
Tell your topic’s story and set the stage for more research or answers towards the future of healthcare.
Structure of the research:
I. INTRODUCTION (why the study was undertaken?)
II. METHODS (how was the study conducted?)
III. DISCUSSION (What do the findings mean?)
IV. RESULTS (What was found from the study?)
Research Questions:
1) What is the prevalence of diabetes in a given population, and how does it vary by age, gender, ethnicity, and other factors? This question can be answered using survey data, medical records, or other sources.
2) What is the risk factor for developing diabetes, and how can they be identified and addressed? This question can be answered using epidemiological studies, observational studies, or clinical trials.
3) What are the most effective treatments for diabetes, and how can their effectiveness be measured?
4) How does diabetes impact health outcomes, such as mortality, morbidity, quality of life, and healthcare costs?
5) How can diabetes prevention and management programs be designed and evaluated to maximize their impact and cost-effectiveness?
Resource: Please review the Health Information Management Research Guide Resource:
The Process for the research:
1) Start with the CINAHL database (which indexes leading journals for the HIM and health informatics fields).
2) Run test searches with keyword search strings, such as: “data analytics method*” or “data analytics in healthcare” or “big data in heathcare”
[The quotations tell the search engine to retrieve the phrase; the asterisk is a truncation symbol that allows for the retrieval of method, methods, methodology all in the same search.] Then consider:
What data analytics methods are presented … and which of these might fit with your chosen topic?
This will provide you guidance on other key words to use in your search with your topic.
3) Next run test searches — in CINAHL, MEDLINE, etc. — using keywords that relate to your topic, plus keywords and/or MESH headings one would add to try to pull in data analysis-related citations
Data analysis in chronic disease research typically involves collecting and analyzing large amounts of data from various sources, including electronic health records, population surveys, clinical trials, and administrative databases. Please, include the key data analysis techniques used in chronic disease research, such as:
1. Descriptive analysis: This involves summarizing and presenting data in a way that can be easily understood, such as tables, graphs, and charts.
2. inferential analysis: involves making inferences and drawing conclusions about the population based on data collected from a sample.
3. Predictive modeling: This involves developing mathematical models that can predict the likelihood of developing a chronic disease or the effectiveness of a particular treatment.
Be sure to include your research statement, data analysis, including descriptive statistics, charts, pivot tables, etc, and conclusions about the data, including inferential statistics test.