Question attached. 

Final Term Project Task

Referral file- Health Care System Using Data Mining Techniques- can use for introduction etc

You have been asked by management (manufacturing, healthcare, retail, financial, and etc.,) to create a research report using a data mining tool, data analytic, BI tool. It is your responsibility to search, download, and produce outputs using one of the tools. You will need to focus your results on the data set you select.

Ensure to address at least one topic covered in Chapters 1-9 with the outputs. The paper should include the following as Header sections. You can find some related topics if you want. Then write the term paper.

Example of topics:

1. Using data mining techniques for learning systems….

2. How to improve Health Care System using data mining techniques… (This would be my topic based on week 6 discussion, File attached)

3. Design and develop Network/Information Security using data mining techniques…

4. How efficiently extract knowledge from a big data using data mining techniques…

5. Using data mining techniques to improve the financial/stock information systems…

Types of Data Analytic Tools:

https://www.octoparse.com/blog/top-30-big-data-tools-for-data-analysis/

Excel with Solver, but has limitations

R Studio

Tableau Public has a free trial

Microsoft Power BI

Search for others with trial options

Examples of Dataset:

http://www.rdatamining.com/

https://www.forbes.com/sites/bernardmarr/2016/02/12/big-data-35-brilliant-and-free-data-sources-for-2016/#4b3e96f1b54d

Example: Project Construction Format:

You should follow the following content format:

Title: Topic

Name:  <>

ID: <>

I. Introduction

II. Background [Discuss tool, benefits, or limitations]

III. Review of the Data [What are you reviewing?]

IV. Exploring the Data with the tool

V. Classifications Basic Concepts and Decision Trees

VI. Other Alternative Techniques

VII. Summary of Results

References

(Ensure to use the Author, APA citations with any outside content).

Assignment Instructions:

1. No ZIP file

2. The submitted assignment must be typed by ONE Single MS Word/PDF file.

3. At least 10 pages (not including heading and content list pages) and 5 references.

4. Use 12-font size and 1.5 lines space

5. No more than 4 figures and 3 tables

6. Follow APA style and content format: UC follows the APA (American Psychological Association) for writing style in all its courses which require a Paper or Essay.

http://www.apastyle.org/

Grading Rubrics:

This assignment is an individual work. Please do NOT co-working with colleagues to violate the academic integrity. Grading for this assignment will be based on answer of completed the above requirements, quality, logic/organization of the paper, and language and writing skills. Please see as follows:

· Comprehension of Assignment (Addressed the question completely and thoroughly. Provided additional supporting evidence, demonstrating a full comprehension of subject matter): 30/30 points

· Application of Course Knowledge and Content (Thorough technical application of course knowledge and content in a complete and concise manner): 30/30 points

· Organization of Ideas (Original ideas are effectively developed and presented in a logical, sequential order throughout the entire assignment. Includes adequate and appropriate supporting evidence): 30/30 points

· Writing Skills (Mechanics (spelling, grammar, and punctuation) are flawless, including proficient demonstration of citations and formatting throughout the entire assignment): 30/30 points

· Research Skills (Accurate and applicable use of resources relevant to the subject matter that enhance the overall assignment): 30/30 points

Data Mining in Health Care Industry

ABSTRACT

Data mining involves the process of examining the existing databases that are in large amounts with the aim of generating new information. The process involves the obtaining new pieces of data from large files of data which is stored for later use. The healthcare uses data mining in getting the crucial elements from large databases that are important in solving the various hazards that occur in the healthcare sector. The healthcare professional will be able to store the patient data including treatment records that are vital to the delivery of quality services. The healthcare sector use data mining in predicting future observations that are yet to occur. The data mining offers insights into the medical sector in solving complex problems in the medical field.

INTRODUCTION

The patients’ information on treatment is securely stored without getting mixed up by the system that facilitates the opportunity for medical personnel to easily retrieve data when needed. Accessibility of information is offered to a project that facilitates storing data in relaxed way with the knowledge of having patient data in files (Rojas, Munoz-Gama, Sepúlveda and Capurro, 2016). The patient does not worry about losing their health information as they are sure of secure storage allows follow ups. The clinician is able to obtain the information of a patient before prescribing the dosage and the drugs from the medical files. The information about allergies can show up from the medical files that will promote offering of better health services and analyze the patient appropriately (Raghupathi, 2016). The eminence of the management will be dependent on the handiness of the patient’s conduct facts. This improves the healthcare sector as it offers the physicians to have a look at previous information on various issues in the facilities.

In cases where there are problems with care teams on patient treatments, data mining facilitates the obtaining of the relevant information to solve the problem. The association which is fundamentally the infirmary is liable for the delivery of organization and harmonizing possessions. These are applied in provision of the slog and the expansion of the upkeep crews and the big schemes in the infirmaries. The crews often encounter situations that need different strategies to come up with decisions that may contradict the treatment procedures causing outcomes that were not expected (Komal, 2017). Data mining will reveal the various decisions made that will help solve treatment problems for patients with similar health issues.

The cost of healthcare is reduced by data mining through the facilitation of abilities to leave a trace of activities. At the administrative level, the health workers are remunerated for doing more with great proficiency. The treatments are overly repeated in the absences of the sought hypothesis of the test. The charge of care is develops due to the increase of protracted ailment that comes along with old age population that lashes up the budgets (Stoddart and Evans, 2017). With data mining, the healthcare will be able to focus with the needed treatments for patients without necessarily conducting tests similar to past ones. This will improve the healthcare by reducing the cost of resources that are needed in the conducting tests (Pradhan, 2018). The healthcare professionals will be able to gather different hypothesis for tests carried out increasing accuracy in the healthcare systems.

References

Evans, R. G., & Stoddart, G. L. (2017). Producing health, consuming health care. In Why are some people healthy and others not? (pp. 27-64). Routledge. Retrieved from

https://www.taylorfrancis.com/books/e/9781315135755/chapters/10.4324/9781315135755-3

Komal, S. (2017). Data Mining Techniques in Healthcare. Retrieved from 

http://www.ijcstjournal.org/volume-5/issue-6/IJCST-V5I6P11

Pradhan, M. (2018). Indian Healthcare Service Management Through Data Mining: Datamining for Healthcare Services. In Next-Generation Mobile and Pervasive Healthcare Solutions (pp. 219-233). IGI Global. Retrieved from

https://www.igi-global.com/chapter/indian-healthcare-service-management-through-data-mining/187525

Raghupathi, W. (2016). Data mining in healthcare. Healthcare Informatics: Improving Efficiency through Technology, Analytics, and Management, 353-372.9). Producing health, consuming health care. In Why are some people healthy and others not? (pp. 27-64). Routledge. Retrieved from

https://scholar.google.com/scholar?q=related:zmoPwrbHUwwJ:scholar.google.com/&scioq=Raghupathi,+W.+(2016).+&hl=en&as_sdt=0,5&as_ylo=2016

Rojas, E., Munoz-Gama, J., Sepúlveda, M., & Capurro, D. (2016). Process mining in healthcare: A literature review. Journal of biomedical informatics, 61, 224-236. Retrieved from

https://www.sciencedirect.com/science/article/pii/S1532046416300296