Approved CEU Program

AHIMA Approved CEU Program logoAHIMA Approved - CEU Program: This program has been approved for 12 continuing education units for use in fulfilling the continuing education requirements of the American Health Information Management Association (AHIMA).


This program has the prior approval of AAPC for 12.0 continuing education hours. Granting of prior approval in no way constitutes endorsement by AAPC of the program content or the program sponsor.


CHIMA Approved - CPE Program: This program has been approved for 12 continuing professional education (CPE) credits for use in fulfilling the continuing education requirements of the Canadian Health Information Management Association (CHIMA).

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Health Data Analytics with Microsoft Excel

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This course is not being offered at this time.

Course Description

Health data analysis involves the process of translating data into information valuable to the support of operational and clinical decision-making. This course is designed to provide participants with hands-on experience in health data analytics using the widely adopted tool, Microsoft® Excel®. 

Participants can expect to learn fundamental skills essential to data integrity and preparation, such as sorting, filtering, summarizing, visualizing, and interpreting healthcare data. These skills will follow closely with each required step of the data analytics lifecycle.

After taking this course, you will have a better understanding of the nature of health data analytics, how to leverage the use of Microsoft® Excel® for carrying out fundamental analytical tasks, and ultimately how to discover new knowledge from data. 

About the Course Author

Portrait of Shauna Overgaard, MOOC Course AuthorShauna Overgaard, MHI is an adjunct professor in the College of St. Scholastica's Department of Health Informatics and Information Management, where she instructs a graduate-level course called Healthcare Data Analytics. She is a Ph.D. student of biomedical health informatics and biostatistics at the University of Minnesota. Her clinical research has largely focused on the analysis of MRI, DTI, and fMRI neuroimaging data as well as proteomic and genomic phenotypic data for psychiatric and neurological disorders. Shauna spent several years working in a clinical research setting, designing, implementing, and supervising research studies; building database systems for automated clinical data entry and extraction; and analyzing and interpreting clinical outcomes data. 

While earning her master's degree, she was awarded a UPHI fellowship and specialized in healthcare information exchange. She is an IPHIE Fellow, a Merrill H. Knotts Fellow, is AMIA student working group co-member-at-large (doctoral/Ph.D.), and contracts with AHIMA for analytics related projects. Shauna is currently completing her dissertation in the Department of Radiology at the Mayo Clinic in Rochester MN. Her research is aimed toward the development of bioinformatics tools, in neuroimaging and genomic modeling, to assist in the prevention of Alzheimer's disease.

Assessments

The course includes six assessments in the form of multiple-choice quizzes. The quizzes are meant to test your knowledge of foundational guidelines presented and analytical techniques performed in Microsoft Excel. All quizzes are administered online and should be completed without any aid from other persons.

Technical support and academic honesty

Limited technical support is available through videos and other resource links provided. Participants are asked to comply with our policies relating to academic honestly, intellectual property, and other principles of our institution. Please see Terms of Use for details.


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