- Use Visio to create a data model that supports a health care clinic’s business practices. Include all data points provided by the clinic in the data model.Introduction
A data model shows the structure of a database, including the relationships that determine how the data is stored and accessed. Data models also determine which data management system will be used. Most data management systems are built for a specific data model. Among the numerous types of data models are relational, conceptual, logical, physical, and entity-relationship models. Data models are represented by diagrams. In this assessment, you will use Visio to develop a data model for a specific health care scenario.Demonstration of Proficiency
By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:- Competency 3: Use data analysis skills to support health information integrity and data quality.
- Construct a data model that supports the clinic’s business practices.
- Group data under appropriately labeled category headings.
- Use data modeling symbols and notations.
- Apply knowledge of data modeling concepts.
- Competency 5: Communicate in a professional manner to support health care data analytics.
- Create a clear, well-organized, professional document that is generally free of spelling errors.
- Preparation
Note: The software listed below is strongly recommended to support you in completing the course competencies. If you have access to other tools that you believe may still meet the requirements of this course, please discuss your selected alternatives with your faculty member.For this course, follow the instructions provided through the links below to download and install software or register for an account, as required.You will use Visio, available through MS Imagine, to create your data model. There is no additional cost for this software and technology. It will be made available to you through Capella’s subscription with Microsoft. Microsoft Software
- If you have a Capella MS Imagine account, go to Step 2. Otherwise, see the instructions for registering an account at MS Imagine -? Registration.
- Log in to the Capella Microsoft Imagine Webstore.
- Identify the version of MS Visio that is compatible with your operating system.
- Download and install.
- If you encounter any difficulties in the download and installation process, post a detailed question in the Ask Your Faculty Discussion in the menu dropdown when you click the image of your faculty. Note: As a Capella learner, you have access to IT online resources through Capella’s Skillsoft subscription, where you can find helpful materials.Instructions
A Vila Health Clinic has provided you, a data analyst for Vila Health, with the data points listed below. From these data points, you are to apply your knowledge of data modeling concepts and develop a data model for the clinic. Please be sure to do all of the following as you develop your data model:
- Structure the model to support the clinic’s business practices.
- Group the data points together under appropriate category headings.
- Identify each category with a short descriptive title.
- Use the symbols and notations found in entity-relationship diagrams.
- Data Points
- Consumer ID.
- Last name.
- First name.
- Date of birth.
- Sex or gender.
- Street address.
- City.
- State.
- ZIP code.
- Telephone number.
- Social Security number.
- Type of radiological test.
- Date ordered.
- Physician last name.
- Physician first name.
- Physician specialty.
- Physician ID.
- Physician telephone number.
- Insurance name.
- Insurance group number.
- Insurance type.
- Effective date.
- Expiration date.
- Diagnosis.
- Signs and symptoms.
- Presenting problem.
- Time of arrival.
- Time of discharge.
- Additional Requirements
- Length and Format: Data model using all data points created in Visio.
- Writing: Create a clear, well-organized data model that is generally free of spelling errors.
- Resources: Data Governance
- Buffone, P. N. (2016). The ‘cure’-all for 21st century data sharing. Pharmaceutical Executive, 36(8), 39, 50.
- Capella University Health Care Administration Undergraduate Library Research Guide.
- Please consult this guide as needed to conduct independent research on course topics. This resource will direct you to scholarly, peer-reviewed, and authoritative resources.
- Kadlec, L. (2014). Coming soon to your healthcare facility: Information governance – A look at healthcare information governance trends through practical case studies. Journal of AHIMA, 85(8), 26–32.
- Kersten, S. (2013). Moving the needle toward a data-driven health care system: Optimizing the EHR through information governance. Journal of Health Care Compliance, 15(3), 45–46, 62.
- Marbury, D. (2016). Interoperability: Dream vs. reality. Managed Healthcare Executive, 26(10), 29–31.
- Simon, N. (2016). The dread of data sharing. Health Management Technology, 37(8), 25.esources:
- esources: Data Modeling
- 1keydata.com. (n.d.). Data modeling – Conceptual, logical, and physical data models. Retrieved from
- Ambler, S. W. (n.d.). Data modeling 101. Retrieved from
- This article discusses the fundamentals of data modeling and how it is used in practice. Examine the sample data models.
- Arunachalam, S., Page, T., & Thorsteinsson, G. (2017). Healthcare data warehousing. i-Manager’s Journal on Computer Science, 4(4), 1–13.
- Lucidchart. (n.d.). What is a database model. Retrieved from
- Mazzali, C., & Duca, P. (2015). Use of administrative data in healthcare research. Internal and Emergency Medicine, 10(4), 517–524.
- Rho, M. J., Kim, S. R., Park, S. H., Jang, K. S., Park, B. J., Hong, J. Y., & Choi, I. Y. (2016). Common data model for decision support system of adverse drug reaction to extract knowledge from multi-center database. Information Technology and Management, 17(1), 57–66.
- Resources: Data Modeling
- 1keydata.com. (n.d.). Data modeling – Conceptual, logical, and physical data models. Retrieved from
- Ambler, S. W. (n.d.). Data modeling 101. Retrieved from
- This article discusses the fundamentals of data modeling and how it is used in practice. Examine the sample data models.
- Arunachalam, S., Page, T., & Thorsteinsson, G. (2017). Healthcare data warehousing. i-Manager’s Journal on Computer Science, 4(4), 1–13.
- Lucidchart. (n.d.). What is a database model. Retrieved from
- Mazzali, C., & Duca, P. (2015). Use of administrative data in healthcare research. Internal and Emergency Medicine, 10(4), 517–524.
- Rho, M. J., Kim, S. R., Park, S. H., Jang, K. S., Park, B. J., Hong, J. Y., & Choi, I. Y. (2016). Common data model for decision support system of adverse drug reaction to extract knowledge from multi-center database. Information Technology and Management, 17(1), 57–66.
- Competency 3: Use data analysis skills to support health information integrity and data quality.
Expert Solution Preview
To create a data model using Visio that supports a healthcare clinic’s business practices, the following steps should be taken:
1. Determine the data points that need to be included in the data model. The data points provided by the Vila Health Clinic include consumer ID, last name, first name, date of birth, sex or gender, street address, city, state, ZIP code, telephone number, Social Security number, type of radiological test, date ordered, physician last name, physician first name, physician specialty, physician ID, physician telephone number, insurance name, insurance group number, insurance type, effective date, expiration date, diagnosis, signs and symptoms, presenting problem, time of arrival, and time of discharge.
2. Group the data points together under appropriate category headings. For example, personal information such as consumer ID, last name, first name, date of birth, sex or gender, street address, city, state, ZIP code, telephone number, and Social Security number can be grouped under the category of “Patient Information.” Medical information such as type of radiological test, date ordered, physician last name, physician first name, physician specialty, physician ID, physician telephone number, insurance name, insurance group number, insurance type, effective date, expiration date, diagnosis, signs and symptoms, presenting problem, time of arrival, and time of discharge can be grouped under the category of “Medical Information.”
3. Identify each category with a short descriptive title. The two categories identified above can be labeled as “Patient Information” and “Medical Information.”
4. Use the symbols and notations found in entity-relationship diagrams to create the data model. Examples of symbols and notations that can be used include rectangles to represent entities, diamonds to represent relationships, and arrows to represent cardinality.
5. Construct a data model that supports the clinic’s business practices by ensuring that the relationships between entities are accurate and that all data is properly normalized.
By following these steps, a well-constructed data model can be created using Visio to support a healthcare clinic’s business practices.
