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Introduction to Health Care Data Analytics

Introduction to Health Care Data Analytics. Module 4: Data Analysis Tools and Techniques. Lecture c, Databases Part II.

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Introduction to Health Care Data Analytics

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  1. Introduction to Health Care Data Analytics Module 4: Data Analysis Tools and Techniques Lecture c, Databases Part II This material was developed through a collaboration between Bellevue College and the Veterans Health Administration, U.S. Department of Veterans Affairs, funded in part by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology award number 90WT0002. Except where otherwise noted, this work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.

  2. Learning Objectives • Define data analytics terms • Describe the process steps of data analytics and the tools used in each step • Describe the role of the data analyst • Identify tools and techniques used to analyze and interpret health care data effectively • Describe key database concepts. • Describe the various types of databases and how they are structured • Describe key data warehouse concepts • Describe enterprise data architecture as seen in health care organizations

  3. Overview This lecture further explores the various conceptual models of database designs and types of queries Image by Stuart Miles, 2014

  4. Types of Databases • Databases and database management systems (DBMS) are categorized by structure (how the data is related or organized) • Example database models: • Flat file • Hierarchical • Network • Relational • Object oriented

  5. Flat File Database • Contains one table without any structured relationship between the records • Advantages: Simple, all records stored in one place, easy to search and filter • Disadvantages: Cannot handle large volumes of data, data redundancy, low data security, multiple versions • Example: Microsoft Excel spreadsheet

  6. Hierarchical Database • Widely used on mainframe computers in the 1960s; found today on older systems • Data is organized in a tree-like structure • Each child record has one and only one parent (1:1) • Each parent record can have one or more child records (1:M) • Relationships are organized using address pointers linking records • Start at the root to retrieve data • VA (VISTA) is a hierarchical database Shelly, Cashman & Rosenblatt, 2003 Image by Brandt, K., 2016

  7. Hierarchical Database:Parent-to-Child Relationships Image by Brandt, K., 2016

  8. Hierarchical Database Example Image by Brandt, K., 2016

  9. Hierarchical Database: Advantages & Disadvantages Advantages • Able to handle large volumes of data • Able to map simple business processes (one to many) • Improved data integrity, data security, data sharing, and access speed Disadvantages • Not user friendly • Data structural dependencies • Cannot model all types of relationships • Reduced flexibility • Lack of standards

  10. Network Database • Similar to the hierarchical database in structure except that each child entity can have more than one parent • Each relationship called a set • Each set contains a parent record (owner) and child (member) • Not widely used today but may exist in legacy systems • Advantages: Map complex relationships, improved structural dependencies • Disadvantages: Still not user friendly Image by Brandt, K., 2016

  11. Relational Database • Most common type of database • Tables are connected via primary and foreign keys • Primary key (PK): Unique identifier for each distinct row within a table • Foreign key (FK): An identifier that is a primary key in a different table • Relationship between PK and FK are displayed using an entity relationship diagram or E-R diagram • Examples: Microsoft Access, SQL Server, MySQL, IBM DB2, Oracle Database

  12. Entity Relationship Diagram(E-R Diagram) Image by Brandt, K., 2016, using Microsoft Access Northwind sample database

  13. ER-Diagram Example • One patient has one or more appointments • One or more appointments are scheduled for one patient Image by Brandt, K., 2016

  14. Relational Database:Advantages & Disadvantages Advantages • User friendly • Complete data structure independence • Improved security with privilege access control • Reduced data redundancies • Perform ad hoc queries with SQL Disadvantages • Costly to set up and maintain • Changes between the relationship between tables may affect other relationships within the database • Multiple versions

  15. Object-Oriented Database • Developed for more complex data types (images, audio, and video) • Represent real-world objects • Data and their relationships are in a single structure Advantages: • Can store more complex types of data Disadvantages: • Not user friendly • Lack of marketing interest • Lack of standards • Decreased flexibility

  16. Object-Oriented Database Example Image by Brandt, K., 2016

  17. Flat & Hierarchical Databases: Advantages & Disadvantages

  18. Network & Relational Databases: Advantages & Disadvantages

  19. Object Oriented Database: Advantages & Disadvantages

  20. Query • A question answered by the database • May use various methods, such as Structured Query Language (SQL) and Query-by-Example (QBE) • Results presented on screen to be saved or printed

  21. Query Example Query-by-Example (QBE) Images by Brandt, K., 2016 SQL Statement Query Results

  22. Summary • Conceptual database model: • A database structure using entities, attributes and instances • Depicts relationships between entities • Follows business rules • Types: Flat, hierarchical, network, relational and object oriented • Database queries can be performed using SQL and QBE methods

  23. Data Analytics Tools and Techniques References – Lecture c References Capron, H. L., & Johnson, J. A. (2004). Computers: Tools for an information age (8th ed.). Upper Saddle River, NJ: Prentice Hall. Rob, P., & Coronel, P. (2004). Database systems: Design, implementation & management (6th ed.). Boston: Course Technology. Shelly, G. B., Cashman, T. J., & Rosenblatt, H. J. (2003). Systems analysis and design (5th ed.). Boston: Course Technology. Images Slide 3: Miles, Stuart (2014). Database magnifier shows bytes magnification and computing stock photo. Retrieved from http://www.freedigitalphotos.net/images/database-magnifier-shows-bytes-magnification-and-computing-photo-p294453 Slides 5–8, 10, 12–13, 16: Brandt, K. (2016). Graphics

  24. Introduction to Health Care Data Analytics: Data Analytics Tools and TechniquesLecture c This material was developed through a collaboration between Bellevue College and the Veterans Health Administration, U.S. Department of Veterans Affairs, funded in part by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology award number 90WT0002.

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