Introduction to Health Care Data Analytics Module 4

Introduction to Health Care Data Analytics Module 4: Data Analysis Tools and Techniques Lecture a 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 90 WT 0002. Except where otherwise noted, this work is licensed under the Creative Commons Attribution-Non. Commercial. Share. Alike 4. 0 International License. To view a copy of this license, visit http: //creativecommons. org/licenses/by-nc-sa/4. 0/.

Data Analysis Tools and Techniques 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 2

Overview Data analysis “is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making” Wikipedia, 2016 Image by ©arka 38, Shutterstock 3

The Role of the Data Analyst Image by Ambro, 2011 4

The Process of Data Analysis Image by Ambro, 2011 5

Problem Definition Image by Ambro, 2011 6

Data Management Goal: Capture quality data and enable credible outcomes • Data Collection – Acquiring data from the source systems • Data Evaluation – Looking for data quality issues • Data Cleansing – Removing poor quality data • Data Integration – Combining data from disparate sources 7

Data Exploration Goal: Describe and determine need for further data refinement • Descriptive Statistics – Discover main characteristics of the data set • Data Structuring (Modeling) – Represent the data relationships to meet the analysis requirements Image by Ambro, 2011 8

Analyzing Data & Interpreting Results Goal: Obtain constructive information applied in answering questions, formulating conclusions, predicting outcomes, and supporting decision making • Data Mining: Identify patterns and establish relationships – – – Association Sequence Classification Clustering Forecasting 9

Analyzing Data & Interpreting Results – Continued • Data Segmentation: – Organize the data to facilitate the analysis – Enable correct interpretation of data • Data Visualization: – Aids in understanding and interpretation • Validation of Results: – Did we ask the right question? – Were the right questions answered? – Did we perform the analysis correctly? 10

Reporting Goal: Communicate key findings of the analysis • Tailored to Audience – Leadership – Stakeholder Image by Ambro, 2011 11

Summary of the Process of Data Analysis 12

Data Management Tools Images by Stuart Miles, 2014; Image by ©ramcreations, Shutterstock; Idea go, 2010; and Stuart Miles, 2013 13

Exploration, Analysis & Interpretation Tools Data Visualization Techniques Structure: Mining or Confirmation: Data looking for patterns or validation using trends • Frequency distributions • Histograms Examples: • Scatter Plots • Linear Regressions Examples: 14

Reporting Tools Data Visualization Techniques Graphical: Based on Geometrics: graphs Sophisticated visual • Bar charts representations • Pie charts of data • Line charts Examples: Image by Stuart Miles, 2015 Image by Daniel Tenerife CC BY-SA 4. 0, via Wikimedia 15 Commons

Summary Five steps of the data analysis process: • • • Problem definition Data management Exploration Analysis and interpretation Reporting of results Data analysts use various tools and techniques: • • • Process and clean Explore and visualize Mine and model Analyze and interpret Produce reports Image by Ambro, 2011 16

References: Data Analytics Tools and Techniques References – Lecture a Burns, Ed. (n. d. ). Data exploration. Retrieved from http: //searchbusinessanalytics. techtarget. com/definition/data-exploration Data analysis. (2016). In Wikipedia. Retrieved from https: //en. wikipedia. org/wiki/Data_analysis Hargreaves, C. (2013). The 7 -step business analytics process. Retrieved from http: //carolhargreaves. com/2013/08/31/the-7 -step-business-analytics-process Hemsoth, N. (2013). Six steps to extract value from big data. Retrieved from http: //www. datanami. com/2013/10/07/six_steps_to_extract_value_from_big_data Modern Analyst. com. (n. d. ). Data analyst role. Retrieved from http: //www. modernanalyst. com/The. Profession/Roles/Data. Analyst/tabid/189/Default. aspx Noble, S. (2012). One size does not fit all—Data segmentation #e-metrics. Retrieved from http: //www. stateofdigital. com/one-size-does-not-fit-all-data-segmentation Provost, L. P. , & Murray, S. (2011). The health care data guide: Learning from data for improvement. Case Study C: Reducing Post-CABG Infections. San Francisco: Jossey-Bass. Rouse, M. (n. d. ). Data scrubbing (data cleansing). Retrieved from http: //searchdatamanagement. techtarget. com/definition/data-scrubbing Rouse, M. (n. d. ). Data mining. Retrieved from http: //searchsqlserver. techtarget. com/definition/datamining 17

Data Analytics Tools and Techniques References – Lecture a – Continued Images: Slide 3: Arka 38. (n. d. ). Data analysis process. Purchased from Shutterstock. Retrieved from http: //www. shutterstock. com/pic-344758613/stock-photo-data-analysis-process. html ? src=v. CNZUOZiwmx 5 jc. EPev. Wc 7 g-1 -1 Slides 4 and 8: Ambro. (2011). Business people under discussion. Retrieved from http: //www. freedigitalphotos. net/images/Business_people_g 201 -Business_People_ Under_Discussion_p 46998. html Slides 5 and 16: Ambro. (2011). Elder businessman. Retrieved from http: //www. freedigitalphotos. net/images/Business_people_g 201 -Elder_Business_Man_ p 46956. html. Slide 6: Ambro. (2011). Business men and women in meeting. Retrieved from http: //www. freedigitalphotos. net/images/Business_people_g 201 -Business_Men_And_ Women_In_Meeting_p 46953. html Slide 11: Ambro. (2011). Business meeting. Retrieved from http: //www. freedigitalphotos. net/images/Business_people_g 201 -Business_Meeting_ p 46947. html. 18

Data Analytics Tools and Techniques References – Lecture a – Continued 2 Slide 13: Miles, S. (2014). Technology touch screen shows innovation improvement and hi-tech. Retrieved from http: //www. freedigitalphotos. net/images/technology-touch-screen-shows-innovationimprovement-and-hi-tech-photo-p 250806 Ramcreations (n. d. ). Business graph. Purchased from Shutterstock. Retrieved from http: //www. shutterstock. com/pic-110265173/stock-photo-business-graph. html? tpl=77643108110&irgwc=1&utm_campaign=Idee%20 Inc. &utm_ medium=Affiliate&utm_source=77643 Idea Go (2010). UP 3 D. Retrieved from http: //www. freedigitalphotos. net/images/Charts_and_ graphs_g 197 -UP_3 D_p 13889. html Miles, S. (2013). Question mark key shows doubt and help. Retrieved from http: //www. freedigitalphotos. net/images/question-mark-key-shows-doubt-and-help-photop 207228 Slide 15: Miles, S. (2015). Graph report represents trend graphics And finance. Retrieved from http: //www. freedigitalphotos. net/images/graph-report-represents-trend-graphics-and-financephoto-p 328836 Tenerife, D. (2010). Social red. Retrieved from https: //commons. wikimedia. org/wiki/File%3 ASocial_Red. jpg 19

Introduction to Health Care Data Analytics: Data Analytics Tools and Techniques Lecture a 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 90 WT 0002. Version 1. 0/Fall 2016 20