LIVE ONLINE COURSE
ON EXTRACTING VALUE
FROM HEALTHCARE DATA
20 JUL 2023 - 29 AUG 2023
Duration:
6 WEEKS
TUESDAYS & THURSDAYS
5 PM PT / 8 PM ET
Behind better patient outcomes and healthcare profitability, you'll find data-based insights — and the people who know how to extract them. Isn't it time you became one of them?
No matter your current healthcare role, gaining data analytics skills is the one thing you can count on to advance your career. Seamlessly move from theory to practice as you learn how to find, analyze, interpret, and present healthcare data over 6 dynamic weeks.
THIS COURSE IS FOR YOU, IF...
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YOU WANT TO GET UPSKILLED FOR THE DATA AGE
As your organization accumulates data, will you put it to use or get left behind? Now is the time to build the skills to navigate growing volumes of healthcare data. Whether you're in patient care, insurance, or administration, rise to the occasion with the ability to collect, store, retrieve, and present data with ease.
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YOU WANT TO TURN DATA INTO ACTION
Prepare to rise to the mandate of data-based decision making with crystal clear instruction and hands-on labs. You'll build the skills needed to understand the data in front of you, engage with data roles on your team, and act on the right recommendations. Still got questions after class? Just shoot Marc an email or catch him in office hours.
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YOU'RE A DATA NERD MOVING INTO HEALTHCARE
The healthcare industry stands apart from other areas of data analysis, yet it's often swept under the unspecific "data science" rug. In this course, Marc addresses everything specific to US healthcare that general data science training doesn't address: types of healthcare data, how to work with e-healthcare data compliantly, and the regulations that will impact your work.
Learn like you're already in the role.
You'll use data to respond to realistic healthcare scenarios from Week One. This course is packed with tools, case studies, real-world data sets, and data labs to train you for the complexity of real-world healthcare analysis.
Replace "figuring it out" with outstanding instructor support.
Gain unparalleled access to practice and support as a learner in a live, expert-led classroom. From weekly assignments and labs to insights over coffee during office hours, there's no better place to start converting your ambitions into hard skills.
Start using Excel, Power BI, and Tableau to manipulate data and extract value. You'll learn how to collect and organize health data to be ready for analysis as needed. Practice finding patterns in data and visualize them.
Build skills to confidently test hypotheses, work with qualitative data at-scale, and employ data storytelling. Be the leader in the room when it comes to making and presenting persuasive, data-based recommendations.
Advance your career with expert insights into healthcare analytics. Maximize this powerful resource for enhancing healthcare delivery with tips and tricks from Marc's own dynamic career.
VOORHEES LinkedIn Profile
- Executive Director in Analytics, Strategy, and Insights at DWA Healthcare Communications Group
- Over 10 years of experience in designing and building world-class analytics solutions at Pfizer, MPM Consulting, and Chaucer Consulting
- Led the development and implementation of Pfizer’s data warehouse to drive reporting and interface tools with higher quality healthcare data
- Passionate instructor and mentor, accomplished in building and mentoring top-performing teams.
COURSE INTRODUCTION
A number of factors are driving the increased role of advanced analytics in healthcare. You'll start your learning by contextualizing analytics within healthcare systems, understanding who the stakeholders are, and how organizations use data and analytics.
- What does healthcare data analytics look like?
- Types of analytics in healthcare
- Drivers of healthcare transformation and the role of analytics
Assignment #01
Write a short response to the following questions: So far, how have you used Excel for data and analysis? Do you see a role for Excel in assessing a variety of data and analysis in healthcare? Why or why not?
It's a topic that has been front and center for quite some time: data security, privacy, and governance at organizations. This class considers the appropriate application of privacy laws in various healthcare environments and the type of legal and ethical concerns you may encounter in regards to health data.
- Health data and the appropriate application of privacy laws
- Technical, administrative, and physical safeguards to minimize the risk of a data breach
- Ethical concerns and dilemmas in the use and disclosure of health data
Assignment #02
Find a recent data breach at a private company or government entity and describe it. Are there any indications in the information you found about how the breach could have been prevented? What are they?
Now that you understand the environment in which health data analysis is taking place, Marc will teach you the initial steps of analysis. You'll learn how to locate data and inspect it for regularities.
- Sources of healthcare data
- Data used for decision-making
- Importing data into Excel and data cleaning
- Missing data
- Managing data
- Merging and joining different sources of data
Assignment #03
Your office has been grappling with the worksheet in Dataset 3. In a team meeting, the issue is identified as swapping rows and columns. An assistant offers to retype the sheet such that the rows and columns are swapped.
You suggest that there is an easier way to accomplish this. Swap the current rows and columns so that years are now in rows.
This workshop gets you comfortable with descriptive statistics, charts, and figures. You'll get trained in two powerful tools for modern analysis, and build a vocabulary to discuss data.
- Define common data types
- Recognize common patterns or distributions in statistics
- Describe distributions using measures such as mean, median, and standard deviation
- Identify common graphs to represent data, including histograms and bar charts
- Demo: Tableau and Power BI
+ Workshop Hour #1: Introduction to Power BI
Assignment #04
You are an analyst with a health advocacy group. Dataset 1 contains data you'll present to your team. Your task is to analyze two fields: column F (Premature Death Value) and column K (Poor or Fair Health Value).
- What considerations will you be mindful of as you start to look at these data and prepare it for presentation?
- Use a pivot table to summarize information on these two fields at the state level.
- Prepare a chart that shows a comparison of five states with the highest premature death value.
- Prepare another chart that shows average poor or fair health value.
- Summarize the key points from your data analysis in two slides.
This class steps up from basic data representation to advanced chart and figure types. You will learn how to choose the right type of chart for your data and Marc will demonstrate visualizing data with 3D maps.
- Identifying your data
- Using pivot tables and other chart types
- Considerations for choosing a chart type
- Demo: Visualizing data in 3D maps
Assignment #05
With the continuing changes in healthcare reform, there is renewed interest in the early effects of the Affordable Care Act. Dataset 4 contains information on changes in the uninsured rate from 2010 to 2015 in each state. What specific question can you ask using this data? Make two slides demonstrating your questions.
In this class, you'll learn how to evaluate whether two means differ significantly and meaningfully from each other. Marc will offer a scenario to demonstrate how a healthcare organization makes these assessments in the real world.
- t-tests: Assumptions, two-sample means, paired means
- Longitudinal data and t-tests
- Demo: Visualizing data in 3D maps
+ Workshop hour #2: Instructor's choice
Assignment #06
The VA is concerned about the experience of customers at VA facilities. In 2017, HCAHPS surveys were completed in a large sample of VA facilities nationwide. Senior management is convinced that the problem is the variable "Communication With Nurses". Refer to Dataset 2 to better understand the role of this variable. Next, test whether there is a relationship between "Communication With Nurses" and "Patient Recommendation of Hospital".
Healthcare data does not always offer the luxury of comparing only two means. In this class, you will learn how to evaluate whether three or more means differ significantly and meaningfully from each other.
- Calculating ANOVA for three or more groups
- Creating categories
- Stating hypotheses
- ANOVA for longitudinal data
Assignment #07
For Dataset 2, which contains HCAHPS summary data for October 2018, how would you test if there is a difference in mean values for “Nurse Communication” across the high/medium/low categories of “Recommend Hospital”?
- Define high/medium/low categories for “Recommend Hospital” using the 75th percentile as cutoff for high and the 50th percentile as cutoff for medium.
- State your null and alternative hypotheses.
- Run a test to accept or reject your hypothesis. State your test statistics and interpretation of results.
Today, you will advance to comparing two or more variables. This workshop teaches how to evaluate whether there is a significant and meaningful relationship between multiple variables overall.
- Scatterplots and correlation
- Regression: Single linear and multiple
- Demos: Exploring relationships and patterns in Excel
+ Workshop hour #3: Tableau (Part 1)
Assignment #08
You have been tasked to better understand the health insurance market for individual health insurance plans. Use Dataset 4 to better understand the variable “Individual Market - Individuals With Marketplace Coverage (Q1 2016)". To better understand this variable, develop scatter plots and regressions model to interpret and predict various values, according to criteria provided by Marc.
A sample design is the framework, or road map, that serves as the basis for the selection of a survey sample. You'll learn how to determine the best type of sample design for different situations, and about the role of research design in health-related research.
- Research driven by questions
- Sampling
- Different types of sampling designs
- Research design
Assignment #09
You are working with the executive team at the Veterans Administration (VA). Your team would like to focus the attention of the executive team on specific issues that are flagged in the Consumer Assessment of Healthcare Providers and Systems in VA facilities.
Rather than show data from all facilities, you consider using stratified random sampling to select 40 VA facilities from Dataset 2. Use quartiles of the variable “Recommend Hospital” to create four strata and then identify 5 facilities from each stratum. For your sample, provide the average value for the variable “Recommend Hospital”.
Patient engagement in health research is becoming increasingly common. Today, you'll turn from quantitative data to learn how to analyze words instead of numbers in Tableau.
- Qualitative data in healthcare
- Qualitative analysis and Excel
- MeaningCloud Add-In
- Text classification
- Sentiment analysis
- Topic extraction
- Text clustering
+ Workshop Hour #4: Tableau (Part 2)
Assignment #10
You have just been handed patient reviews of a dentist (Dataset 5). Use the MeaningCloud Add-in in Excel to identify sentiments expressed by patients and caregivers.
- How would you start your analysis and what approach(es) to analyses will you adopt? Why?
- Prepare a summary of your analysis, including appropriate charts and figures.
How can the value of quality healthcare be understood in numbers? This class teaches you how to measure quality in healthcare, and why these measures are important for public and private stakeholders.
- Define healthcare quality and value
- Define measures, metrics, and indicators
- Describe the purpose and use of Key Performance Indicators (KPI’s)
- Describe how health care organizations achieve performance goals
Assignment #11
Use Dataset 1 to find the top 5 states in overall quality of life. Next, find the bottom 5 states in overall quality of life. What results allowed you to come to these conclusions?
Data is only as useful as it is understandable. In this class, you will learn how to present data to effectively tell the story of your findings.
- Tableau for data storytelling
- Display data so your audience can understand
- Select appropriate formats for displaying information
- Identify background information that should be included in reports
- Determine the best ways to communicate information with specific stakeholders
+ Workshop Hour #5: Resume and Interview Tips.
What our students say
"ELVTR Data Analysis in Healthcare course/modules is an eye opener to new opportunities. It has really helped me in my current job in the aspect of processing and analyzing the raw data we generate on a daily. Also the course is packed with plenty of information that are very useful in the management of the new analysis squad recently created in my organization. Thanks for this opportunity."
“This course contains exactly one of the things I needed learn to give my career a huge positive nudge, and the instructor is explicit in his teachings.”
"Understanding the fundamentals of Data Analytics that can be applicable in every type of industry."
"Wonderful Training with lessons in an organized and easy to navigate manner."
"Mr Voorhess knows how to communicate and convey the methods needed to be successful. I like that fact that he emphasizes that mistakes happen, but we must be confident and not afraid to make them, while willing to admit errors."
"I like the pace of the course and how well detailed every class has been. I think by breaking down the material piece by piece it gives us a chance to grasp each portion before ultimately putting the entire concept together. I personally learn better this way because it gives me a better understanding of the process as a whole."
"Overall, the course is interesting and important and can be used to improve our work."
"Marc really knows his material! I can tell he is happy to teach this subject and also passionate about his field. It makes me more eager to learn."
"The content is useful and practical."