This course is closed.
Healthcare data is messy — learn how to control it with Excel
Highlights of this course:
Addresses solutions in Excel for real-life problems of working with healthcare data
Over two hours of video training — download them, yours to keep forever
Downloadable exercise files — follow along with the course
Discussion forum — ask questions and talk about the course with the instructor and other students
Why healthcare professionals should learn Excel
Healthcare is probably the most complex industry, so it should follow that its data is hard to handle.
In my three years of experience as a healthcare business analyst, here’s what I found most difficult.
- Data is not joined — you must consolidate data from multiple sources for analysis
- Payroll and scheduling — every department schedules differently, and you’re left with a stack of calendars
- Revenue analysis — making sense of how charges are generated and trending
- Data cleansing — importing data from legacy systems with difficult data formatting, or coworkers who don’t know better
- Creating dashboards and reports that guide clinical decisions without distracting or overpromising
Excel can solve these pain points.
Who should take this course?
This course is best for:
– Current healthcare administrators and analysts looking to make sense of their data
– Nurses, physicians, and other clinical providers who are moving into managerial roles
– College and medical students who want a distinctive skill set as business leaders
Lesson 1 – Introduction
Why exactly is healthcare data so messy, and how can Excel help?
Lesson 2 – Scheduling and Personnel Management
Payroll is the most significant operating expense of a hospital. Yet there’s often no consistency or control in how people are scheduled. We will cover how to build schedules and payroll reports in Excel.
Lesson 3 – Revenue Analysis with PivotTables
Healthcare revenue is difficult to analyze. What departments or codes are they coming from? How are the collections? Trends can change on a dime. PivotTables can keep up. We’ll cover how to analyze revenue with PivotTables.
Lesson 4 – Cleaning Up Exported Data
Data often comes from legacy systems in hard-to-use formats. We will cover how to transform this into ready-to-use data with Excel.
Lesson 5 – Dashboards and Visualization
Dashboards and visualizations can make data easier to understand and act upon. But with poor design and project management principles, they will fail miserably. We’ll cover the basics of dashboards in Excel.
Lesson 6 – Conclusion
You know Excel — what’s next? I’ll share some thoughts on what the future means for healthcare analysts.
I like helping people manage their data so they can think more creatively.
Armed with a liberal arts degree and a master’s from a leading business school, I set out into the world to become an amazing analyst.
Over the past few years I have worked on projects ranging from Canadian retailing to neurosurgeon compensation.
While I had big ideas about making an impact to the business, I felt drowned and overwhelmed in the data. There was no way to see the forest, because I was stuck in the trees of confusing spreadsheets.
Through this experience, I’ve noticed patterns of what makes a good analyst. Specifically, I’ve seen the best and worst in Microsoft Excel and data analysis.
RankedBlogs.com and Feedspot.com have both recognized me as a top online authority on Excel. This mastery forms the basis for posts on business analytics, career management and innovation which have been featured on leading sites like Excel.TV and Brazen.
As featured on:
More about me…
I hold a bachelor’s in economics, magna cum laude, from Hillsdale College and two master’s degrees from Case Western Reserve University’s Weatherhead School of Management, in finance and information systems.
I have also completed a certificate in business analytics from Indiana University’s Kelley School of Business as well as a Certificate of Achievement in Quantitative Methods, also from Weatherhead.
Contact me at firstname.lastname@example.org