Course Description


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

Topics covered

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.

Analyst, Educator and Consultant at georgejmount.com

George Mount

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. 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. My online training is meant as a resource for recent grads and others who want to advance their career through Microsoft Excel, data analytics, and business economics.I've been featured on Excel TV, the Smart Data Collective, Brazen Careerist, and other blogs about business analytics and career development.

Course curriculum

  • 2

    Calendars and Scheduling

    • Calculating Working Days and FTEs with NETWORKDAYS

    • Building Shift Planners with Conditional Formatting

    • Building Shift Planners with Data Validation

    • Tracking Tenure with DATEDIF

    • Resources

  • 3

    PivotTable Revenue Analysis

    • Understanding PivotTables

    • Adding Calculated Fields in PivotTables

    • Heatmaps with Conditional Formatting

    • Color-Coding Variances

    • Importing data from Access

    • Speeding Up a PivotTable

    • Writing Access queries from Excel

    • Resources

  • 4

    Cleaning Up Exported Data

  • 5

    Dashboards and Visualization

  • 6

    The Future for Healthcare Analysts

    • Conclusion -- What Comes Next for the Analyst?

    • Resources