[Note: When I planned this post for National Physicians’ Week, I would never had imagined what our physicians would be battling. Thank you all for your front-lines service in this pandemic. You are the reason I can stay home and write blog posts like this.]
Most physicians have become rightfully suspicious of computers. They are undergoing alert fatigue. They did not go to medical school to become computer scientsts.
And you as a patient probably did not go to see a computer, either — you want to talk to a person, not the person’s back and a keyboard.
Doctors improve lives daily.
They also get stuck with administrative tasks daily. They are put in administrative roles where they need to analyze budgets or forecast utilization rates.
Excel provides a fantastic foray into data cleanup and automation for everyone, doctors included. As I’ve said before, I paradoxically have put so much into learning Excel so that I can spend less time in it: that is, the more I can be efficient and automate my workbooks, the less time I need to spend doing menial tasks in it and the more time I can spend on the operations that matter.
My hope for this workshop is that, with a bit of digital Excel literacy, physicians can regain if just the slightest amount of autonomy over their workflow.
Here is my half-day workshop learning guide on Excel for physicians.
Lesson 1: Data cleaning
Objective: Student can clean and manipulate data extracts
Description:
- Parsing cost centers
- Merging clinical and payroll data
- Working with string and date functions
- Consolidating data sources
- Importing and cleaning external data extracts
Functions/tools used:
- Identifying and removing duplicates
- Custom cell formatting
- String and date functions
- LEFT(), RIGHT(), MID(), text-to-columns
- VLOOKUP()
- Power Query
Time: 50 minutes
Lesson 2: Analyzing clinical data
Objective: Student can prepare, inspect and analyze clinical data
Description:
- Evaluating patient safety data
- Ranking patient satisfaction scores
- Comparing healthcare cost and utilization
- Investigating prescription history
Functions/tools used:
- Sorting and filtering
- Math functions
- PivotTables
Time: 50 minutes
Lesson 3: Analyzing operational and financial data
Objective: Student can perform basic financial data analysis
Description:
- Summarizing data by cost centers and units
- Creating calculated fields
- Heatmaps for variance analysis
- Conditional formatting for variance analysis
- Finding top and bottom values per category
Functions/tools used:
- PivotTables
- Conditional formatting
Time: 50 minutes
Lesson 4: Visualizing performance
Objective: Student can build dynamic visualizations
Description:
- Monitoring trends at-a-glance
- Monitoring performance across units
- Building dynamic date-based visualizations
- Forecasting trends
Functions/tools used:
- Sparklines
- Slicers
- Named ranges
- Chart forecasting
Time: 50 minutes
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