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Staffing Strategy
1. How Can Data Science Reduce Wait and
Cost in an Emergency Room?
A Service Disabled Veteran Owned Small Business
2. 2
Emergency Rooms Have Highly Uncertain Demand
Leading to Chronic Understaffing and Overstaffing
Which Demand Percentile Balances the Risk of Understaffing
against Cost?
PROBABILITY
Average Demand
Increasing Risk of
Chronic Overstaffing,
High Cost
Increasing Risk of Chronic
Understaffing, Long
Waits, LWBS
Predicted Patient Demand
.
PATIENT DEMAND
3. RPG’s Team of Data Scientists Predict Demand, Simulate
Performance and Develop a Staffing Strategy
.
A Staffing Strategy
maintains or improves
operational effectiveness
while minimizing cost
Staffing Strategies guide
scheduling, enabling
departments to:
Support performance goals
the right staff at the right time
Manage costs
minimize FTE & hours worked
STRATEGIC
TACTICAL
3 Remove “Guesstimation” From Planning
Planning
Operational
Staffing
Detailed
Scheduling
1
2
3
4
5
RPG Model of Staffing
and Scheduling Activities
4. 4
Understanding Current State Planning
• Staffing & Scheduling
Policies
• Manpower
Requirements
.
Planning
Operational
Staffing
Detailed
Scheduling
1
2
3
4
5
What are your
goals?
Do you have a
substantiated plan in
place to achieve them?
• Performance Goals
• Financial Goals &
Staffing Budget
5. 5
Model and Predict Patient Demand
Predict Future Patient
Demand
Collect
Historical
Data
V11139950091
Apply Data
Science Techniques
• Hour-of-Day
• Day-of-Week
• Month
• Season
• Holidays
• Special Events
• Long-term Trends
Key Factors:
Historical Data and Advanced Data Science Techniques
Reduce the Uncertainty of Future Demand
• Operational Staffing is driven by patient demand
• RPG method: Historical data + data science techniques =
accurate demand predictions
.
Planning
Operational
Staffing
Detailed
Scheduling
1
2
3
4
5
6. 6
Develop Scheduling Targets
Scheduling Targets
Understaffing
Overstaffing
Comparing an actual schedule against scheduling requirements
typically reveals both over and understaffing
.
Planning
Operational
Staffing
Detailed
Scheduling
1
2
3
4
5
• Patient demand and Staffing and Scheduling Policies
enable the calculation of scheduling targets for each staff
type
• Scheduling targets are compared against actual schedules
Scheduling
Performance Metrics
•% Overstaffed
•% Understaffed
•Schedule
Efficiency
7. # Constraint FTE
Impact
Cost
1 12 Hour Shifts 11 $1232k
2 Midshift start
times
6.5 $878k
3 10 Hour Shifts 5 $643k
55 3 consecutive day
rule
1.2 $84.4k
56 Day shift start
times
0.8 $49.6k
7
Analyze Cost of Business Rules, Define Shifts & FTE
Requirements
Each constraint:
• Increases the total number of staff required to fulfill a
schedule (increases fixed cost)
• Decreases scheduling efficiency (increases total hours
worked higher variable costs)
.
Planning
Operational
Staffing
Detailed
Scheduling
1
2
3
4
5
…
…
…
…
FTE Requirements
Shifts Definitions
Advanced
Analytical Model
9. 9
Case Summary
.
• An Emergency Department in the Southeastern United States
seeks to improve performance
• RPG identified that staffing and scheduling activities were not
aligned to demand, and optimized them resulting in
significant performance gains while reducing costs
Performance Indicators Before Target After
Door-to-Doc (min) 52 30
Length-of-Stay (min) 141 120
LWBS (%) 0.71 < 2.0
105
0.08
Initial Annual Staffing Cost: $2,536,000
Projected Annual Staffing Cost: $2,208,000
Projected Annual Savings $328,000
27
12.9%
Savings
See a Dr.
25 min
Faster!
Note: Initial annual staffing cost and savings calculated to show costs savings and cost avoidance.
The site in this case study was not meeting demand prior to changes. Given existing policies it would cost the site
2.536M annually to meet demand. Actual annual spend at site while not meeting demand was $2.375M. Savings
versus actual spend is 7% annually
10. Contact
David Gilinson
Chief Data Scientist
dgilinson@staffsked.com
dgilinson@reefpointgroup.com
914.714.8252
A Service-Disabled, Veteran-Owned Small Business
410.267.0413
3168 Braverton St Suite 280
Edgewater, MD 21037
Hinweis der Redaktion
Overview
Data science and advanced analytics
Personal Introduction
Senior management consultant
Systems engineer, experience using data to improve processes in a number of industries
Will talk more at end
If you staff to the average demand, you should expect to be understaffed about half the time, and overstaffed about half the time
If you staff to your worst case scenario, you will be chronically overstaffed, and spend far too much
We help quantify
So, you need to staff somewhere in between. We have found that generally this is around the 80th percentile, however each department has its own risk tolerance, and it is important to calibrate staffing decisions based on this tolerance.
Stratified – ESI 1 vs ESI 5
Enables communication
----
The graphic to the shows that there is a probability distribution associated with our predictions of future demand. If we schedule to average or (really median) demand, the EDs would be understaffed half of the time. So clearly, we need to staff to above that level. But how far above it? If we staff to the worst case scenario, say the 100th percentile, the busiest day we think is possible, we would be chronically overstaffed and will incur very high costs.
We have found that from our experience that the 80th percentile of demand is a best practice staffing level. That way we are adequately staffed the vast majority of the time, while balancing the risk of overstaffing. However this level can be tailored to the risk tolerance of individual departments.
DiGiorgio: may still not understand following the explanation provide an example to illustrate (staffing to 100 percentile, worst day, always enough staff but almost always too many people and inherently wasteful); ask if there are questions following the presentation of this slide
The first step is understanding what you want to achieve
We do this as a consulting service, not just some tool
For example there is tradeoff between performance goals and budget. do you have physicians available to reduce your door-to-doc time? Or will this number of docs cost more than you have targeted to spend?
Per DiGiorgio:
Speak to examples for performance goals (ie performance throughput) and financial goals (ie budget); are they working against each other, etc.
Jim:
Add examples to voicetrack – tradeoff between performance goals and budgeting
Use historical data and data science to predict future demand
Many EDs “predict demand” by running reports from their EMR and looking at simple averages, which tend to be inaccurate
We’ve done market research to see where we are at, there are a lot of tools out there that use lr/poisson distributions
We have experts in applied mathematics that take this a step furthe
----
However, simple averages are not the best predictions we can make. Using data science, we can evaluate demand patterns and develop more accurate estimates of future demand. For example, demand may vary weekly, monthly or seasonally. Additionally, special events and holidays may drive patient demand. And, patient demand may vary differently for different subpopulations segmented for example on acuity or age. It is valuable to consider these and other factors when predicting future demand.
We can quantify how well you are scheduling Physicians, nurses, and PAs
As we make improvements, we can see these metrics improve
Comparing an actual schedule against scheduling requirements typically reveals both over and understaffing
% Overstaffed: The percent of hours per week that too many resources are scheduled
% Understaffed: The percent of hours per week that too few resources are scheduled
Schedule Efficiency: Required / Total Man-Hours Schedule
Define constraints
For example – if you only allow 12 hour shifts
Constraints are not always obvious, you probably have more than you realize
Every rule adds cost, we help you understand how much
For example how much would you save if you changed your shift lengths?
Would it be worth it?
Example: nurse start times
------
Additionally, we perform an in-depth analysis of scheduling constraints so that departments can better understand their impact. In reality, any rules about how you schedule staff will cause some misalignment with demand, and decrease your staffing efficiency. Generally because understaffing must be controlled to acceptable levels you will need additional FTE every time you apply a scheduling constraint. This translates directly to higher costs for the department. Therefore, eliminating staffing constraints is an effective way to increase margins.
Its not practical to eliminate all scheduling constraints. As you know, it is very difficult to change schedules without significant pushback from staff. This is because schedules have more than a professional impact on people, schedules effect their personal lives. RPG, as part of our staffing and scheduling service offering performs an in-depth review of all scheduling constraints in your department. Our analysis enables you to make targeted changes that will have a large impact, rather than potentially upsetting staff over scheduling changes that have little or no impact on your bottom line.
People live with constraints. They are not always obvious
Once all of this analysis is complete, we document our findings as a Staffing Strategy. This document provides a guide for Departments to capture the value identified by our data-driven techniques.
