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Managing Bed Capacity
Towards a Solution
Claire Cordeaux Executive Director of Healthcare
The challenge…..
0
5
10
15
20
25
30
35
Num
ber
of
Beds
Actual Beds What actually happens
Inefficient
Increased mortality rates
Managing variation in bed planning
We asked 20 hospitals and service
improvers….
What you need…..
What we really want
Prevent delays
Ensure patients get to the right bed
Manage variable demand
Utilize beds efficiently
Deliver great patient care
1. Staff shift patterns are changed?
2. Patient mix changes?
3. Beds are flexed between specialties?
4. Short and long term ward closures?
5. Length of stay changes?
6. Discharge planned in advance?
7. Services outside hospital change?
8. Bring forward decision-making
What
If…
Introducing……
Bed.P.A.C.
Bed.P.A.C. Experiment Freely. Plan Confidently.
What if you knew a bed crisis was going to happen before it
happened? Could you do something to reduce its impact?
The Benefits
PREDICT
Gain insight into how your
policy changes will impact
your bed occupancy. Test,
plan and experiment in a
risk free environment.
Know when you’re going
to run out of beds need.
ACT
Improve the patient
experience by testing the
impact of improvement
decisions on cancellations,
waits and costs. Be
confident that your
decision is the right one for
costs and patient care.
COMMUNICATE
Get departments working
together on patient
placement decisions.
Shared forecasts give
shared visibility.
Avoid costly cancellations and long inpatients
waits by making decision today that will help drive
improvement tomorrow……..
Key Features
Import your data Auto builds
demand profiles
Visualize trends in arrivals, LOS,
discharges
Simulation engine,
variability…
Easily experiment by changing any
input parameter
Prebuilt what if scenarios
Fab Reports to share
Run forward All online – access it anywhere
…and the one feature that will transform how you operate every day……….
Near Real Time………..
Near Real Time
Stop dealing with crisis when they’re happening. Gain insight
into your bed occupancy levels over the next 7 days to help aid
decision making now and reduce the impact of your pending
crisis. Be a bed ahead.
How it works……
For long term planning
Input Your Historical Data
Import 1 year of data from
your internal system.
• Admissions
• Discharges
• LOS
• By Cohort, Month, Day
and Hour
1
Bed.P.A.C uses
your data to
automatically build
the parameters for
your simulation.
You can easily
change these
parameters
manually too if you
need more control.
Auto build 2
You select a period to run
Bed.P.A.C for
• 1 Month
• Quarter
• 1 Year
Bed.P.A.C will run using your
historical data and trends.
Simulate 3
Bed.P.A.C will output results for a typical week for each month. A typical week will show you predicted daily and hourly patterns of:
• Number admissions
• Number discharges
• Wait Time
• Number of Outliers
• Ave/Max Beds in Use
• Empty Beds
Results 4
Now you can experiment with changing inputs to
see the potential impact of your improvement
initiatives.
• Increase/decrease arrivals
• Increase/Decrease LOS
• Change Discharge Pattern
• Change number of beds
Experiment 5
Bed.P.A.C will give you a report based on
the baseline and experiment results to
inform your bed capacity plan each year.
It can also be used drive regular
improvements to the department.
Report 6
How it works……
For short term planning
Bed.P.A.C links with your internal systems and reads recent patient logs. This populates Bed.P.A.C with your current bed occupancy and patient mix.
Run Bed.P.A.C and it will animate and visually show what happened and pause when it reaches your current state.
Populate Current State 1
1 year historic data
‘3’ weeks historic data
Real patient data (today)
Starting from the current
bed state, choose to run
forward for 1 – 7 days.
Bed.P.A.C. will predict
from your current state
using the historical
trends data.
Predict 2
3 weeks recent data
Real patient data (today)
Use historic data to predict
7 days
After the run users will see a summary results
screen which highlights potential problem days.
Results Overview 3
Each day has detailed results by hour of the day
which highlight clearly where problems might
occur and at what time.
Result Detail 4
When Bed.P.A.C. shows problem days you can
experiment with different parameters to decide
what could help avoid the crisis.
Experiment 5
Let’s see it in action……
The impact……
Small improvements make a
big difference
Make decisions
Users can make daily bed placements
decisions with confidence based on
evidence.
Bed.P.A.C. can be run every day to continue
to give accurate near time results for bed
placement.
This is an expensive problem
A patient in the wrong bed costs
• A patient in the wrong bed extends their stay by 1 day, costing $1,600 per day per patient
• If just 10% of patients are in the wrong bed that’s $10,000 per day
A patient in the right bed has better outcomes
• A patient placed in the wrong bed has increased mortality of 2.57%
• If just 10% of patients are placed in the wrong bed, that’s 26 lives per year that can be saved
Cancelled Ops cause patient pain and lose income
• 4% of scheduled surgery is cancelled for non surgical reasons
• Surgery generates revenue around $1,500 per case. That adds up to $75,000 per month in lost revenue.
• Cancelled ops leave your whole team idle. Your anaesthetist, surgeon and nurses. That’s also wasted time and money.
Better bed management can
save you $370,000 #
per month per hospital and give
patients better outcomes.
Get involved
SIMUL8Healthcare.com/bedpac-join
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