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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