How simulation is used in healthcare
Pressure from rising patient demand and budget limitations make hospital bed management a day-to-day challenge.
Our Bed.P.A.C. simulation tool enables health teams to identify problem areas, predict shortages, and test solutions to mitigate a bed crisis before it happens.Learn about Bed.P.A.C.
Managing bed capacity is essential to the smooth running of a hospital since all departments are in some way dependent on bed availability.
As well as improving patient flow and outcomes, better bed management has been shown to save as much as $370,000 per month per hospital.
However, many hospital planners still rely on deterministic spreadsheets, based on average demand, to plan and manage bed capacity.
Without considering variation in demand, it could look like there are enough beds. In reality, patients regularly have to be placed in a non-ideal unit when beds are unavailable, or have to wait in the emergency department until a bed becomes available.
These delays and incorrect bed placement lead to significant costs for hospitals. If a patient in the wrong bed has to extend their stay, this costs $1,600 per day. If just 10% of patients are placed in the wrong beds, that’s $9,800 per day in additional costs.
Include variation for more accurate planning than spreadsheets.
Every decision made in your hospital has an impact on bed availability and in turn, patient flow.
A change in one part of the hospital could improve or disrupt the whole system, so you can’t take a siloed approach to bed planning and management.
Managing inpatient bed units is proving ineffective for staff as outdated tools like spreadsheet models don’t provide the answers to realistically support day-to-day planning.
Only simulation provides fast, accurate answers to these questions and many others.
Incorporating the variation in demand experienced by hospitals, staff can quickly and precisely forecast bed capacity requirements for both long term and real time planning.
Automatically build demand profiles for patient arrivals and length of stay from your historic data.
Using accurate distributions, you can better forecast demand, discover looming trouble spots and know when you’re going to run out of beds.
In one click, run a range of simulation scenarios to see the impact of changes in policy, staff shift patterns, patient volumes, length of stay and capacity on performance.
This enables safe experimentation to find solutions for increasing bed capacity and improving performance against waiting time targets.
Improve decision-making and get departments working together using a shared, visual and objective view of trends in admissions, length of stay, discharge and wait times.
Using the evidence provided by simulation, you can present the operational and financial implications of proposed changes to stakeholders.
Talk to us about your challenges, ask our healthcare simulation expert questions and explore Bed.P.A.C.’s features in a confidential demonstration.
NHS Isle of Wight used the Bed.P.A.C. simulation tool to change the use of existing beds, gaining 17% additional capacity for medical inpatients.
“Bed.P.A.C. has stood up to scrutiny from clinicians and managers within the Trust, consequently the results output have led to constructive discussions about solutions to issues rather than ongoing debates about the integrity of the modeling. Consultants have been particularly impressed by our ability to recognize the maximum bed requirements and how often a certain number of beds will be utilized rather than referring to average bed requirements.”
What would the impact of better bed management be for your organization?
Our bed management ROI calculator will estimate how much better bed management could save you each month and more importantly, how many lives it could save.
Could you avoid a bed crisis before it happened?
Find out how better bed management can save approximately $1.8 million per quarter per hospital AND improve patients outcomes.
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NHS Fife wanted to understand the impact of an aging population on demand for services, and to test the impact of the introduction of a virtual ward on bed capacity requirements.
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Dr. Paul Schmidt, explores how simulation is being used to model a new operational strategy for unscheduled care at Portsmouth Hospitals NHS Trust in the UK.
West Kent CCG used simulation to improve services for people at the end of their life including enabling people to die in the place of their choice.
Simulation was used at the Golden Jubliee National Hospital's heart and lung center to assess if an enhanced schedule would improve waiting times and cancellations, or if more radical changes, such as capacity or other resource reallocations should be considered instead.