Bed Capacity Management

The pressure of ever increasing patient demand and budget restrictions make bed management a daily and crippling challenge for clinical staff. All hospital departments are in some way dependent on bed availability.

Variation in Bed Planning

Variability in arrivals and lengths of stay and ensuring that patients are able to access the right inpatient unit for their condition add to the complexity of managing beds, all factors that simulation can help manage.

Too often we look at an average number of beds per specialty. Demand for beds from both elective and emergency patients, together with patient discharge delays creates pressure on hospital beds that builds over the course of the day. On average, it looks like there are enough beds, but the reality is that patients are often placed in a non-ideal unit if the right bed in the right unit is not available at peak demand, or they may have to wait in ER until the bed becomes available.

Read more on how variation undermines your bed planning

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The power to ask 'what if' in bed planning

Every decision in your hospital impacts on bed availability, and that impacts on overall patient flow. A change in one part of the hospital can improve or disrupt the overall system. You cannot take a silo approach to bed management, you must look at the system as a whole. This can’t be done in a spreadsheet, you need the sophistication of simulation. Simulation is the only method that can accurately answer questions like:

  • How could you manage your staff shifts better to more effectively meet demand?
  • What happens if you flex beds between specialties?
  • What rules do you need to set up to make sure certain patients go in certain beds?
  • And when those beds aren't available, what's the next best place to put them?
  • What happens when you have to close wards unexpectedly?
  • What happens if your patient mix changes?
  • What impact do community beds have, how many do you need?

Learn more about Bed.P.A.C. our simulation tool for bed planning

“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. ”

BedPAC has given our commissioners assurance on capacity that exists to deliver agreed demand plan with the exception of specific identified areas.”

IAIN HENDEY
Deputy Director - Information, Finance & Performance Information Service
Isle of Wight NHS Trust

Learn more about Iain's team have used simulation

Inpatient stays are one of the most expensive areas of healthcare

What would the impact of better bed management be for your organization? A patient in the wrong bed extends their stay by one day and increases their chance of mortality by 1.45%. Our Bed Management ROI Calculator will calculate how much better bed management could save you each month and more importantly how many lives it could save.


Bed Management ROI Calculator

Learn More About Simulation for Bed Management

Managing Bed Capacity Towards a Solution

SIMUL8 Executive Director, Health and Social Care, Claire Cordeaux introduces our bed management system Bed.P.A.C.

Claire showcases how Bed.P.A.C. helps improve long term planning and provides real time forecasting. What if you knew a bed crisis was going to happen, what could you do about it beforehand, in order to reduce any adverse impact?

How could you predict what the impact of changes might be whether they're policy changes, whether they're operational changes? And how could you understand that within that risk free environment that Simulation offers, to know what's likely to happen.


Watch the webinar

NAO Study into Maternity Capacity

Having a baby is the most common reason for admission to hospital in England. NAO investigated whether maternity services could adapt to changes in demand and whether there was sufficient capacity to meet the Department of Health’s objectives of providing one-to-one care during labour at all times.

Their simulation suggested that there were enough beds and that they could probably absorb a relatively substantial increase in demand but provided evidence that providing one-to-one care during labour would be very challenging.




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Cornwall acute and community stroke bed capacity modeling

Around 940 people in Cornwall have a stroke each year. Immediate treatment is provided at acute hospitals in Truro, Plymouth or Barnstaple. Around 40% of these patients will require follow-on care in a Rehabilitation Stroke Unit (RSU) based in community hospitals.

Currently patients can choose which RSU to attend, but patients who choose to attend Bodmin are often unable to access a free bed. These patients are either sent to an alternative RSU, increasing travel times for patients and their families, or wait in the acute hospital, which can lead to delays in transferring new patients from A&E to a dedicated stroke ward.


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Planning Bed Capacity in Specialized and Integrated Care Units

This paper looks at bed blocking in the Cardiac Intensive Care Unit at Morriston Hospital and its impact on bed capacity.

Different wards, e.g. general ward, Intensive Therapy Unit, High Dependency Unit, are organized to provide different levels of patient care as they progress through the treatment pathway. Bed blocking occurs when patients are clinically ready to be discharged from specialized wards can't be transferred to wards offering reduced care because of no beds are available.

This has implications on throughput of clinical activity, as well as patients’ cost of treatment.


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Simulating Acute Bed Capacity - 7 days a week

Improving emergency care is complex and depends on a range of factors including: daily and hourly variations, in patient demand, varying lengths of hospital stay, discharge practices, availability of health and social care services pre and post-discharge.

Understanding the impact of changing to 7 day working on the system is challenging, and stakeholders want to understand the resource implications for acute beds.

This project brought together the data and improvement evidence into a simulation that demonstrates best practice.


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Bed-occupancy in a critical care unit

The aim of the study was to optimize the number of beds available in order to minimize cancellations of Elective surgery and maintain an acceptable level of bed-occupancy at a Critical Care Unit (CCU) of a large teaching hospital.

The simulation seeks to simulate the bed-occupancy of the CCU as well as monitoring any cancellations of Elective surgery. Several ‘what-if’ scenarios are run including increasing bed numbers, ‘ring-fencing’ beds for Elective patients, reducing length of stay to account for delayed discharge and changing the scheduling of Elective surgery, and the results are reported.


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Simulating Future Delivery Scenarios for Acute Care

As part of reviewing the provision of emergency and unscheduled care, elective and rehabilitation services, NHS Ayrshire & Arran had to estimate the bed capacity requirements for all specialties under different care delivery scenarios.

Taking into consideration the volumes of patients attending the A&E departments and flowing through the different inpatient sites under various proposed models of care, they used simulation to aid decision making on the delivery of a range of services.

The paper reflects the difficulties in giving a recommended number of beds and the approach accepted.


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Demand and Capacity Modeling for Acute Services

Ever increasing demand with severe capacity and financial constraints, means NHS acute services will continue to struggle and needs to make sure that resources are utilized in the most effective way.

Acute services need to improve efficiency by enhancing the match of capacity and demand. They need to model the level of resources needed by patients in acute services as a function of demand factors, e.g. population projections by age group, with a range of supply issues.

It is vital to understand the patient pathway in order to demonstrate the full impact of change.


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Improving bed capacity management with Simulation

In this webinar our healthcare consultant Fiona Lindsey draws on recent simulation projects to consider the questions that need to be answered, the levels of complexity required and lessons learned for constructing simulation for bed management.

She describes how she worked with NHS IMAS to develop simulation to show the impact of 7 day working on bed capacity, and goes through the process of how she helped Royal Free tackle bed management. Fiona helped them build a simulation to understand their bed consumption by specialty for both emergency and electives and the impact this would have on their ER.

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