More than any other, one question we repeatedly get asked is “how many beds?”. Whether planning, improving patient flow, speeding-up discharge, producing business cases or responding to Covid-19, bedded capacity is frequently the biggest factor affecting both efficiency and outcomes. Robustly analysing patient flow and bed utilisation can drive effective decision-making and can facilitate future planning.
Edge Health has been engaged in helping multiple NHS Trusts to forecast their bed requirement and analyse the drivers of bedded pressure to support planning.
Mitigating risks and optimising bed planning
While monitoring bed requirements relative to the Trusts’ capacity is crucial, it is equally important to understand the underlying factors driving the demand for beds in a hospital. Taking this into account, we identify primary drivers of bed demand using detailed patient and ward level data to simulate bed requirements in an NHS Trust. These scenarios have been instrumental in aiding the planning of bed requirements in the Trust as they provide useful insights for effectively managing the Trust’s capacity.
It is very important to recognise the significance of understanding the variation of bed occupancy for the efficient calculation of the monthly bed requirements of a Trust. Hospital bed occupancy varies by minute and hour or each day – particularly for wards with short length of stay and quick turnaround times. Due to this variation, simply calculating the average number of occupied beds at the end of each day can misrepresent average occupancy levels and be unreconcilable with the experience of ward staff.
Variation in hourly bed occupancy over time
Our modelling approach
Detailed patient level data forms the basis of our analysis. To further understand the Trust’s capacity, we’ve also engaged with the staff to dive deeper in the wards structure and capacity, as well as any potential future capacity changes (including opening/closing of wards).
Utilising the available data, the key steps in our methodology approach are:
Calculating total number of occupied beds using hour-by-hour patient level data, accounting for the variation in hourly data.
Using the detailed ward allocations, aggregating the data on a division/ward/specialty level.
Exploring requirements for achieving different levels of target occupancy.
Creating multiple simulation scenarios to explore critical drivers of demand:
Variation and impact of length of stay.
Impact of ‘medically safe for transfer (MSFT)’ patients on capacity.
Effects from changing numbers of elective and non-elective admissions.
Influence of interventions like virtual wards.
Employing a flexible modelling approach enables us to gain valuable insights and understand crucial aspects related to bed planning in a Trust. The main advantages of our approach include:
Capturing the relationship between key variables in the analysis and measuring their influence.
Quantifying the impact of areas of uncertainty in bed planning.
Leveraging the potential outcomes of interventions to develop effective strategies and optimise resource allocation.
This modelling approach serves as a powerful tool in aiding bed planning and driving critical strategic decisions within the Trusts.
See more examples of our work on bed modelling here:
Elevating Performance and Driving Clinical Excellence: the Discharge Pathways Model Analytical Tool
As the NHS grapples with ever-growing demand for secondary care from the elective backlog and aging population, establishing an efficient patient flow out of secondary care is fundamental for alleviating system pressures.
Minimising acute capacity required for delayed discharges and ensuring patients have the right level of support available to them upon discharge, at home or in a community bed, will not only reduce costs for the NHS and free up the resources for those who need them most, but also help achieve better outcomes for patients.
The importance of access to accurate and up-to-date data in trying to accomplish this is paramount.
Answer the right questions
Assessing the level of demand, identifying system bottlenecks, and linking local practices with patient outcomes are all crucial undertakings on the path to better managed care.
The important questions like “How many patients are expected to be discharged into the community?”, “What causes the majority of delayed discharges” or “What can I learn from my peers who are performing better?” need to be carefully considered and answered on both system and national levels.
Edge Health has been commissioned by NHSEI to support them in tackling the complexities of the interface between secondary and community care and improving the patient flow.
Working with a multi-stakeholder group, including academics, clinicians and system leads, and in collaboration with the national rehabilitation team, we have developed a Discharge Pathways Model Analytical Tool, hosted on the NHS Foundry Platform, that facilitates access to the most up-to-date data that can be used to address those questions.
Benchmarking interface, part of the Discharge Pathways Model Analytical Tool
A one-stop place to benchmark, learn, and plan
The tool allows systems to benchmark their performance against their peers to identify areas of success and avenues for improvement.
It opens up a conversation around what can the systems learn from each other’s experience and provides crucial insights to the national team, informing a larger clinical effort to develop best-practice for care in the community.
Scenario modelling capabilities for effective bed planning
The modelling element of the tool allows the users to explore different models of care that can be implemented and thus support the planning activities for this winter and beyond.
The tool is now live and accessible to users across all the 42 systems, as well as the regional and national users.
A Proactive Solution to Bed Configurations: Using Simulation to Challenge Narratives
Being able to plan proactively to devise flexible bed configurations is a major challenge for Trusts that strive to improve the services they provide to patients and meet their changing needs.
Edge Health was recently approached by a large specialist Trust that wished to better understand their bed requirements. The Trust wanted to challenge the existing narrative within the organisation on the number of beds required and gain the ability to simulate initiatives such as building new theatres, adjusting case-mix, or achieving national or peer benchmarks for length of stay.
Our expert solution
To meet these needs, Edge followed a tried and tested three-step bed modelling approach, now implemented at several Trusts, which balances efficiencies from using existing frameworks together with bespoke tailoring to ensure a good fit for local circumstances.
Here are the key steps of our approach:
We collected detailed hour-by-hour patient data by ward, team and procedure to gain a deep understanding of the Trust’s current bed usage.
We engaged with individuals in the wards and across the Trust to understand the wards structure, usage, capacity and any future changes, and collect requirements for the bed model.
We built an interactive simulation tool to reflect the Trust’s risk preference and occupancy rates. We built several iterations of the tool to ensure it fully fitted the Trust’s needs.
A product built to last
The model is now used within the Trust to scope the building of new theatres, change the booking of patients to achieve more constant bed occupancy, and plan for next year. We received excellent feedback from our client, who praised the interactivity and the built-in ability for lateral thinking.
Finally a bed model that you can play with, use to challenge narrative and look at things from different angles. Not just a report. I really like it
– The trust’s COO
We look forward to continuing to help healthcare organizations make data-driven decisions. If you have any questions or would like to know more about our approach, please don’t hesitate to get in touch.