“How many beds?”: Enhancing planning with bed requirement simulations

Overview

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:

1. Calculating total number of occupied beds using hour-by-hour patient level data, accounting for the variation in hourly data.
2. Using the detailed ward allocations, aggregating the data on a division/ward/specialty level.
3. Exploring requirements for achieving different levels of target occupancy.
4. 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.

Key insights

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: