Plan future bed capacity requirements under a range of scenarios (different levels of demand, or different ward configurations)

BedPlanner uses historic patient-level data to predict future bed occupancy based on expected admission rates. These prediction scenarios can be altered to reflect expected or known changes in demand, such as post-Covid-19, to simulate different demand scenarios. Or patient flow rules can be changed to simulate the effect of changing clinical processes or ward configurations (e.g. maximum time in Assessment Unit capped at 36 hours). This approach, which uses granular data means the model is calibrated with a rich understanding of local demand and usage patterns.

Example problems solved:
• How to reconfigure hospital wards to better match demand
• How to identify the requirement for additional beds

• Secure and easy to access on-line platform
• Metrics on bed demand, capacity, and utilisation
• Multiple pre-coded demand, capacity and flow scenarios included.
• Machine learning
• Clustering
• Statistical analysis
• Downloadable reports summarising metrics

• Bed demand and capacity with insights and analysis on usage patterns
• Ward and specialty view provide an in-depth understanding of Trust specific pressure points
• Easy to access information for different users
• No user limits

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