One of the key functions we are aiming to provide is the ability to visualise what the future would look like based on certain assumptions and then be able to plan for it. This may be part of regular, ongoing planning (ie, the next few weeks or the upcoming budget year), but also considering the ‘what-if’ scenarios, in terms of what might be possible if a hospital changes the way it manages patient flow and/or available resourcing.
In terms of the regular planning for inpatient areas, we are currently working on streamlining the way hospitals do their forecasting so that users can more confidently adjust their resourcing to meet predicted patient demand. The aim of this is to make it easier for hospital planners and managers to enter their assumptions around how many patients there are and how long they are going to stay, and then understanding how these will impact resourcing, such as beds and nursing.
In terms of theatre/OR planning, we’ve introduced our theatre flow/OR functionality, which includes optimisation and simulation capabilities. This provides the ability to do both the regular planning as well as consider the ‘what-if’s. This enables planners and managers to determine theatre/OR throughput and assess the resource requirements in both theatre/OR and inpatient.
As an example of ‘what-if’ planning, in the UK the National Health Service has identified a number of resource management issues that hospitals can improve upon. One recommendation is to increase day case rates where patients enter hospitals for a minor elective operation and leave the same day. Clinically there is little reason why some elective patients need to take up an inpatient bed at all, yet often they are admitted to hospital and end up taking up a bed for a few days. The NHS is suggesting that more elective patients could be reclassified as day cases.
Hospitals can create ‘what if’ scenarios to see what the occupancy of the hospital would look like if this were to happen. They can do this by actually simulating patient flow based on assumed care paths. Optimisation can then also be employed to automatically determine the best allocation of theatre/OR activity to meet targets within assumed resourcing. This will also show any resourcing and financial impacts this might have, including bed allocation, the amount of theatre/OR time required, and any bed days exceeding capacity that may result.
Armed with these predictions, managers can then determine what adjustments they can make to administration and resourcing to improve patient flow. Thus, if more beds could be made available, hospitals can consider whether they can process more patients through theatre/OR and achieve higher rates of surgery.
It’s about creating a best fit solution that enables managers to quickly weigh-up the assumptions with the predicted impacts, determine what is achievable, and then adjust hospital procedures accordingly to achieve optimal operations.
Andrae Gaeth Product Specialist, Emendo