User interface for A&E - bed denied (mock-up)
User interface for A&E - bed accepted (mock-up)
User interface for wards (mock-up)
A&E interface - add new patient (demo)
A&E interface - patient info (demo)
A&E interface - bed denied (demo)
Ward interface (demo)
Data supporting a deterioration in meeting A&E targets in England (1)
Data supporting a decreasing availability of beds within hospitals (2)
One of the biggest challenges facing the NHS today is a failure to meet defined A&E targets outlined within the NHS Plan, which states that patients attending A&E must either be discharged from or admitted into the hospital within 4 hours (1). The most recent time 95% of patients met this target in England was in Summer 2015. Performance has since been deteriorating (1).
A significant contributor to this deterioration is an inability to accommodate patient admissions from A&E due to a shortage of available beds within hospitals (2) and highly inefficient bed management systems that rely on roaming hospital wards and seeking telephone updates multiple times a day to update bed states/ locate vacated beds (3).
- Over the past 30 years, the number of available hospital beds in England has decreased by more than 50% (2).
- Occupancy rates for overnight acute beds have also increased: from 87.1% in 2010/11 to 90.4% in 2016/17 (2).
We set out to create a platform with a bed-matching algorithm and user-friendly interface for A&E staff and ward managers to maximize resource utilization for hospital beds.
What it does
Alpha Beds is a platform that optimizes bed management within hospitals via a user-friendly interface for hospital staff. The Alpha Beds algorithm matches demand for hospital beds from A&E to supply within hospital wards to enable meeting 4-hour A&E targets.
Challenges we ran into
- Identifying a problem to solve
- Maintaining motivation within later hours of the night
- Amount of work required to build the interface
- Different levels of coding experience within the team --> difficulties allocating responsibilities
Accomplishments that we're proud of
- Building the application in under 24 hours
- Good time management to balance hacking and team-bonding
What we learned
- Learning Python / Machine Learning
- How to create mock-up applications
- Inner workings and terminology within the NHS
What's next for Alpha Beds
- Building a more user-friendly interface
- Focus groups with healthcare staff to identify areas for improvement
- 2nd attempts at requesting beds
- Following NHS encryption guidelines and integrating with existing NHS systems
- Beta testing within select hospitals