Simulating Acute Bed Capacity 7 days a week
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Simulating Acute Bed Capacity 7 days a week

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Simulating Acute Bed Capacity – 7 days a week ...

Simulating Acute Bed Capacity – 7 days a week
NHS IMAS
Poster from the 'Delivering NHS services, seven days a week' event held in Birmingham on 16 November 2013
More information about this event can be found at
http://www.nhsiq.nhs.uk/news-events/events/nhs-services-seven-days-a-week.aspx

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    Simulating Acute Bed Capacity 7 days a week Simulating Acute Bed Capacity 7 days a week Document Transcript

    • Simulating Acute Bed Capacity - 7 days a week Introduction Improving emergency care is complex and depends on a range of factors including: • Daily and hourly variations in patient demand • Varying lengths of hospital stay • Discharge practices • Availability of health and social care services pre and post-discharge Project Aim The aim of our project was to bring together the available data and improvement evidence into a simulation model which could be used to demonstrate best practice and to allow hospitals to test their own solutions and enter their own data to understand which improvement might be most effective for them. Understanding the impact of changing to 7 day working on the system is challenging, and stakeholders want to understand the resource implications for acute beds. Partnership Russell Emeny NHS IMAS Fiona Lindsay SIMUL8 Corporation Claire Cordeaux SIMUL8 Corporation The project has been a partnership between the NHS IMAS Emergency Care team (ECIST) and the Cumberland Initiative (an academic, industry, NHS partnership) with specific input from Professor Sally Brailsford at Southampton University and Professor Terry Young at Brunel. It has been informed by an in depth study of the evidence and based on the field work of the NHS IMAS team. SIMUL8 Corporation has provided the modelling expertise and software to develop the simulation. Simulation Simulation is an accurate computer model that looks and acts just like a real life process, allowing experimentation with changes to a system, without taking the risk of making the changes in real life. Because it can manage the complexity of a system like health and social care, including variation in arrivals, patient types, lengths of stay, staff and bed capacities and costs, simulation can provide the evidence needed for decisions about which intervention is the most cost effective and can improve the flow and decrease bottlenecks in the system. The Acute Bed Model The simulation model represents patients arriving at hospital through an emergency care route and needing to be admitted. Patients are admitted to a bed for a length of stay and are then discharged. Admissions are sent directly to a bed and length of stay is simulated using a distribution based on midnight stays depending on the hour of the day and the day of the week that the patient was admitted. As with the arrival data the simulation has been populated with default LOS data and this can also be adjusted to reflect local data. Results show: • Bed occupancy as a percentage and numbers of beds in use • Time spent waiting for a bed Improvement Scenarios: • GP referrals arriving earlier in the day • Effective ambulatory care • Increasing proportion of patients who only stay 2 nights • Shifting the hours of discharge earlier in the day • Reducing the length of stay for patients over 75 who stay 14 nights 7 Day Working All scenarios function 7 days a week in this simulation model. We also simulated the impact of having a Monday profile of length of stay every day of the week. We assumed that Monday’s profile, being the furthest from the weekend might give the best representation of this “what if?” scenario. What we found was the bed utilization actually increased and there were longer waits for a bed. Why? Our explanation is that simply extending current practices from five to seven days may paradoxically increase length of stay. This is because Friday creates a ‘breakpoint’ that clinical teams work to and without such a psychological deadline, pressure to discharge may be reduced. Two Conclusions 1. 7 day working defines all our emergency care data and simply using historic data to model impacts may not provide us with the evidence we need to drive forward change. We need to carefully consider what is likely to happen when access to care and clinical judgement, rather than the weekend, drive emergency arrivals and lengths of stay. 2. 7 day working in itself will not derive the expected benefits if other improvements are not implemented