Small steps: why patient flow could help to reduce bed-blocking


During this winter period, it has become clear that the National Health Service (NHS) in the UK is under even more than the usual additional strain. With routine operations already being cancelled to manage emergency treatment, hospitals cannot afford any delayed discharge of patients because of the knock-on impact on available beds. However, evidence suggests that delayed discharge is once again on the rise.

The rise of delayed discharge

The media is already making headlines from numerous figures, including:

Delayed discharge, also known as “bed-blocking”, occurs when patients are well enough to be discharged from hospital, but remain there because they do not have the correct care, support or equipment at home or in the community to continue their recovery. These patients can often spend weeks in hospital when they could be cared for at home or in the community, where their recovery might well be quicker. This practice is putting unnecessary pressure on A&E departments and wards, increasing waiting times and staffing costs, and often leading to cancelled operations.


Patient management can be challenging and time consuming.

This is not a simple problem. It occurs at the boundary between health and social care (and perhaps more importantly, their budgets), and involves issues relating to family responsibilities. Various solutions have been trialled to address the issue, with mixed results but often increasing costs. These have included increasing the supply of nursing staff, building more care homes, keeping a ready supply of equipment in hospitals and changing the system of managing people coming to A&E, as well as merging health and social care organisations and budgets.

Developing patient flow modelling

No single organisation will ever hold all the answers to delayed discharge or bed-blocking. Cooperation is always going to be the best way to attempt to manage the problem, and, indeed, to improve patient outcomes across the system.

However, individual organisations can improve matters, for example, by use of patient flow modelling. This is a discrete simulation model which will allow hospitals to improve patient management, bed control, the logistics supporting the movement of patients and overall bed use. The model includes:

  • Patient points of entry;
  • Recovery units;
  • Hold time thresholds;
  • Routing process; and
  • Staffing levels/beds.

It can be used to model complex interactions between patients and units, key decision points, and ‘what if’ scenarios. It also provides comprehensive KPIs that can help managers in hospitals and social care understand the causes and effects of delayed discharge. This is important because these vary considerably around the country, and the solutions are therefore different. Understanding the ‘pinch points’ and problem areas means that tailored solutions can be put in place to manage delayed discharge at particular hospitals, or in specific areas or regions, and help improve patient outcomes as well as reduce cost.

Developing a data-informed NHS

Hospitals have not traditionally made decisions based on extensive data analysis. However, this type of modelling offers them a chance to increase efficiency and address their problem areas.

Understanding the problem is still only the first step towards addressing it, but it is an important one. Solving issues of delayed discharge will require hospitals to work closely with social care and community providers, to develop a fully integrated care model. Nobody is suggesting that this will be easy, but ensuring that the model is based on evidence - and not just ‘gut feeling’ - will make it more likely to succeed. This, in turn, will result in better patient outcomes, increased efficiencies and cost savings for the NHS and its partners. That’s something we all want to see!

To find out more about how analytics can help in healthcare.


About Author

Mark Frankish

SAS Data Scientist, SAS UK

Mark Frankish has over 15 years’ Analytical experience, with a breadth of industry domain knowledge and the SAS portfolio. He is a specialist in the Public Sector and the challenges and solutions in Welfare, Health and Fraud.

1 Comment

  1. Mark; I suspect there are many analogous aspects of clinical care pathways to proven numerical techniques from other industries. I recall Financial Services adopting some in the late 90's from manufacturing and the modern day use of IoT will surely only improve what previously was achieved with bar codes and RFID tags. I know there is work in the SW being done to move away from RAG based queuing to a more process oriented control paradigm in certain NHS Trusts. How do these techniques cater for the variable nature of the raw ingredients i.e. us the patients ? On a broader note I fully support your premises that DATA are the jewels in the NHS that offer more TRANSFORMATIONAL POTENTIAL DIFFERENCE than is currently realised.

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