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DTOCs - A growing piece of a bigger problem?

Blog 2 of 2. DTOC statistics don't always show the full picture when it comes to factors affecting the safe and timely discharge of patients.  Our expert practitioner discusses the bigger picture of delayed discharges, along with some simple changes that may help deliver the breathing space required for the NHS to focus on solving the wider problem.

Read the first of this two part journal entry: 'DTOCs - Exploring the issue'

Improved patient flow is critical

In a recent blog, I explored the statistics behind the rising trend of Delayed Transfers of Care (DTOCs) and the impact this is having on the NHS. We saw that, in the past 3 years, the total number of delayed days has risen by almost 60%, with DTOCs in an acute setting rising a staggering 70%. What makes this worse is that the current measures for DTOC patients are, in some cases, significantly underestimating the number of delayed discharges. To understand how, it is worth considering the official definition for a DTOC patient as set out by NHS England:

NHS England defines a patient as being ready for transfer when:

  • a clinical decision has been made that the patient is ready for transfer, or “medically fit”, and
  • a multidisciplinary team has decided that the patient is ready for transfer, or “functionally fit”, and
  • the patient is safe to discharge/transfer.

To be recorded as a delayed transfer in the official statistics, an adult patient must meet all three of the above conditions and remain in hospital.

What the DTOC statistics do not record are the patients who have been declared ready for transfer by a clinician, but not declared ready for transfer by the Multi-Disciplinary Team (MDT). The term for a patient who is medically fit for discharge is ‘Medically Optimised’ and is defined as ‘the point at which care and assessment can safely be continued in a non-acute setting’.

Unfortunately, only some NHS organisation collect data for medically optimised patients, with the majority choosing to focus on those who are both medically and functionally optimised. Given that these are the statistics they are targeted to minimise i.e. DTOCs, it is no wonder that this is the case.

However, this reveals, or rather hides, two potential problems:

  1. Delays in the MDT team declaring the patient functionally fit are not observed and therefore identified.
  2. Patients who have been declared medically fit, had a delay in being declared functionally fit, and as a result have now become medically unfit, are not identified either.

Why this is a problem

In addition to the obvious implications this has for quality of patient care, there are worrying implications for the way in which hospitals prioritise improvement initiatives to overcome challenges with delayed discharges. Working for an organisation whose foundations stem from the Japanese Lean methodology and the principles of problem solving and continuous improvement, a common quote we often use is “to solve a problem, you must first understand it”. By only measuring the delays to patients according to the NHS England definition, you are only capturing part of the problem. This potentially masks both the root cause and true impact of the problem, inhibiting your ability to design and implement an effective solution to combat it.

You may at this stage be thinking that the problem can’t be that significant given that a delay to the discharge of a medically optimised patient is only likely to be at most a few days, whereas there are stories of DTOC patients waiting months or even years to be discharged. An important consideration is that, whereas delayed transfers due to social care challenges (the majority of DTOC cases) only tend to affect the elderly or those with complex support needs, these delays can occur with every patient admitted to hospital - including surgical patients. It's well accepted that the welfare impact of extending the stay of a healthy patient can be significant. A report published by the National Audit Office in May 2016 on the subject of discharging older people from hospital found that 10 days of bed rest for a healthy older patient can lead to 10 years of muscle aging and associated loss of function.

The extent of the problem

Unfortunately, there is no regularly released data to easily quantify this problem at a national level as, as previously mentioned, there is no obligation for a Trust to report this information.

However, the same report by the National Audit Office found that in 2015 there were 1.75 million hospital bed days lost due to delayed transfers of care, but an estimated 4.2 million bed days occupied by people no longer in need of acute hospital care. Albeit not a direct reflection of the medically optimised patients I have been referring to, it demonstrates the extent to which national DTOC statistics are underestimating the challenge.

More specific analysis has been undertaken by a number of organisations, conducting audits on hospital wards to compare the medical and discharge status of patients. The results consistently showed  a significant number of medically fit patients, who did not fall within the current definition of DTOCs, awaiting functional interventions by the MDT before they could be discharged.   

This is obviously an expensive and labour intensive way of quantifying the issue, which would not be practical for the majority of NHS Trusts. Whilst not a direct link, a simpler way of identifying the problem is to understand the effective use of a patient’s Planned Discharge Date (PDD), or Estimated Discharge Date (EDD), and comparing it with their actual discharge date. 

A patient’s EDD is the estimated date that they will be discharged based on their initial diagnosis. Obviously, there are a multitude of reasons why in reality the patient would not be able to be discharged on this date, such as secondary conditions or complications arising during their stay. However our health team have regularly observed cases where a patient has been declared medically fit by a clinician on (or prior to) their EDD, but there has then been a subsequent delay whilst MDT interventions, required for the patient to be ready for discharge, were completed.

NHS Improvement identified the need to use a patient’s EDD when they released their SAFER Patient Flow Bundle, stating that “all patients will have an Expected Discharge Date (EDD) and Clinical Criteria for Discharge (CCD), set by assuming ideal recovery and assuming no unnecessary waiting”. However, despite being set, many organisations are not using the EDD for its intended purpose and as a result it serves little value in improving discharge processes.

A potential solution

NHS England acknowledge within their DTOC guidance document that some Trusts collect information on medically optimised patients in order to improve patient flow. In this context, patient flow is the process of moving patients through the hospital as seamlessly and quickly as possible i.e. from the emergency department, through an acute assessment unit, into a bed and discharged home or elsewhere. Anything that inhibits this flow; for example a patient’s discharge being delayed, not only impacts that particular patient but has a knock on impact on capacity and flow back through the hospital.

If we accept that undischarged, medically-optimised patients are negatively impacting flow through the hospital then it begs the question: "why aren’t all Trusts collecting this data for the same purpose?".

The first step to take in solving any problem is to collect data in order to measure the issue. Subsequent analysis can be used to quantify the scale and identify the root-cause of the problem, enabling improved decision making and, crucially, the design and implementation of an effective solution. The good news… in many cases, the solution to this problem is faster and less complex than solving the problem of DTOCs.

By proactively using a patient’s EDD to schedule and prioritise multidisciplinary interventions, based on a pre-existing understanding of how long those MDT steps and assessments take, you can reduce the delay between clinical and multidisciplinary “ready to transfer” status; reducing the patient’s length of stay.

I mentioned in my last blog that certain Trusts are recognising the importance of the collaboration between the different MDT functions. In an effort to improve the flow of patients these Trusts have started to house social care teams on site and integrate them into the MDT. The enhanced visibility and accuracy provided to the social care teams, of the patients likely discharge date, allows for much greater planning and control of social care handovers.

The worrying trends discussed in the previous blog still remain; resolving the challenge of rising DTOCs will still require the successful delivery of Accountable Care Systems (ACS), and the realisation of Sustainability and Transformation Plans. However, making these simple operational changes could provide the capacity or, at the very least, ease the burden on acute facilities to focus on the larger challenges that lie ahead.

The Unipart Way: performance improvement that sustains

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