This week we will continue to explore the Case of Chronic Pain in the A&E Department of St.Elsewhere’s Hospital.
Last week we started by ‘taking a history’. We asked about symptoms and we asked about the time patterns and associations of those symptoms. The subjective stuff.
And as we studied the pattern of symptoms a list of plausible diagnoses started to form … with chronic carveoutosis as a hot contender.
Carveoutosis is a group of related system diseases that have a common theme. So if we find objective evidence of carveoutosis then we will talk about it … but for now we need to keep an open mind.
The next step is to ‘examine the patient’ – which means that we use the pattern of symptoms to focus our attention on seeking objective signs that will help us to prune our differential diagnosis.
But first we need to be clear what the pain actually is. We need a more detailed description.
<Dr Bob> Can you explain to me what the ‘4-hour target’ is?
<StE> Of course. When a new patient arrives at our A&E Department we start a clock for that patient, and when the patient leaves we stop their clock. Then we work out how long they were in the A&E Department and we count the number that were longer than 4-hours for each day. Then we divide this number by the number of patients who arrived that day to give us a percentage: a 4-hour target failure rate. Then we average those daily rates over three months to give us our Quarterly 4-hour A&E Target Performance; one of the Key Performance Indicators (KPIs) that are written into our contract and which we are required to send to our Paymasters and Inspectors. If that is more than 5% we are in breach of our contract and we get into big trouble, if it is less than 5% we get left alone. Or to be more precise the Board get into big trouble and they share the pain with us.
<Dr Bob> That is much clearer now. Do you know how many new patients arrive in A&E each day, on average.
<StE> About two hundred, but it varies quite a lot from day-to-day.
Dr Bob does a quick calculation … about 200 patients for 3 months is about 18,000 pieces of data on how long the patients were in the A&E Department … a treasure trove of information that could help to diagnose the root cause of the chronic 4-hour target pain. And all this data is boiled down into a binary answer to the one question in their quarterly KPI report:
Q: Did you fail the 4-hour A&E target this quarter? [Yes] [No]
That implies that more than 99.99% of the available information is not used.
Which is like driving on a mountain road at night with your lights on but your eyes closed! Dangerous and scary!
Dr Bob now has a further addition to his list of diagnoses: amaurosis agnosias which roughly translated means ‘turning a blind eye’.
<Dr Bob> Can I ask how you use this clock information in your minute-to-minute management of patients?
<StE> Well for the first three hours we do not use it … we just get on with managing the patients. Some are higher priority and more complicated than others, we call them Majors and we put them in the Majors Area. Some are lower priority and easier so we call them Minors and we put them in the Minors Area. Our doctors and nurses then run around looking after the highest clinical priority patients first … for obvious reasons. However, as a patient’s clock starts to get closer to 4-hours then that takes priority and those patients start to leapfrog up the queue of who to see next. We have found that this is an easy and effective way to improve our 4-hour performance. It can make the difference between passing or failing a quarter and reducing our referred pain! To assist us implement the Leapfrog Policy our Board have invested in some impressive digital technology … a huge computer monitor on the wall that shows exactly who is closest to the 4-hour target. This makes it much easier for us to see which patients needs to be leapfrogged for decision and action.
<Dr Bob> Do you, by any chance, keep any of the individual patient clock data?
<StE> Yes, we have to do that because we are required to complete a report each week for the causes of 4-hour failures and we also have to submit an Action Plan for how we will eliminate them. So we keep the data and then spend hours going back through the thousands of A&E cards to identify what we think are the causes of the delays. There are lots of causes and many patients are affected by more than one; and there does not appear to be any clear pattern … other than ‘too busy’. So our action plan is the same each week … write yet another business case asking for more staff and for more space.
<Dr Bob> Could you send me some of that raw clock data? Anonymous of course. I just need the arrival date and time and the departure date and time for an average week.
<StE> Yes of course – we will send the data from last week – there were about 1500 patients.
Dr Bob now has all the information needed to explore the hunch that the A&E Department is being regularly mauled by a data mower … one that makes the A&E performance look better … on paper … and that obscures the actual problem.
Just like treating a patient’s symptoms and making their underlying disease harder to diagnose and therefore harder to cure.
To be continued … here