Because acute care is generally delivered over a short time, when we think about it we tend to focus on what is happening at a particular moment. Mental Health, on the other hand, deals with treatments that last a long time and which need to be seen in a different way.
Even a clear example of short-stay care, say an operation performed as a day case, may require an attendance beforehand for tests and perhaps a follow-up outpatient appointment afterwards. The care is provided by a pathway embracing all three.
And then there are those conditions that have to extend over longer periods. Cancer treatment may involve courses of chemotherapy and radiotherapy, with perhaps surgery as well. There are many other conditions for which this is true: diabetes, asthma, obesity, coronary heart disease, and the list keeps growing. The complication for many of these is that the pathway isn’t even limited to hospital setting alone: much of the care may be provided by GPs or by community hospitals.
This leads to many challenges for information services.
Even within a single hospital, we need to find ways of linking data about emergency attendances, outpatient appointments and inpatient stays. Having made the links, we need to apply logical rules to break some of them again: the patient who had a coronary in June may be the same as the one who was treated for cholecystitis in September, but there are two pathways here that need to be distinguished.
It’s also only a first step to link data about attendances and admissions. We also need to pull in departmental data: records about medication, diagnostic tests, therapy services, and so on, all need to be associated with the corresponding events.
And not just with the events – they also need to be associated with the whole pathway. From one point of view, it may well be interesting to know that the Full Blood Count was carried out following a particular outpatient attendance, especially if the protocol requires that it be carried out then. On other pathways, however, we just need to know that the test was done, without specifying when on the pathway it happened. So we need links to events and to pathways.
All this requires relatively complex processing. It’s made far worse if the data is poor or incomplete – say the patient identification data is only partial on some of these records. That can be a major challenge. It seems to me, though, that the only way to solve the problem is to start working with the data: when staff see that the analysis is happening, they’ll have a massive incentive to get the data right.
The rewards are extraordinary. This kind of analysis allows hospitals to start applying protocols of care, because they will have the means to check whether they’re being respected or not. My guess is that they’ll be astonished by the results. So far, I’ve only worked with some limited sample data, but I’ve been amazed by the variation in care pathways it reveals – for example, even simple conditions requiring day surgery may involve one, two or even three inpatient stays.
One particular case springs to mind, of a patient who had a Caesarean preceded by no less than six outpatient attendances. The data quality for her was however good: difficulties with labour had been recorded as a diagnosis. Suddenly the data came to life. We weren’t just looking at a bunch of entries from a PAS, but at a real live case of a woman with a real problem, and a hospital that was working to help her deal with it.
It was the pathway view that revealed the real nature of that story.
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