Healthcare needs data warehouses. But what for?

The word warehouse conjures up an image of racks of shelving reaching high up towards a roof. Piled high across them are packages, boxes and crates of different sizes and types, reaching into the dim distance in every direction.

As it happens, a data warehouse isn’t that different. Ultimately, it’s a convenient way of storing large quantities of data. The key term here is ‘convenient’.

In one type of data warehouse, convenience is maximised for storage. It’s made as easy as possible to load data and hold it securely. This is the approach taken, in a different field, by major books repositories such as the British Library: as books arrive, they’re simply stored on the next available shelf space with no attempt to try to put them into any kind of order, whether of author or of subject matter. The label that goes on the back of the book simply indicates where in the shelving it’s stored and tells you absolutely nothing about the nature of the book or what’s in it.

Trinity College Dublin

The problem, of course, arises when you want to retrieve the book. It’s fine if it’s exactly where the label suggests it should be. However, if it has been taken out and then incorrectly returned, it may be quite simply impossible to find. A librarian at the British Library told me of a book which had been lost for many years, until someone found it just two shelves away.

This approach is ideal for storage, hopeless for retrieval.

A great many data warehouses, and in particular most of the older ones, are of this type.

The data is securely stored and, as long as you can go straight to it and find exactly the information you want, then it’s fine to hold it that way. However, if you want to do something a little more sophisticated, say you want to start collecting related groups of information, this method is no good at all.

What you need in these circumstances is something less like the British Library and more like a bookshop. There the books are collected first by subject matter, then by author or title. The beauty of this is that as long as you know the structure, you can find not just the particular book you want but also get quickly to other, related books. You wanted a book about travel in Spain – you may well find a whole shelf of them including not just the one you were looking for but perhaps another which is even better.

Of course, when it comes to data you can do far, far more than a bookshop. Because pulling the data together into various collections can be done simultaneously in many different ways. I’m sold on the approach known as dimensional modelling. What this means, from a user point of view, is that a healthcare data warehouse would contain lists of patients, dates, specialties, consultants, diagnoses, in short of anything that can be regarded as a ‘dimension’ or classification of your’. Each of these lists is linked to a set of facts about what was done for any patient at any time.

A fact table at the centre, dimensions linked to it

What this means is that you can quickly ask for all information about care activity carried out in a particular specialty in a particular month, or by a specific consultant for a particular primary diagnosis. And when I say ‘all the activity’ I mean all of it: you don’t have to get hold of inpatient data first and then go back for the outpatients, you’d see the lot from the outset.

That’s a bit like knowing that John Le Carré’s Tinker, Tailor, Soldier, Spy is simultaneously stored under spy novels, under fiction about the cold war, under Le Carré but also under his real name of David Cornwell, under books published in 1974, and under any other category that some user might find interesting. And, because we’re talking about computer technology, it’s under all those categories although there’s actually only one copy of the book in the bookshop.

Now that’s a warehouse structure designed to optimise retrieval rather than storage, and therefore to make reporting particularly easy. That’s why this second more modern approach to structure is so much more to be preferred than the older one.

But then there’s one other aspect of data warehouses which makes them particularly powerful, whether they’re of the older or the newer type.

They can include rules engines which manipulate the data.

If the incoming data is of poor quality, rules can tell you so: in the bookshop example, you’d get an alert saying ‘the author’s name is illegible’, ‘the date of publication isn’t given’ so that you can get the classification information improved.

If you need to add new information derived from the incoming data, rules can do that too: if you know that data from one department in the hospital shows the consultant identifier as a code, say ‘MKRS’ and you want it to be stored as ‘Mr Mark Smith’, you can define a rule that adds the form you want. In the bookshop example, it could add ‘David Cornwell’ to John le Carré’s name.

Taken together, these aspects of data warehouses – structures optimised for reporting and the application of well-defined rules – make them absolutely essential tools for understanding healthcare activity. They can take raw data and turn them into management information. With the difficult management decisions that lie ahead, that’s more crucial than ever before.

Finding the right pathway to understand healthcare

One of the most important ways in which Mental Health can become a model for healthcare generally is in promoting the pathway approach to care delivery.

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.

Patient Level Costing - not just for geeks

When you work in health information, there is a terrible tendency to get into some bad habits. It’s a sector which is much too easily satisfied. We get data that’s 95% complete and we say ‘hey, that’s not bad.’ At 99% we’re ecstatic.

That’s why it’s been such an eye-opener to work on Patient Level Costing. This is because when it comes to completeness, finance staff only know one acceptable figure – 100%. If there's a discrepancy, then it needs to be small and we have to be able to account for it, to explain it in its entirety.

There’s something refreshing about this uncompromising demand for the highest standards of rigour. It’s made it a lot of fun to spend a lot of time over the last three years in this field.

As it happens, the fundamental principles of Patient Level Costing are an intriguing challenge in themselves. The problem is that you’re trying to reconcile the irreconcilable.

The clinicians who are involved with a particular case take a patient-centric view of what they do. They see that the patient had an X-ray of a leg and then an operation to pin a badly broken bone. He had an anaesthetic during the operation, an antibiotic to combat possible infections and an analgesic to combat the pain. He received nursing care, medical care and an intervention by a surgical team. Consumables were consumed in the operation, a bed was provided, the patient was served food (which may even have been passable).

Unfortunately, the hospital’s General Ledger simply doesn’t recognise any of these categories. There will be entries for drug costs and anaesthetics, there will be entries for staff pay, there will be entries for food and consumables and laundry and cleaning and maintenance. None of these will give anything like a coherent account of what happened to our patient. It’s rather like the first diagram below: two cogs that don’t mesh and turn in opposite directions.

Patient Level Costing therefore has to bring in a third cog, a Costing Engine, to mesh with the other two and make them work together. Such a costing engine has to include complex logical processes to convert the Ledger view of the hospital world into the patient-centric, clinician view. In other words, it takes the values in the ledger and finds a way to translate them into costs and income values that can be assigned to individual patient records.

Now that sounds like an exciting thing for geeks and no-one else. In reality, though, it’s a lot more significant than it sounds. Because carry it off and what you’ve done is to provide a common vocabulary for communication between Management and Clinicians. Currently Management sees that Trauma and Orthopaedics is overspent (that’s just an example, but isn’t it sad that it tends so often to be Trauma and Orthopaedics?). With Patient Level Costing, suddenly the hospital can identify the specific patients where the overspend occurred.

Suddenly the Clinicians can investigate the source of the problem. Is it a mistake not to give an antibiotic as a prophylactic before certain operations – does it lead to significantly higher costs, on average, later? Is it a mistake to use a particular medication to treat a condition which might be dealt with more quickly and cheaply using another, even though it is itself more expensive? Once the costs have been associated with individual patients, it becomes possible to answer those questions.

Which means that the problems can be addressed by the only people who can actually make a difference – clinicians.

So Patient Level Costing isn’t just for geeks. It’s for all of us who’d like to see care made more efficient – and more effective. And that’s basically all of us.

Mental Health may show the way to Healthcare sanity

Although I’ve been active in healthcare information, mostly in Britain, for a quarter of a century, it’s only in the last couple of years that I’ve had much to do with Mental Health.

To my shame, I have to admit that I was surprised by what a pleasure it’s been. I was expecting something far less enjoyable. As in most countries, Mental Health has tended to be the poor cousin when it comes to healthcare information systems, if not the poor cousin of healthcare generally. In recent times, however, that has been changing rapidly.

Healthcare in Britain has been the subject of an apparently unending succession of organisational reforms, by governments of all hues. The latest wave is under way right now and promises to be particularly painful. In passing, let me say that it’s incomprehensible to me why governments think that by constantly reorganising the way healthcare’s managed, they are helping it be more efficient, more effective or less expensive.

One initiative a few years ago was the introduction of Foundation Trust status for hospitals. This gives them far greater autonomy, in the way they manage not just their work but also their finances. A large number of Mental Health hospitals applied for and were granted that status. One of the results was that they suddenly needed to become far better equipped in information systems to support decisions by their managers, including clinical managers.

This came on top of a brave and highly effective reform that they had themselves driven through over 25 years, as they moved away from being a strongly hospital-based service to delivering far more care in the community. This was particularly difficult to achieve as Mrs Thatcher’s government in the early eighties, at the start of the process, only saw care in the community as a way of saving money. At the time I lived in Hastings where a local Mental Health hospital had recently thrown out a lot of its former inmates. I remember groups of sad individuals moping around as they experienced the joys of being cared for in the community by being left on street corners.

Since then, however, there has been serious investment in Mental Health. Today, therefore, there is real care in the community, allowing people to live at home, with their families and friends and even jobs, rather than being shut up in hospitals out of sight. The possibility of inpatient care is available to those who really need it, either for extended periods or for a briefer time until they are well enough to return to the community. All this has added up to a dramatic improvement in the quality of Mental Healthcare over the time that I have been working with the NHS.

But the final aspect that completes this picture is the way that Mental Healthcare, instead of being little more than an also-ran in healthcare generally, is beginning to emerge as a model. This is because a lot of healthcare, of the kind that used to be provided by acute (short-stay) hospitals is becoming long-term chronic care. Diabetes, cancer, certain types of heart disease, obesity, infections like HIV among many other conditions, are not treated by spectacular actions at a specific point in time – say a massive and complex operation – but by careful management over long periods, with regular interventions by many different types of staff (doctors, nurses, therapists, counsellors) who have to work together as a team.

That is precisely the way that Mental Health functions. Treatments can take months, years or even an entire lifetime. They involve many different types of professionals working in different contexts – in a hospital, in an outpatient clinic, in a peripheral clinic or health centre, in the patient’s home – and having to coordinate their activity. Why, the concept of the multi-disciplinary team meeting, now increasingly widespread across different types of hospitals, is central to the way Mental Healthcare is delivered.

So suddenly it may be Mental Health that can teach the rest of Healthcare a thing or two.

All these things make the Mental Health sector vibrant and exciting. Long may it remain so – and survive the ravages of next wave of cuts.