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Nosokinetics

Looking in from the outside

time to get through the door

Mark Mackay, Principal Project Officer, Department of Health, South Australia

Staking our place

Previously I have suggested that it is time to stake a place in the “health care problem” ground by health care modellers, particularly in relation to those modellers involved in patient flow modelling activities (see Mackay, 2006). In this NK article I outlined that the health care sector is perhaps different to other industries - there are many players involved in decision-making and no-one group is likely to be able to solve the current problems being experienced across health systems without involvement of members from some of the other players.

Tribes and sub-tribes

The players include doctors (and don’t ignore their sub-tribes - the specialties and sub-specialties), nurses, administrators, bureaucrats, politicians, academics, consultants, and somewhere among these tribes is the small group (or individual) of modellers. Having worked in the health sector for some time it is interesting to observe how the tribes, and even more so the sub-tribes, can come together on some matters and yet be at war on other matters. Thus, working the system can be complex.

Cottage industry

Furthermore, while “hospitals” are often viewed akin to the large factory, in reality it is a large building occupied by various cottage industries that co-exist and share facilities and services as required. A large bit of the glue binding the services is the hospitality services required by patients. Clinical and diagnostic services are also part of the glue (e.g., theatres and imaging services). Furthermore, the variation in practice and problem is far greater than any widget producing factory that I’ve seen - and I’ve seen a few as a consequence of employment in other sectors other than health.

Complexity

So it’s a complex environment, what’s the big deal I hear you ask? Modelling has the potential to help improve decision-making in the health care sector, particular in relation to patient flow issues. Yet modelling doesn’t appear to have “cracked” the potential that exists in the health sector. Just as the sector itself is complex, the reason for not cracking the market is undoubtedly also complex.

Getting heard

Currently I think that health care modellers often sit on the outside and are yet to get heard at the main table. Reasons for not getting heard include the variety of modelling tools that exist and aren’t well understood by the non-modelling tribes (language and tool barriers); the results are sometimes at best variable (see Fone, Hollinghurst et al. 2003); sometimes there’s not enough resources to enable inclusion of the modellers; the solutions provided by modellers are not sufficiently timely (i.e., can’t meet delivery deadline of answering the problem yesterday in a political and reactive environment); and (or) don’t solve the problem (either in a desired way or identify things that people really don’t want to hear).

So what do I do? I could go on. Or I could give up.

Right time

Given the pressures beginning to occur on hospitals as the volume of baby boomers with health problems increases and the forecast consequences of chronic diseases (not affecting just the older members of the community, but increasingly younger members as well), the time is probably most conducive for getting through the door and being heard at the table.

It’s time to tip the balance!

But how can the “tipping point” (Gladwell, 2000) be reached? While I suggested some mechanisms in the NK article last year, many of these are things that will have an impact over time, such as education. However, we need to be going through the door now or at least sometime very soon.

Plain language

The book adaptive business technology (Michalewicz et al., 2006) is perhaps a good starting point. It’s in plain language. While the concepts it deals with are undoubtedly complex, it provides a great example of how to communicate the gains decision-makers can make from the application of data-mining and modelling. Plain English (or other language if not in an English speaking country) is a key - it provides a means of reaching across the divide so that others can understand what is being offered.

Answering the questions people are grappling with.

This provides a real tension for academics - the priority is often to publish and the application may or may not be a priority. It may also have to be at a level that is probably less complex than some academics might like. But without opening the door, there is no entrée to showing those already at the table the vast arrange of value that can be added by “the modeller”.

Leave them with something - some basic tool that is based in software that they probably are comfortable in using (even if only at a basic level) and don’t charge them for it. They may never use it, but they didn’t pay for it (unless of course specified as part of the work). It provides the opportunity to exchange and build up trust.

This will give us “the champion” and “the champion” will help us to reach the tipping point.

“Some business model?” you say. Well, if it’s good, they’ll come back and you’ll get more papers or more consulting (or whatever it is that is driving you to be in this game). And the end result… may be the modeller will be contributing more to the future of the health sector, particularly in relation to patient flow issues.

References:

Mackay M (2006). Nosokinetics - staking our claim. Nosokinetics News, June, vol 3.3 pg 4-5.

Gladwell M (2000). The Tipping Point: How Little Things Can Make a Big Difference. (ISBN 0-316-31696-2)
http://en.wikipedia.org/w/index.php?title=Special:Booksources&isbn=0316316962 first published by Little Brown and Company, Great Britain.

Michalewicz Z, Schmidt M, Michalewicz M and Chiriac C (2006). Adaptive Business Intelligence. Springer, Berlin.

Fone D, Hollinghurst S, et al. (2003). "Systematic review of the use and value of computer simulation modelling in population health and health care delivery." Journal of Public Health Medicine, 25(4): 325-335.

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