Model 4: data, information, knowledge, wisdom

The Model from Infovis below shows just what I always struggle in explaining to tohers as to why the results of one project cannot just be pushed onto other, adopting, groups.

The producers, the pilot projects, create the basic data and some information (patterns) about it. The consumers (the adopters) need to retest this in their own environment.  Any pilot project that can be written up in a way that helps the consumer to bridge the gap from information to knowledge will likely be more successful at spread than others. This can include things like: you can adapt this in the following way, we did the following and it didn't work but it may work in xyz circumstances etc.

Model 3: data, information, knowledge, wisdom

One of the QI refrains is "increase the capability and capacity of employees". While this is a great concept, easy to declare and impossible not to support, for me it lacks any concrete applicability. What exactly is meant by this? There is another one of our data-information-knowledge-wisdom models which may help pin down what might be meant. Next time you hear somebody say the capacity/capability thing then whip this model out and ask them to explain their intentions and expectations along the data to wisdom curve.

 The challenge here is to produce learning experiences that enable someone to move up the curve. In my experience, much of healthcare improvement work is focused on developing data based skills - how to measure change. Some people get to the information stage where they learn to look for patterns, say by using SPC charts. Can they port this knowledge to other projects in a predictable way? Can they make intelligent choices? To what extent do the participants on a QI project become "wise"?

The above curve comes from Designing Knowledge Eco-Systems for Communities of Practice.  The web resources are excellent - especially if you are developing CoP's as part of your QI strategy.

Model 2: data, information, knowledge, wisdom

There is an excellent post about wisdom on one of my favourite sites - Big Dog and Little Dog's Performance Juxtaposition (yes, really!).  It's a place I recommend you spend some time checking out.

I like the way this model gets me thinking about how we learn - there are connections here to the Honey & Mumford Learning styles.  The fact that there is a continuum for context is also thought-provoking.  This model has left me wondering whether in many of our quality improvement projects we focus too much on the bottom left hand corner and assume the progression to wisdom will be automatic. What would happen if we thought more and designed more of the journey to wisdom into our improvement interventions (and by extension, into our evaluations of projects)?

Model 1: data, information, knowledge, wisdom

The old adage goes along the lines that knowledge can be defined as knowing a tomato is a fruit, and that wisdom is therefore knowing that you don't add a tomato to a fruit salad...  There are a number of models and frameworks that investigate the data-information-knowledge-wisdom continuum and in the this series of posts I cover a few of these.

For the theorist a good place to start is with an online paper A Primer:, Enterprise Wisdom Management and the Flow of Understanding by ScottCarpenter@CognitiveCybernetics.com

I like the way environment and context have come into play as important factors in understanding that knowledge and wisdom have a contextual perspective.

New Paper: What is the experience of national quality campaigns?

I liked the conclusion in this paper - "..may depend on.." as it summarised my experience of national quality campaigns - the results depend on a multitude of factors - and I would add depends on the perspective/s of the stakeholders involved.

 Health Serv Res. 2010 Dec;45(6 Pt 1):1651-69.

What is the experience of national quality campaigns? Views from the field.

Bradley EH, Nembhard IM, Yuan CT, Stern AF, Curtis JP, Nallamothu BK, Brush JE Jr, Krumholz HM.

OBJECTIVE: To identify key characteristics of a national quality campaign that participants viewed as effective, to understand mechanisms by which the campaign influenced hospital practices, and to elucidate contextual factors that modified the perceived influence of the campaign on hospital improvements.

CONCLUSIONS: The impact of national quality campaigns may depend on both campaign design features and on the internal environment of participating hospitals.

New Paper: Short and long term effects of a QI collaborative on diabetes mgt

I'm always on the look out for evidence of the sustainability of QI projects. A new paper in Implementation Science has some thoughts on this though I am not convinced 1 year classes as "long term".

Implement Sci. 2010 Nov 28;5(1):94. [Epub ahead of print]

Short- and long-term effects of a quality improvement collaborative on diabetes management.

Schouten LM, Hulscher ME, Van Everdingen JJ, Huijsman R, Niessen LW, Grol RP.

ABSTRACT:

INTRODUCTION: This study examined the short- and long-term effects of a quality improvement collaborative on patient outcomes, professional performance, and structural aspects of chronic care management of type 2 diabetes in an integrated care setting.

CONCLUSIONS: At a time of heightened national attention toward diabetes care, our results demonstrate a modest benefit of participation in a multi-institutional quality improvement collaborative focusing on integrated, patient-centered care. The effects persisted for at least 12 months after the intervention was completed.