Report: Virtual QI Collaborative

It seems to have taken years for the QI family round the world to gain their trust in virtual improvement programs. My personal experience is they can work as effectively as face-to-face programs, although they need to be designed to work in a different way and need proper virtual facilitation.

There's a useful report about a virtual QI collaborative from the Robert Wood Johnson Foundation. The results look pretty good to be.

Model 7: data, information, knowledge, wisdom

I thought I would stop at 7 models on the data, information, knowledge and wisdom theme - afterall, the brain is supposed to be able to hold a maximum of seven thoughts at any one time.  I've left my favourite to last. I particularly like the examples given at each stage. You can read more about this model on this blogsite.

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 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. 

New Paper: How to use an article about quality improvement (JAMA Nov 2010)

One of the difficulties in spread and adoption is, on the one hand avoiding the temptation to take the results from one project and then do a back of the envelope calculation and announce if the results were spread then there would be x billion savings etc; and on the other hand, if you're a project lead, how do you read a piece of evidence and work out its relevance for your own work?  There is a new paper out which touches on this subject.

 JAMA. 2010 Nov 24;304(20):2279-87.

How to use an article about quality improvement.

Fan E, Laupacis A, Pronovost PJ, Guyatt GH, Needham DM.

Abstract

Quality improvement (QI) attempts to change clinician behavior and, through those changes, lead to improved patient outcomes. The methodological quality of studies evaluating the effectiveness of QI interventions is frequently low. Clinicians and others evaluating QI studies should be aware of the risk of bias, should consider whether the investigators measured appropriate outcomes, should be concerned if there has been no replication of the findings, and should consider the likelihood of success of the QI intervention in their practice setting and the costs and possibility of unintended effects of its implementation. This article complements and enhances existing Users' Guides that address the effects of interventions--Therapy, Harm, Clinical Decision Support Systems, and Summarizing the Evidence guides--with an emphasis on issues specific to QI studies. Given the potential for widespread implementation of QI interventions, there is a need for robust study methods in QI research.