Paper: Complexity science and spread

Well, the best bit about this paper for me is the introduction of the terms SUS - scale up and spread!  It focuses on self organisation (complexity science principle) and how the complexity of healthcare and all the interactions are part of the problem of SUS programs.

Now, I'm biased and I'm with Ralph Stacey who says that when we think we can "control" or "use" self organisation then we are operating with a mindset not much different from Taylorism (see his work on complex responsive processes which superceded complex adaptive systems around 2001).

Whilst using insights from complexity science is useful, it is just that - an insight. When it comes to moving on to a more practical thought about - "so what do we do now", CAS and Complexity Science as such, falls flat.  There is a well trodden, pragmatic and practical systems theory and modelling that would be helpful in understanding interdependences - "Systems Thinking". Unfortunately it requires a bit of effort to grasp and seems not to have the cachet of "complexity science". Shame.

Soc Sci Med. 2012 Jul 4. [Epub ahead of print]
How complexity science can inform scale-up and spread in health care: Understanding the role of self-organization in variation across local contexts.
Lanham HJ, Leykum LK, Taylor BS, McCannon CJ, Lindberg C, Lester RT.

Paper: Developing clinical guidelines - excellent set of papers

Here is a paper (series of three) from authors who are experts in this field. I've always been a bit ambivalent as to whether guidelines actually work - in terms of changing behaviour. I'm still not convinced but it's good to see a bit more work being done to identify the target audiences for guidelines as well as considering conflicts of interest etc.  Getting them right is a lot more complex than just collating what seems to be best practice, writing it up and then distributing them widely.

Oh, and the full text of the papers is free - that's nice. http://www.implementationscience.com/series/ClinPracGuidelines

Developing clinical practice guidelines

Edited by: Prof Martin Eccles, Dr Paul Shekelle 

Collection published: 4 July 2012

These articles describe the state of the art in developing clinical practice guidelines. As well as updating on established areas, such as evidence review and group composition, they also address contentious areas - conflicts of interest - and new and emerging topics including updating guidelines, dealing with co-morbidities and guideline implementability.

(Picture and text above is from the Implementation Science Webpage)

90 Day Projects

I've written about 90 day projects over the last couple of years:

1. How to implement 90 day projects
2. What are 90 day projects
3. Large Scale projects are seldom a linear process
4. Push vs Pull: Twitter Case Study 90 day Project

Many months on I am still convinced that we spend far too long on our healthcare projects. The tradition is they are planned for 18 months - often regardless of the size and difficulty of the change required. There are some changes which may need to be part fo a three to five year project, and others that can be achieved in 7, 30 or 90 days.

If you have examples of 90 day projects successful or not, then please leave a note in the comments. Thanks

Test, Learn, Adapt: Developing Public Policy with Randomised Controlled Trials

A good friend, Bill Russell, told me about a paper produced by the UK Cabinet Office calling for Randomised Controlled Trials for Public Policy. I was sceptical. When he told me Ben Goldacre (author of the excellent book, "Bad Science") was involved I was intrigued, and then wondered whether it was a spoof. But it isn't.

Hallelujah!

This paper is required reading. [update: new link] I commend it to you all and especially those I've been trying to convince for years that spreading improvements or innovations can have an ethical bias - how do you know it's a good and effective thing to spread?

And when you've read it - read it again. This has to be the best paper I've read for some years.

(I hope someone has passed it on to the Department of Health and the NHS Commissioning Board.)

Please. No. More. Research. We. Need. Action.

Now before you send me a complaint, I'll start by saying I do believe that research is a good thing. However, we can have too much of a good thing.

The February Editorial in Implementation Science pitches the question as to whether we need a scientific study for research on how to improve healthcare. Here are my thoughts:

• I am not convinced we need any more "what" when it comes to improvement; we are drowning in good practice, guidelines etc.
• When it comes to the how" then I'm more interested in getting people to the "do" stage of making changes, than in spending more time pondering how best to go about it.  By doing, the people learn.
• Researchers, and I'm a closet researcher so I know, tend to be separated from the real world in time and space. 
• I suspect we have 80% of the "how" that we need to improve healthcare. What we lack are the people within healthcare who are sufficiently motivated to make the changes - or get out of the way of people who are motivated to make the change

Implement Sci. 2012 Feb 29;7:10.
Does the world need a scientific society for research on how to improve healthcare?
Wensing M, Grimshaw JM, Eccles MP.

Dissemination Science. OK, that's a useful way of thinking about it.
A framework for training competency in implementation and dissemination science - now that sounds very useful.

Acad Med. 2012 Mar;87(3):271-8.A framework for training health professionals in implementation and dissemination science.Gonzales R, Handley MA, Ackerman S, Oʼsullivan PS.


This is their abstract

"The authors describe a conceptual framework for implementation and dissemination science (IDS) and propose competencies for IDS training. Their framework is designed to facilitate the application of theories and methods from the distinct domains of clinical disciplines (e.g., medicine, public health), population sciences (e.g., biostatistics, epidemiology), and translational disciplines (e.g., social and behavioral sciences, business administration education). They explore three principles that guided the development of their conceptual framework: Behavior change among organizations and/or individuals (providers, patients) is inherent in the translation process; engagement of stakeholder organizations, health care delivery systems, and individuals is imperative to achieve effective translation and sustained improvements; and IDS research is iterative, benefiting from cycles and collaborative, bidirectional relationships. The authors propose seven domains for IDS training-team science, context identification, literature identification and assessment, community engagement, intervention design and research implementation, evaluation of effect of translational activity, behavioral change communication strategies-and define 12 IDS training competencies within these domains. As a model, they describe specific courses introduced at the University of California, San Francisco, which they designed to develop these competencies. The authors encourage other training programs and institutions to use or adapt the design principles, conceptual framework, and proposed competencies to evaluate their current IDS training needs and to support new program development."

Quality Improvement Collaboratives - New Paper

There's a new paper out (see below) which comes to a conclusion similar to ones found a few years ago - namely, in Quality Improvement Collaboratives, teams where the members have low knowledge of the topic or improvement science, are the ones which come out best. It also demonstrates that good leadership trumps the teaching of theory.

I've always thought that the more we push theory under the guise of "Improvement Science" at these short term interventions, the more we may confuse participants and in fact create a type of "performance anxiety" where they become afraid of doing what comes naturally, because it has been turned into what appears to them as a right-wrong application.

Implement Sci. 2012 Jan 9;7(1):1. [Epub ahead of print]
Factors associated with the impact of quality improvement collaboratives in mental healthcare: an exploratory study.
Versteeg MH, Laurant MG, Franx GC, Jacobs AJ, Wensing MJ.

ABSTRACT:
BACKGROUND:
Quality improvement collaboratives (QICs) bring together groups of healthcare professionals to work in a structured manner to improve the quality of healthcare delivery within particular domains. We explored which characteristics of the composition, participation, functioning and organization of these collaboratives related to changes in the healthcare for patients with anxiety disorders, dual diagnosis, or schizophrenia.

METHODS:
We studied three QICs involving 29 quality improvement (QI) teams representing a number of mental healthcare organizations in the Netherlands. The aims of the three QICs were the implementation of multidisciplinary practice guidelines in the domains of anxiety disorders, dual diagnosis, and schizophrenia, respectively. We used eight performance indicators to assess the impact of the QI teams on self-reported patient outcomes and a number of process of care outcomes for 1.346 patients. The QI team members completed a questionnaire on the characteristics of the composition, participation in a national program, functioning and organizational context for their teams. It was expected that an association would be found between these team characteristics and the quality of care for patients with anxiety disorders, dual diagnosis, and schizophrenia.

RESULTS:
No consistent patterns of association emerged. Theory-based factors did not perform better than practice-based factors. However, QI teams that received support from their management and both active and inspirational team leadership showed better results. Rather surprisingly, a lower average level of education among the team members was associated with better results although less consistently than the management and leadership characteristics. Team views with regard to the QI goals of the team and attitudes towards multidisciplinary practice guidelines did not correlate with team success.

CONCLUSIONS:
No general conclusions about the impact of the characteristics of QI teams on the quality of healthcare can be drawn, but support of the management and active, inspirational team leadership appear to be important. Not only patient outcomes but also the performance indicators of monitoring and screening/assessment showed improvement in many but not all of the QI teams with such characteristics. More studies are needed to identify factors associated with the impact of multidisciplinary practice guidelines in mental healthcare.

Does opinion leadership change over time? New Research

I'm pleased to see useful research is being done to clarify further what we mean by opinion leadership. Too often I hear people reducing what is a very complex topic to a simple slide of Roger's characteristics. Roger's initial work on the Diffusion of Innovations was researched and published before the age fo the Internet and before many staff were born. We need updates and we need to grasp a deeper understanding of the complexities.

There's a new paper out.
Implement Sci. 2011 Oct 11;6(1):117. [Epub ahead of print]
Opinion leaders and changes over time: a survey.
Doumit G, Wright FC, Graham ID, Smith A, Grimshaw J.


I've posted the conclusions to this paper below - and recommend you read the original.


"CONCLUSIONS:
Opinion leaders identified in this study were not stable over a two-year time period and generally appear to be monomorphic with clearly demarcated areas of expertise and limited spheres of influence. These findings may limit the practicability of routinely using opinion leaders to influence practice."

The meaning of Implementation Climate

I've just read a new paper about implementation climate and how it differs from organisational climate - all part of the "readiness for change" strategies than many of us use.  You can read the whole paper at Implementation Science (online - open access). I've pasted the abstract here, though I recommend you read the whole paper.

The meaning and measurement of implementation climate.

Weiner BJ, Belden CM, Bergmire DM, Johnston M.

Abstract

BACKGROUND:

Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study.

DISCUSSION:

Implementation climate differs from constructs like organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational-level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual level theories of behavior change could be more useful in explaining implementation effectiveness.

SUMMARY:

This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use.