Multilevel Interventions in Health Care Conference: Presentation by Brian Weiner, PhD

Uploaded by NIHOD on 05.05.2011

>>>DR. STEVEN CLAUSER: The next session has really kind of
transitioned us into really talking about getting into some
of the real applications, on the challenges and opportunities,
as it is called, for multi-level intervention research.
And in particular, we are going to be looking at
practical ways of trying to figure out do we select
interventions, what are some of the conceptual and
theoretical issues about timing and other things and
thinking about appropriate interventions.
And then talk about some of the research methods that are very
appropriate for thinking about getting into this field in a
way to really address some of the extraordinarily challenging
conceptual questions that we talked about this morning.
So my first speaker is going to be Brian Weiner,
he is professor of the Department of Health Policy and
Management at the School of Public Health at the
University of North Carolina Chapel Hill. Dr. Weiner is a
good friend and he's also Director of the Program of
Healthcare Organizations at the Cecil Sheps Center for
Health Services Research. His research focuses on such things
as adoption, implementation and sustainability of innovations,
very appropriate for this meeting, in healthcare
organizations and he earned his PhD in organizational
psychology from the University of Michigan.
>>>DR. BRIAN WEINER: So I would like to begin with a Sufi
teaching story that goes something like this.
You think that because you understand one,
that you also understand two because one and one make two.
But you forget that you must also understand "and."
And I think that actually does a nice job setting up this
particular talk and the paper that we have wrote about the
search for synergy. And in the interest of disclosure,
we are going to shift in this particular ten minutes to a
different model of thinking about multi-level interventions
from the biopsychosocial model that Steve Taplin represented
to the social ecological model, which was one of the three
that he mentioned. So if you feel confused, that's probably
because this is a good example of where different people
using the word multi-level have different ideas about what
that means. So I just want to alert you to that.
The social ecological perspective provides a very
compelling justification for multi-level intervention.
While there are numerous variants of the social
ecological perspective, they share three - excuse me,
two basic principles. The first is that human health
results from the complex interaction of personal factors
and multiple aspects of social and physical environments.
The second principle is that these multiple factors that
influence health are interdependent,
that is they mutually influence each other.
On the basis of these two principles,
proponents of the social ecological perspective contend
that multi-level interventions should be more effective
than single level interventions. The key to designing an
effective multi-level intervention, however, they
note, is to select and combine interventions that work in
complimentary or synergistic ways. All good advice.
Conspicuously absent, however, are discussions of how,
when or why interventions at different levels of influence
work together in mutually reinforcing ways.
The problem is that without such guidance,
multi-level intervention designers run the risk of
combining interventions that produce scattered,
redundant or even potentially contradictory effects.
So using a causal modeling framework,
we described in the paper, and I will briefly touch on it
during this ten minute presentation,
five strategies for increasing the potential complimentarity
or synergy among interventions that operate at different
levels of influence. Given the importance of interdependence
in the social ecological framework, we focus on two
types of causal relationships, mediation and moderation to
illustrate the potential strategies for increasing
synergy or complimentarity. We, in the paper, and as you'll
see in the slides that follow, focused on multi-level
interventions designed to improve the quality of
treatment for locally advanced rectal cancer.
In the accumulation strategy, interventions at different
levels produce a cumulative impact on a common mediating
process or pathway. Note here that the effect of each
intervention in this particular strategy is not conditional
on the other interventions. Rather, the interventions
exhibit what scholars and organization science called
pooled interdependence, meaning that the intervention,
each intervention makes a discrete contribution to the
outcome through the mediating variable or pathway
without being dependent upon each other.
In the amplification strategy, by contrast,
the effect of one or more interventions is conditional on
another intervention. One intervention increases the
target audiences sensitivity to or receptivity to the
other interventions. That is, one intervention amplifies the
effect of other interventions on the mediating process
or pathway. And so you can see in this example the
use of reimbursement is used to increase the sensitivity
to or receptivity to changes in public reporting or
interventions that are designed for public reporting or an
opinion leader intervention is trying to change social norms
around the provision of chemo radiation therapy for patients
with locally advanced rectal cancer.
For those of you who are curious, this particular
strategy exemplifies a form of mediated moderation.
In the facilitation strategy, the effect of one or more
interventions is, again, conditional on another
intervention. However, instead of boosting the signal,
the conditional intervention, in this case the clinical
reminder, clears the mediating pathway for the other
interventions to produce the desired outcome.
In other words, one intervention removes the barriers
or facilitates the effect of the other interventions.
This strategy is another form of mediated moderation.
In the cascade strategy, an intervention at one level
affects the desired outcome in and through one or more
interventions at other levels of influence.
The interventions demonstrate what scholars refer to as
sequential interdependence meaning that the outputs of an
intervention at one level become the inputs of an
intervention at another level. By linking multiple mediating
processes into an integrated causal pathway,
cascading interventions create a circuit through
which the effects of interventions combine and flow.
And I must say, I have a little bit of concern about calling
this the cascade strategy because it implies a trickle
down effect, but in fact it is quite possible for the effect
to trickle up. Many of who have worked, for example
in the community care network study or in community
empowerment studies or in community based research know
that sometimes in order for interventions at lower levels
of influence or smaller units of human organization to
be effective, change has to occur at a higher level of
influence or a higher level of, a higher unit of analysis.
And then finally, in the convergence strategy,
interventions at different levels mutually reinforce one
another by altering the patterns of interaction among
two or more target audiences. The interventions in this
particular strategy exhibit what scholars call reciprocal
interdependence meaning that the outputs of some interventions
become the inputs of other interventions and vice versa,
so that's the difference between the sequential and the
reciprocal forms of interdependence.
They are not necessarily linked in a chain, but rather
there is this constant back and forth. I Know that
is just a gloss of what we talk about in the paper and
I certainly hope that you will be intrigued enough to read it.
I think what we have tried to do in this paper is to develop
a general framework to guide people's thinking about the
causal logic for multi-level interventions. And this can be
useful not only for intervention designers, but also for
reviewers of multi-level intervention proposals.
I think what we wish to do is to avoid a kitchen sink
approach, which can be very wasteful and expensive and
perhaps burn through a lot of goodwill among stakeholders
and communities, healthcare delivery systems and the
patients and families. Theory and research clearly play
a critical role in clarifying the causal logic for combining
interventions at multiple levels and this raises several
questions for discussion. The first is, do we have theories
that explain how determinants at multiple levels of
influence produce health or other outcomes?
I might be over-exaggerating, but it seems to me that we have
psychological theories that look at intra-personal factors,
we have organizational theories that look at organizational
factors and we have political theories that look at political
factors, but they don't necessarily look at how factors
at multiple levels of influence interact in order to produce
health and other outcomes. The second question is do
we have enough cross level research that examines the
interdependence of variables or determinants at
multiple levels of influence? What I think we need
more of is sort of cross level research.
So if we are going to stick with the innova framework and
think about multi-level modeling, we need to not
only focus on which level explains the most
variants or which factors at any given level explain the
variants at that level, but we really do need to be looking at
cross level effects in order to understand the interaction of
causal factors at different levels of influence.
And then finally, do we have a sufficient grasp of the causal
mechanisms through which many commonly employed
interventions produce their effects?
Now I have been struck by several papers that have been
published in Implementation Science and other journals that
have looked at the intervention of audit and feedback which,
as many of you know, has been studied in hundreds, or at
least tens, if not hundreds of times in various places.
But it's only really in the last two or three years that
we have begun to ask the question how or why does
audit and feedback work? In other words, what is the theory
about the causal mechanism through which this works?
And some very interesting work is now occurring;
it is just surprising to me that we had to do forty or fifty
studies before somebody finally wrote a paper about that.
So those are the three discussion questions that I
would like to encourage the individuals at the tables to
take up when we have our discussion time. Thank you.