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I'm Pat Remington, and I'm
The first Monday of each month, the the institute sponsorsute.
a seminar.
here... I'm g( laughter )Pat Remington
to give this month's seminar. This actually was a stand in
for a guest that we had hoped to bring in.
I did look back over the seminar
over the past couple of years and noticed that I'm a fairly
regular presenter.
any old work that I've already So I had to filter out
that we're doing presented and focus on new work
*So, this is the outline withinfor today.tute.
And I want to leave time
or comments about some at the end for any questions
I'll begin with-- ofIs that all right, Denny,g.
or is it my angle?
With a background on the issue* It looks dark.
information to improve of using surveillance
It's a specific aspect of my work that I have been doing
since I really started working
and Epidemiology in Public Health
I'll talk about three ongoing public health surveillance
activities that we have been putting a lot of time
and effort in at the institute, and then talk about this issue,
and the focus really of how to evaluate the impact
of surveillance information to improve populations health,
and then conclude with some next steps that we're taking.
*So, some of you may be aware
others may not. Now almost 20 years ago,
the Institute of Medicine established a committee
to look at the public health
It published a very troubling, system in the U.S.
in public health. but It was entitledport
the "Future of Public Health."
"In recent years..." The main quote is that,
"...there has been a growing And this is again, 1988.
as a profession, sense that public health
and as a commitment of society as a governmental activity,
adequately supported, is nor fully understood."d,
And the term used is that the assessment of the Institute
of Medicine was that
was in disarray 20 years ago. *As a result, the committee
looked, not at defining public health as what you do
in government, but what you can do well, and so it
came out with a recommendation
get out of the direct delivery of services, primarily
healthcare for the poor, and
And those were defined as: go back to its core functions.
looking at assessment, surveillance,
then driving policies with those data, not so much
in program delivery,
and then finally the assurance but in policy development;
services are not being provided, function that if in the end
is the provider of last resort. *This core function
of assessment is one that I've spend quite a bit of time
working on when I was at the CDC from 1982-1988,
and worked on one important surveillance system
that was developed then,
surveillance system to broaden this core function
to not just infectious diseases and mortality data,
but include behavioral
quality of life information and really brought surveillance
from a national stage to a state and local stage.
It's obviously the collection,*
of information on the health of the community, and it includes
all sorts of things everywhere. People debate whether
surveillance, in fact, or the assessment function includes
the use of this information in policy development.
But most people feel that simply
disseminating it collecting the information,
it being used for policy without an eye towards
would be an incomplete or program development
*And this is a model that assessment role.
Rick was the editor of the MMWR. Rick Goodman and I--
Health Law program at CDC. He now directs the Public
loop from data collection, The CDC taught this surveillance
and then dissemination. And again, when Alex Langmuir
developed this CDC
the idea was, this is really Epidemic Intelligence Service
of information collection, the surveillance loop, the idea
But the move has really been interpretation, dissemination.
at the same time for the information
to then revise that you're using your analysis
is to incorporate the data your data collection efforts
understand the importance of fidelity of program
or policy implementation, and then have data systems
in place for evaluation.
surveillance cycle operates So rein close concert withtion*
the program planning and public health improvement effort.
*Well, 15 years passed and the Institute of Medicine
came back to revisit
and issued a new report. the future of public health
the "2002 Report," Sometimes people call it
but technically tit was published in 2003.d
And the major change 15 years later, is that when looking
at the future of public health
health system in 1988, and the view of the public
focused on the governmental role the Institute of Medicine
in those three core functions. in public health
and the public health agenda *But as time went on
not just infectious diseases expanded to include,
but violence, and depression, orand chronic diseases,s,
the Institute of Medicine recognized the importance
of not just government, but healthcare, employers,
media, the community, and academia, and shifted
the frame from strictly focusing
of public health on the governmental function
And in fact, notice this to a broad partnership.
of the report. subtle change in the title
"Future of Public Health," Rather than the
this is "The Future wof the Public's Health."
And we in public health notice
an apostrophe and an "s" that if you just change, or add
themselves to be part of immediately, people consider
as opposed to the limited focus of public health, which is
equated with governmental public health.
*And here is the new IOM view
the center or the mainstay for of government not being at
but rather one of several partners that focus on
ensuring conditions for population health.
And these obviously, again, are the community based
organizations,
businesses, purchasers, healtmedia and academics.ers,
*Well, the challenge then, really is I think,
in let's see 2017,
will come back and revisit the Institute of Medicine
did we do in engaging these new system partners,
and in particular, how does this
relate to the role broader public health system
public health departments. for state and local
the broad members *In of the community realizek
they're a part of this new
I think that's a concept public health system.
within public health that has been hatched
of Medicine committee, and a small Institute
by others in the community. but*So, obviously my biasopted
to the answer to the second question is
the core function of assessment.
of governmental public health in data collection, analysis
and dissemination.
three major projects *Well, we have worked on
the State Health Department, in collaboration with
widely accessible data. There is a whole new effort.
Robert Wood Johnson has supported an effort called
Web-Based Data Query Systems. And this is a not yet
sort of publicly announced, but the idea is that 25 states
now have data that are
data query systems. The idea of the RWJ foundation
is to really improve
to access fairly complex the ability of practitioners
web-based data query systems. *Well, Wisconsin is one of
the leaders in the nation at having the data available.
So for all of these,
that we can obtain online. we have much of the data
One is the look at this idea *I'll talk about these three.
I did talk about this ofat a previous seminar,.
so I won't dwell on that. And then this summer,
we put out a health report card.
to give this seminar, I think, Dave and I were going
so I did want to mention that. in September on this,
our county health rankings, which I think are available
and have been passed out. It's just been released
a couple of weeks ago.
a graduate student worked with *At first, Angie Kempf,
and Dave and me Bon this analysis ofd,
the burden of excess mortality. So when mortality data
are widely available, a standard metric
in population health. However, it's hard to compare
and contrast rates. We find that people,
in particular,
when you talk about a rate in smaller communities
a population of 10,000 per 100,000, and they have
Rates tend to have less meaning we'rethan absolute numbers.ans.
And so we used, rather than indirect standardization,
we directly, in effect, adjusted state mortality rates--
not state mortality rates,
in any county to the population actuallof that community.ty rate
And did it for every age group. *We averaged 10 years of data
to come up
And then we simply with stable estimates.
by the observed rate multiplied this best rate
with an excess in deaths. The difference
between the two rates multiplied by the population
in that age group gives you an excess number
of deaths in that community.
the age groups are shown here. *So here are the counties,
The names of the counties Hewith the best rates.
of the 72 counties in the state.
has an infant mortality rate You can see Wood County
Waukesha county has othe lowest death rate.
for kids 1-14,
all the way down to 65-74. 12 per 100,000,
premature mortality. This is under 75,
it's not always the same county, *And when you look,
I mentioned three times. but Waukesha,
Calumet, Pepin, relatively small rural counties,
but fairly healthy with respect to premature mortality.
*Well this is a spot map showing where each of these
premature deaths would be located across the state.
Obviously, they are randomly
But the number of dots distributed within the counties.
Each dot represents one excess death.
Oh, and then the total
using this method is-- for the state,
about 5,000 would be occurring in excess
of what would be occurring
had the best mortality rate observed in one county.
This is what the state
You can see lots of dots here. looks like.
within the city of Milwaukee, the rest of the county is 320.
So about 1600 of the 4800 excess deaths
occur in Milwaukee county.
the city of Milwaukee, And when you look at the state,*
and the urban counties, texcept the cities.
These are the population
of the five million people distributions
during this study period. iAbout 11%te
live in the city of Milwaukee;
and about 57% 32in Urban counties.s;
But when you look at
almost 2.5 times the premature deaths, about 28%,
are in Milwaukee, the city, and 1600 in rural counties,
about comparable
and the urban counties to the population distribution;
excess of deaths. hAnd this is a bar chartss
showing the same information. Population distribution
in the city, urban counties and rural counties, and again
a much different distribution when you look at
premature mortality.
graphically, and this is about So if you look at it
of premature deaths in the city of Milwaukee.d
These urban counties, about another third.
Then the balance of the state,
So, the major finding from this* is that the city of Milwaukee
has about 28% of the state's excess mortality,
and the balance is equally divided between
urban and rural counties. We presented this information
to the city of Milwaukee, the Mayor of Milwaukee
a couple of years ago,
last Friday morning, presented it again
And clearly this has been used when the Mayor was present.
by the mayor, byto keep focusing attentiont,
on not just high rates
in Milwaukee, but the burden for the state
that he titled his session
a recent editorial, as "As Goes Milwaukee, So Goes
the State of Wisconsin."
of premature mortality, WithMilwaukee necessarilyhare
pulls down overall
for the state. population health indicators
a major surveillance project *A second example of
and this is really that we've worked on,
is the Wisconsin Health with DaveReport Card.adership,
This focuses on our state health plan's goal,
which is for 2010, to protect and promote health for all
and eliminate disparities.
at ways to make Wisconsin So thethe healthiest state look
with less disparity.
the UW Partnership Program. *By way of background,
the America's health rankings measures the population health
of all 50 states. It's been doing it for 20 years.
Wisconsin used to rank 4th, 5th or 6th.
And over the decade,
to 10, 12, even 14. So there's a sense that
not only is Wisconsin not moving ahead in the country,
but actually dropping in its relative health ranking.
America's health ranking
looking at determinants doesand health outcomes,dly,
but it doesn't really look at health disparities within state.
It focuses more on mean or overall population
health measures.
have measured disparities, but *Other organizations
and certainly has not given notthe measure of disparityn,
a value.
what might be ideal, That is, a reference to
to what we currently observe. *This is an important finding
that Angie pointed out. She was searching the literature
and found some reasons
on the health of America. for This is published inngs
the November 14 issue of the "Onion."
New York's rank drops precipitately from 8th to 27th.
And people think
now forcing residents to mug or murder one another.
High rates of murder
higher mortality rates. New Jersey, there was a clerical
error in the medical records, it's been corrected.
Illinois, it extended the legal limit for deep-dish death.
Nevada, 38 wasn't working for them, they're trying
their luck on 39. Wyoming actually improved
in health, and the health department told all
unhealthy people to stay home when the united health
foundation was in town. This is suppose to be funny.
( laughter )
But I think it's really telling that when you make it into
the "Onion," you've really, it's almost like
being on "Letterman." ( laughter )
People are paying attention to health ranking.
*This report card, which we also handed out,
grades Wisconsin
but on health disparities. not just on mean health,
and within population subgroups. It looks within life stages
to look at how And we're just beginning
and by disparities you measure health overall,
mortality and health-related and use two measures,
We're actually working towards quality of life.
of population health broader measures
These are available, generally, by subgroups, by gender, race.
and social and economic factors.
are not. Some of the determinant data
of the report card. And This looks likeults
an easy thing to do.
to finally agree on a system and It took us a long time
*Dave Kindig had this idea in his mind from the beginning
and he won in the end.
an overall health grade The by life stage,have
and Wisconsin would get a "B-". And I can talk about the
technical details of that.
if you look at the distribution Iwithin each age groupt
of each metric, that we used a standard
deviation to say that some states
are excellent and some are failing.
But that within this
a half-standard deviation unit, standathat most gradest, or
would be right in the middle. So Wisconsin is near the top,
but to get an "A",
one, or two, or three states. *Health disparity is measuredp
in a little different way,
that you look at in that ideally every group
And we total up all the possible differences,
that if the mean was an "A",
or the best group was an "A", that every grade down
would be a measure
*And we said that it'd be of total disparity possible.
just a little bit of disparity, but if there's a lot
of disparity that isn't so good.
then, of disparity. *Again one might argue, andon,
I'm looking for your feedback,
to what otherwise would be that this adds a value statement
or risk difference. This says that this is
pretty good and this is pretty bad.
And our purposes--
Our purposes are for I'll get back to it--
the surveillance information not to just have
the community in discussion. be disseminated, but to engage
actually. And this shows, along the X-axis
is the mortality rate for working age adults,
ages 25 to 64 per 100,000 population.
And these are age-adjusted
You can see from 100 to 700. within that age range.
is Minnesota. TheThe worst state257
is Mississippi at 519.
right here at 296. Wisconsin comes out
to worst state, this is the range in the country.
And then each of these flags
in the state represents a subgroup
some college women from Asians, college grads,
Those are all above the best state, and would be
excellent on a national scale.
non-urban residents, Then very good would be whites,
This would be a "C" for men. and rural falling in here.
is poor, down here. And then, those with high school
education or less,
and African Americans would get failing grades
down at this end of the tail. So any questions about this?
It's a simple way to show what otherwise is in the data,
it's just stratifying the overall mortality rates
by gender, education, race, and place of residence.
And this is the standard
*Well, one of the questions mortality data.
is obviously, this is the mean. So here's our mean.
Pretty good, "B-".
is not very good. ButYou'd like to see all ofre
the flags pretty close together so that there's
little or no disparity. But clearly, we have
considerable disparity
So one question would be, what would be the impact,
now focusing on race, Asians, whites, Native Americans
and blacks. What if we asked the question,
the policy question,
on Wisconsin's mortality rate what wand ranking impact
if we eliminated disparities? And we define that as taking
any group that's below
and bringing it up to the next group above the state.
*So if you took
and improved mortality rates Native American mortality
I didn't hear any sort of gasp. Angie gets credit for this.
That was cool.
just in case people were-- You want me to show that again
Notice how the color changes. ( And the number.
She does contract out for Power Point lectures.
That's not it.
with those groups moving up? What is the impact for the state
moves up just a tad. Wisconsin's mortality rate
is although these rates Thare very low,son
the populations represented by these racial groups
are not very large, and it has
Wisconsin, overall, athe mean wouldn't change..
Still get a fall less than
although the number improves. *What if we then focused on
places, and moved the health
and the rural counties of Milwaukee County
non-urban counties, usort of small cities.e
And this is shown here. Again, eliminating
or significantly reducing the disparities,
the impact on the state.
not quite to Minnesota's Still improves it, brings it
but significantly improves it. low mortality rate,
I think, one of interest is, *The next issue which is,
obviously not programmed in this age group, men are
So one would call almost all deaths before 65.
certainly preventable,
So this disparity is real at least iand unlikely to women.
to be genetically based.
are genetically determined, Althougrisk behaviors.haviors
But if you, obviously,
and mortality that would the eliminated gender disparity
up to here. bring We would be the besty rate
in the country. Better than Minnesota,
down to 225.
is what would be the effect *Bof not focusing on racial
and ethnic minorities, but
This says high school or less, on those with lowest education.
It represents 40% of the population in the state,
not just in Milwaukee County
but these people obviously or in southeastern Wisconsin,
What would be the impact live throughout the state.
to be the same as people of bringing that mortality rate
or very close to college grads? Well, can see the impact of that
is Wisconsin's mortality rate drops to 206 per 100,000
and is clearly, by far the
*So what's the effect of heliminating disparity by race?
Some improvement in mean health in the state from 296 to 277.
Not insignificant,
geographic disparities for rural but not as great as eliminating
and certainly not as great as eliminating gender disparities.
And here, the biggest impact
the mortality disparities that we see based on education.
Bringing those with a high school education or less
to the same mortality experience
or more. of those with some college,
accomplish Dave Kindig's goal, And these too would
the healthiest state which is to make Wisconsin
The major finding from this is* in the nation.
in any category elidoes improve Wisconsin'sies
overall health, although
would be the elimination the greatest potential in gain
*Well, let me turn then to the third surveillance project
that we've worked on. And these are the county
health rankings.
in getting us started in 2003, Paul Peppard was instrumental
rankings. aObviously, Bridget Booske,
Dave Kindig, Angie Kempf, and now Jessica Athens--
Actually, every graduate student
has contributed to the rankings. that's worked with us
which I've handed out. This is the 2007,
we define health broadly, *Anot just outcomes, mortality
and health status, but these
We measured the health broad determinant categories.
In the last couple of years the city of Milwaukee
really wanted us
So we now separate out to have them on the rankings.
It is modeled after the United Health Foundation's
America's Health Rankings.
but then summarize these And we define health broadly,
And I remember Denny Fryback. measI once copied a lecture,es.
or actually his contribution
of population health chapter. I need to acknowledge Denny's
work for the last decade, or more,
on the value of summarizing population health,
not just in summary measures
This has turned out of to not only to be sort ofall.
an intellectual challenge, but
results very effectively. We're not mired in the details
of so many numbers. We can actually talk about
the health
It's turned out to facilitate in a communication more sonity.
than I originally thought.
of outcomes and determinants. *We pWe do spark discussioniew
of health issues, stressing the importance that
health is determined broadly. And we have seen discussion
about how insights
can be used to inform practitioners about what works,
or at least hypothesize about what works.
But then also there's been
additional resources a great move to draw
*Why rank? First, it's done all the time.
So it seems to work for others, law schools, hospitals,
counties. There isn't hardly a day
you go by when you don't open up
It just seems to build and say we rank, or this ranks.
of the media and the public. on the competitive juices
that consumers and policymakers can easily understand.
It does draw attention
And again, as I said, to reward entities for high ranking,
but also not in a way penalize, although that may be
an inappropriate use, but draw resources
to lower-performing counties. *Again this is the model,
very simply.
defined as not just mortality, Health outcomes in populations
are determined broadly but quality of life,
over the life course. And then there's something
you can do about it at the policy or program level.
We use a lot of different data.* This is taken a long time
to develop relationships
Bridget is still helping us wiwork with some ofns.
the healthcare entities to try and get data
that's population based and not provider based.
*And this is the model that is probably hard to see,
but you can see the handout.
driven by health determinants, The health outcomes are
and interventions. and influenced by policies
what makes up the model. And I'll just show quickly
a combination of years Again, health outcomes,
mortality measure. of potential life lost,
If there is a single metric of the health of a community,.
and you're forced to use one, people tend to fall back
to years of potential life lost before age 75.
But we draw in the general
give half the weight to this health status,
percent of adults saying measure of population health,
is only fair or poor. Then, the healthcare measures,
we give 10% of the determinant
and quality. weight to healthcare, access
from tobacco, diet, alcohol, Health behaviors, 40%,
and violence. Social and economic factors,
education income and
Then the physical environment, measures of social disruption.
over the last couple of years and wbased on feedback this
from the health department
and measures into air quality, water quality
*And this is the result, what people are interested in
talking about first,
the top performing counties. which is where are
was healthiest in both outcomes Oand determinants,,
followed by Waukesha. The bottom of the list,
Menominee county, the state's only Indian reservation
that's entirely a county, and the city of Milwaukee
second here.
we engage these communities much more from a problem-focus
then the communities
And this is a map of the state.* This is health outcomes,
a combination of mortality
You can see the northern tier counties
rank in the bottom quartile.
are surprisingly, right along Thethe interstate really,es
right up here Mauston, Juneau county.
You see a much lower health,
counties in central Wisconsin in faor western Wisconsin.acent
And again, Milwaukee, southeast Milwaukee and Kenosha County
at the bottom.
and you obviously see *Ththat there's quite a bit,
of correlation. Again, lower determinants rates
broadly defined central sand counties, and then the
southeastern part of the state. And this is a correlation
between outcomes
We wouldn't expect and determinants.
is quite a strong correlation. a perfect correlation, but this
that tend to be unhealthy in mortality are also unhealthy
in determinants,
I don't know how much ato make of the outliers.
It could be, and we tell this to these counties,
that Price County has a high mortality,
poor quality of life, but that their health determinants
are pretty good.
a community that's had It may be that this is
or healthier behaviors that it's economic development,
These are better determinants moving ithan outcomes.rection.
And these counties could be the opposite.
It could be that Florence County
good mortality rates, but that has got long-standing
is not as good. itBut again even engaginglth
in that discussion gets people at the table thinking
about how health is determined
in community health improvement. and what their role could be
a graduate student last year. We used to just sort of tell
the counties to go to the Web and read our spread sheets.
He put them into a snap shot
This is Dane County, which in a very easy way, you can see
the rank and determinants and outcomes.
Some stability here,
It seems to be moving up. pWe programmed some of that in,
because we used multiple years
so we sort of protect against ofwild swings in outcomesme,
and determinants. And you can see that this
is also reflected in the trends in mortality.
*This is Wisconsin and projection to 2015.
Dane County is consistently better.
And, if anything, maybe tracking
Here are the strengths a little better than the state.
Then we provide to the counties their detailed information
in healthcare, health behaviors.
For survey data, we put in You can see the county rate.
to be cautious about a margin of error,
Here's the state over-interpreting survey data.
Same for social and economic factors
and physical environment. And again Dane County,
72nd in environmental health. Very good in social
and economic factors. Number one in the proportion
of people without-- Let's see, no high school degree
or employment rates are best in the state.
But we've got bad air in Dane County compared to
the rest of the state.
third surveillance activity of ours is significant variation*
exists in health outcomes and determinants,
and the least healthy places
Menomonie County, City of Milwaukee, and some
of the central and northern rural counties.
*I'm actually going to skip over the problems.
There are no problems.
I will go to the problems. ( laughter )
the data aren't perfect. And this is not perfect,
too much from minor differences I think pin ranks.d to infer
We see it all the time. Once you engage community
members in a dialog,
the potential for over-interpretation.
Incorrect assumptions about distance between items.
This idea that
for low rank counties. there's low morale
of variables. The poAnd some countiesulation
can spin the data different ways
different ways. oWe have competing interests.a
We would like a stable model, but then as time goes on
we find new ways
and we tend to include it to meso that's a concernalth,
that the ranking three years ago
doesn't look like this year's. for environmental health
That's problem of interpretation We think it's a better measure.
when things are changing. And finally, this continues
to happen, the pressure comes on
What are you doing about it? the local health departments.
sword, in that we've worked with And actually, it's a two-edged
to redirect that back to the local health departments
broadly in the community. *So how do we evaluate whether
surveillance can be used
The first thing you have to do to improve population health?
And I think everybody-- is you hAnybody hereoticed.
not seen these slides?
You know, there's very few So that's amazing.
in the world has seen. surveillance sets that everybody
probably, in health, Everybody in the United States
But there's something about mthis map series that worked.
in population health. We really went from lack
of awareness about trends and obesity, and actually
these were some of the data that we helped collect
when we were at the CDC,
surveillance system. this behavioral risk factor
such a highly cited Had surveillance system.d be
*In trying to communicate
focus less on information health and individuals,need to
which is shown in "a", and more towards getting individuals,
persuading individuals
about health behaviors. But also focusing on providing
information to policymakers so that they can make
the right decisions about healthy communities
and healthy policies. So in effect, what we've seen
in the last ten years in surveillance communication
is a move from simply providing information to inform
to attempting to persuade policymakers to put the right
programs and policies in place, evidence-based programs,
that are driven by health information.
The CDC calls this
or providing information information for action,
to make informed decisions, tnot just for information
purposes but, in fact,
the best decision about population health.
Here's a logic model that we've* developed to help us think about
county health rankings, for example.
So, you have population-based data, lots of it.
You do the rankings.
and local health officers We use the report.tion
The community would become
they would promote engaged in the discussion,
health programs and policies, and population health
would improve down the road.
How have we done in engaging *We can ask four questions.
and the community? the media, health officers
doing monthly teleconferences, We help engage the media by
from the communities it gets us feedback
We also focus on key messages, and it keeps them in the loop.
of the ranking, and nbut the importanceails
of broad determinants,
and that there are things that can be done to affect
community health. We've done an annual survey.
Every year, we send out the rankings, we do a survey
of the health officers, about how they have used the ranking
and we use that the next year.
needs assessments in their program evaluation.
They've presented it
and community partners, tand have used it as a way to
catalyze coalition development, healthy community development.
These are the headlines for the papers
that have covered the rankings. This is just a picture
of the "Waukesha Freeman," the
This is just this year, Winnebago County, northwestern,
up in the Fox River Valley, ranks 8th
out of 72 counties. Here's La Crosse quoting
the local health officer, "We're
but we have tons of work to do." headed in the right direction,
county uses it to promote action So even a relatively healthy
which those of you know, in binge drinking and smoking,
issue in La Crosse. WisOzaukee County talks aboutlar
ranking at the top of the list. Then Buffalo County,
a small rural county, even gets covered about, again
heading in the right direction, but have more work to do.
Here's the Baraboo coverage.
in county board meetings *We found it also being used
talking about how are we and minutes of meetings,
our county health department. goAnd here's a quoter
from one of them talking about
their public health work plan. how they plan to use this in
gets a lot of attention because of ranking at the bottom
of the rankings.
article, "Milwaukee at the Here's the "Journal-Sentinel"
rankings." bottom of state health
Juneau County, the year being the state's unhealthiest.
And I'll see if this might not
Nope, not going to work. work since I couldn't--
which is, we do engage some I breaction from communities.o,*
Here's a letter to me and Dr. Kindig
about five major disagreements. This was a physician
from Juneau County. Here's the five-page letter
that we received. And, "If your organization were
actually serious about improving
Wisconsin, not just providing employment for the public health
researchers, it would begin collaborating with, (i.e.
helping not pontificating to) the primary care providers
of the state. I would appreciate a response.
I intend to send this letter
including those listed on your to various news entities,
notifying them of the inaccuracy web site on or about April 1,
Copied to everybody in the world: Medical Society,
senators, presidents. Well, that did result
in a meeting where I was called to Juneau County.
We met in the courthouse. It wasn't packed, but there were
a lot of people there.
that was the biggest In fact, I heard last week
in Juneau County, puband the most diversever
in the Juneau county courthouse.
But then I got called up Senator Zade was there.
meet with Senator Dale Schultz to the capitol building to
Anyway, lots of things and Sheryl Albers.
The health officer was quoted as saying she was actually
"...pleased that this proposal
since I feel it was media is that did the public healthia
and big favor and was a key ingredient to making
the people notice." *So conclusion, what we know
is that plenty of data exists.
and our anecdotal information You suggests that communityntion
engagement will follow. So I think we've shown
pretty well, media engagement and local health authors
pay attention.
the community gets engaged? And that's really our next step.
How do you replicate
in effect? what happened in Juneau County,
lots of community engagement, people bringing resources
to the table. And then answering the question,
does community engagement lead to evidence-based
public health programs? Well, I was surprised
and pleased when the
put out an RFP in June Robert Wood Johnson Foundation
Public Health Practice of last year called, "Advancing
And their goals, the strategic and Policy Solutions."
for effective public health areapractice and policy,ence
improve performance of local
and increase advocacy for public health policies.
And they said to do that
regulations and policy, thrpublic health advocacys,
or communications in engaging hard to reach
and/or high risk populations
communities. like small, rural underserved
rankings was perfectly suited *Sfor this call for proposals.
So we put in a proposal with a goal of using the project
to engage communities in community health improvement.
Hypothesizing that
communication intervention our proactive, low-cost health
involvement in community could simulate and broaden
The objectives, I'm going to just skip over.
*We use media advocacy.
since we haven't started. We actually got funded.
We heard December 1,
It's a two-year $200,000 grant. tWe're going to use.
media advocacy training,
and engage community leaders purchase local radio time
Using a quasi-experimental in the results.
We're going to pick the 20 least healthy counties,
ranking 50th or lower.
in ten pairs And then we'll divide them
to be the intervention and and randomly pick one
We'll do surveys of stakeholders one to be the control community.
a snowball referral process. in the communities using sort of
the baseline assessment we'll pick ten communities
to intervene into,
and action in those intervention communities.
*So whereas the rankings simply provide information
or press release, we get
and community engagement a little bit of media coverage
With our grant, we want to intensify the trainings,
promote active engagement of the media and community,
try and get people involved in evidence-based
program planning, and hopefully drive the health outcomes
down the road.
demonstrated that rankings *So in summary, we pretty much
have anecdotal evidence dof community engagement.,
And our feeling is that the use of broad measure
in the health rankings
consistent with the IOM model. engages broader partners
replicate this community The challenge for us is to
in other communities, and to have the discussion move
from, "We've got a problem."
But we think this is potentially to "What do you do about it?"
catalyze community improvement. a feasiAnd I'll finishthod to
with my acknowledgement slide.
Jessica Athens, Dave Kindig, Bridget Booske, Angie Kempf,
students past and anfuture. te