NWX-HHS-AOA-1 

Moderator: Lauren Solkowski

10-8-14/1:00 pm CT

Confirmation # 8826144

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NWX-HHS-AOA-1

Moderator: Lauren Solkowski

October 8, 2014

1:00 pm CT

Coordinator: Welcome and thank you for standing by. All participants are in a listen-only 

mode. During the question and answer session please press Star 1 and record 

your name as prompted.

Today’s conference is being recorded. If you have any objections, you may 

disconnect at this time.

I would now like to turn today’s meeting over to Lauren Solkowski. Thank 

you. You may begin.

Lauren Solkowski: Great thank you, (Carolyn). Good afternoon and thank you for joining us 

today for the Administration for Community Living Targeted Technical 

Assistance Webinar entitled Data Driven Decision Making Nutrition’s Role in 

the Changing Healthcare Environment.

As the operator mentioned I am Lauren Solkowski with ACL and I will be 

facilitating our Webinar.
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Moderator: Lauren Solkowski

10-8-14/1:00 pm CT

Confirmation # 8826144

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So before we begin our - the presentation, I have a few housekeeping 

announcements. If you have not done so, please use the link included in your 

calendar appointment to get onto WebEx so that you cannot only follow along 

with the slides as we go through them, but also ask your questions when you 

have them through the Chat function.

If you don’t have access to the link that we emailed you can also access the 

Webinar via www.webx.com then click on the Attend a Meeting button that’s

at the top of the page and then enter the meeting number.

The meeting number for today’s Webinar is 294779244. So that meeting 

number again is 294779244. If you have any problems getting onto WebEx 

please call the WebEx technical support at 1-866-569-3239 that’s 1-866-569-

3239.

As the operator mentioned all of our participants are in listen-only mode.

However we welcome your questions throughout the courses of the Webinar.

There are two ways that you can ask your questions. The first through the 

Web using the chat function in WebEx that’s located at the right-hand side of 

the screen.

You can enter your questions here. We’ll sort through them and answer them 

as best we can when we take breaks for questions after our speakers present.

And then in addition to asking questions via the chat we will offer you a 

chance to ask through the audio line. So when that time comes the operator 

will give you instructions as to how to queue up to ask your question.
NWX-HHS-AOA-1 

Moderator: Lauren Solkowski

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If there are any questions that we don’t get to during the course of the 

Webinar we will follow-up to be sure that we get them answered.

If you think of any questions after the Webinar you are welcome to email 

them to me. My email address I have listed here in the chat function on the 

right-hand side Lauren.Solkowski@acl.hhs.gov.

And then finally we are recording this Webinar as we mentioned. We will post 

the recording, the slides and the transcript of the Webinar on the ACL Web 

site as well as the (In Forays) MLTSS Network Web site. Both of these links 

are also added in the chat box for your reference.

So with that I would like to introduce Linda Netterville. Linda is the Vice 

President of Grants Management for the Meals on Wheels Association of 

America as well as the Director of the National Resource Center on Nutrition 

and Aging.

So Linda I’ll turn it over to you.

Linda Netterville: Okay, thank you Lauren. Just a reminder, this is brought to you by the 

National Resource Center on Nutrition and Aging and our Web site for 

Nutrition Resources is nutritionandaging.org.

So if you want to look at any kind of follow-up studies, data -- anything else 

that we may have already posted it will be@nutritionandaging.org.

So I’d like to introduce the speakers for today and next slide Lauren. We have 

Sherry Simon who is Vice President of Nutrition and Health Programs at 

Meals on Wheels of Tarrant County in Fort Worth, Texas.
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And Sherry has been a dietitian a registered licensed dietitian for over 27 

years and has been with the Tarrant County Meals on Wheels Program since 

2005.

And in her position she has been instrumental in developing many programs 

that enhance nutrition services available such as meal choice and breakfast 

meal delivery.

And with her talking about their program is Alan Stevens, Professor at Texas 

A&M Health Science Center and Centennial Chair in Gerontology Scott 

White Baylor Health Care at Temple, Texas.

And then lastly we have Kali Thomas, Dr. Kali Thomas, Assistant Professor 

Center for Gerontology and Healthcare Research from Brown University and 

also research health science specialist from the Providence VA Medical 

Center.

So next slide, so one of the challenges that all home and community based 

services have is collecting supported outcome data both client, programmatic 

or system type data.

And this data is needed for making effective and appropriate decisions in the 

planning management and administering of a program, developing of new 

programs, developing program enhancements, meeting funder requirements, 

developing grant funded projects and justifying budgets.

Today we’re going to hear from one Meals on Wheels program their data 

collection methods and findings that support positive nutrition service 

outcomes both client and programmatic.
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Moderator: Lauren Solkowski

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And then lastly we’re going to look at more systemic outcomes through 

research analysis conducted by Dr. Kali Thomas.

So I’m going to turn it over now to Sherry Simon so next slide Sherry.

Sherry Simon: All right well welcome everyone and I’m very honored to be here to speak to 

everyone about what we’re doing here in Tarrant County.

I have been a dietitian here at this program for almost ten years now and have 

been able to grow our program from just meals to other kinds of nutrition 

resources or services as Linda mentioned.

Lauren next slide, please. So the things we’re going to talk about today are 

basically from its perspective of one nutrition program here in - here at Meals 

on Wheels in Tarrant County or Fort Worth, Texas.

We’re going to talk about how we collect data, what - we’re going to talk 

about what data is collected how we collect data, how our analysis is 

supported and what - how we’re using those results.

And I’m going to probably take you a little through step by step and just give 

you ideas about how what we’re doing with the data and why we’re collecting 

that data.

Next slide, please. Okay. So what’s happening here at in Tarrant County is 

that we have all different types of programs here.

We do everything from feed homebound residents to feeding pets to getting 

reading materials to our clients. So we have all kinds of things happening 

here.
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Moderator: Lauren Solkowski

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And to do all of those different kinds of things you have to have a means of 

managing that. And we use a access database that has been written 

specifically for us. And that allows us to grow and do different things very 

easily.

We have a programmer that works with us. And so every time we had a 

program, take away a program we can change the system very easily for us.

These are just some ideas of some of the data that we collect. We of course 

have our meals and our meals program and so we do choice meals as Linda 

mentioned.

So we have to have a means of discerning who is going to get what meal? Are 

they going to get - is Mrs. Jones going to get in a meal and Mr. Smith get a B 

meal? So we have to have a way of keeping that all straight.

We also ask homeland security questions. Meals on Wheels Association of 

America had a grant from Homeland Security to ask specific questions for 

homebound clients because what they learned in Katrina is that no one knew 

who the most isolated seniors were.

So we’ve included all those questions for every one of our clients. And that is 

in their database. Any kind of referrals there we receive or make that is put 

into our database.

Of course we need it for accounting. Who’s funding what meal for what 

client? All those decisions and all of those, you know, counting the beans is 

done within our database as well.
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We do health, medical and medication evaluation or collection of data. So we 

are collecting diagnosis. We’re collecting actual medication and dosage.

We’re collecting if a hospital is in ED utilizations, whether they can if they’re

hard of hearing, whether they can need a walker. All those items are collected 

and placed into our database.

Obviously being that we are part - we receive moneys from the state because 

of the federally funded older Americans Act dollars we are required to do 

certain assessments.

Most of those are based on the activities of daily living. We measure those as 

well as using some other evidence based tools such as the NIH NHIS

utilization questions as well as nutrition risk.

We used the determine. We’re also doing the mini nutritional assessments. So 

all those kinds of healthy days which we’re asking how many healthy days 

clients may have within a 30 day period, all of those things, all of those 

questions are gathered those - that data is gathered input into our database.

We also need to collect data for grant funded projects. We have a substantial 

grant from the United Way of Tarrant County which provides for those 

programs you see there -- diabetes, home meds, PAM.

And then the vision grant was something that was funded by the Meals on 

Wheels Association of America. And that’s what Dr. Stevens is going to 

really focus on.

But our diabetes program, we’re sending dietitians in the home and we’re 

actually providing doing nutrition assessments and providing nutrition 

education.
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Moderator: Lauren Solkowski

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So all of that information data is collected and kept in our database. The 

homeless program is an evidence based program that the ACL has approved.

And we are actually looking at medication issues for duplication of 

medication, medications causing dizziness or falls and we’re trying to 

alleviate those alerts or problems and so that we can bring down the 

hospitalizations.

So that - all of that information is also captured in our database. And then 

PAM stands for Patient Activation Measure. So these are for - this is a 

program for our clients that are least likely to be engaged in their health.

And we actually have community health navigators that are helping them get 

more engaged and be proactive in taking control of their health, making their 

doctors’ appointments, understanding their medications -- that kind of thing.

We also are now have embarked on with our dietitians and what we do in the 

home a nutrition diagnosis. And this is something that a lot of hospitals are 

utilizing is from the Academy of Nutrition and Dietetics that basically it’s a 

way if you’re using nutrition diagnosis you can track basically the severity of 

the nutrition problem. And it can be - and you can track back to dollars saved 

or the potential cost of the nutrition diagnosis.

And then I’ve already spoke about Healthy Days data. But that’s basically a 

evidence based tool that we’re using to try to see pre and post how we affect 

the number of days someone is healthy or reports they’re healthy.

Next slide, please. Okay. So what data is collected?
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Moderator: Lauren Solkowski

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Next slide, so these are the types of data that we could collect. Of course 

demographic and we all know what that is, programmatic kinds of information

specific to different programs like our meals program, the dietitian education 

that has to be provided as mandated by either state or federal requirements, the 

home meds. We’ve already talked about PAM or Patient Activation Manager.

We also have another program where we have which is Sage which we have 

physician medical students going into the home and working with our clients.

So these we can all do start and end dates and we can gather quite a bit of 

information of how these programs are working for our clients and how it 

moves us through the operation of making sure that we are getting the items to 

our clients so it’s operational as well as programmatic.

Meal details, this is just simply what diet or choice meal is a client going to 

get? We also can - we also have information about food allergies.

It also can detail the funding source who’s paying for that particular meal for 

that particular client.

Meal history, this is an area where we can actually know exactly how many 

meals a client got for a specific month or a specific year and how they were 

funded. So this is really important to our funders.

Medical screen, so we’ve pretty much within the - our database using access 

have created pretty much an electronic medical record. And so we capture 

everything from diagnosis medical needs, hospitalizations, insurance type 

what hospital they just came out of -- all those that information is collected.
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Moderator: Lauren Solkowski

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And I’ve already talked about medication so we just not only cover actual 

prescription medications but we also ask for supplements as well as any herbal 

items that they may be taking.

Next slide, please. We also capture height, weight other agency involvement 

on our health screen. We do all kinds of documentation in free form writing.

So if they call in with a question or a client calls in with a question or a case 

manager goes out to see a client all of that is document within our database.

So all of the assessments that we need, some of them mandated, some of them 

we put into place ourselves. And you can see we have the 2060 which is an 

ADL or activities of daily living kind of screen, nutrition screen, malnutrition 

screen. We do a diabetes screen to see the risk of someone developing 

diabetes.

Emergent care screen which is a measure to see the likelihood of someone I 

guess the severity of their condition and the likelihood someone may report to 

a hospital because of the severity of their condition.

Healthy days we’ve already talked about. And the EQ5B is basically a quality

of life measure that we also continue to do.

Dietitian notes. We have an actual screen. We’ve developed that electronic 

medical record. We can take pieces of data and input and the - it populates

into the note.

So our dietitians aren’t having to retype BMI if it’s already figured in our 

database or a certain diet is already in there or the diagnosis. They don’t have 

to retype that. It self-populates into the note.
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Outcome questions, so part of being involved with funders is they want to see 

pre and post results. And so we have to ask those outcome questions. And all 

that is captured in our database as well as client contributions so that we know 

who is able to make a contribution to us or who is making that contribution on 

behalf of the client.

Next slide, please. Okay. So this is just quickly a sample of what our database 

can do with regards to a dietitian note. And you can see that it is just like 

something that you might see in a hospital setting.

Next slide, please. Okay. So these are actually the questions that we asked for 

healthy days. And basically it’s, you know, do - would you say your health -

how your health is, your general health, how many days were you thinking,

your physical health which includes physical illness or injury, how many days 

in the past 30 days was your health not good. And so these are our some of 

our we ask is pre or post any kind of intervention.

Next slide, and so how is our data collected? So basically we have what 

makes us unique here in Tarrant County is that we have about 14 case 

managers that are territorial within the county.

And they go out and see the clients and they collect a lot of this data. And they 

have laptops. We have gone away from netbooks and now they have laptops 

with air cards. It allows them to go right into our database to put in this 

information.

They also at the same time we also have people in the office staff that’s also 

working on the same database and updating it as we’ve got a client calling in,

missed a meal, we’re trying to find a client -- those kinds of things.
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Moderator: Lauren Solkowski

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We’ve already talked about that we’ve built in this database in the electronic 

medical record so we can track diagnosis, waste, we can track their 

medication, changes in their medication -- that kind of thing.

Any data that we input into this database we can basically build a report. So if 

we wanted to know how many meals were delivered in a certain ZIP Code in 

a certain period of time we could do that.

And so any field, any data field can then be created into a report. So some of 

the examples I just mentioned here is when we’ve had severe weather here in 

Fort Worth and we had a couple years ago an ice storm that closed down the 

city for about five days Fort Worth Emergency Management contacted us and 

wanted to know who were the most isolated, who did the fire department need 

to go check on within those five days. And so we were able because of our 

data collection we were able to give them the kind of report.

We can also meet an ambulance on the way to a client’s house with 

medication lists and diagnosis so that they have that available to take to the 

hospital whether transporting someone to the emergency room.

Next slide, please. So this is just an example of some of the reports that we 

can do that have already been built. But there’s many times that we have to 

create a report just because of the need of someone calling us or some piece of 

information we want to now search for.

Next slide, and then this is a slide of evaluation team specific reports. Dr. 

Stevens who’s going to speak to you next is one of my evaluators for some 

United Way funded grants as well as we’re working on some of the research 

together.
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So he has access to our data and so these are some reports that were built 

specifically for the evaluation team.

Next slide. And how is that analysis supported?

Next slide, please. So internally we have office staff that’s dedicated to all 

different types of input into the database depending on their job.

We have an IT manager here within our facility. We also have a technology 

committee that’s made up of volunteers outside of our agency as well as 

people who work here in the agency and as well as some board members.

And then just know that every call, every action, everything that we do here is 

documented in to the database.

Next slide, the external report we have is that we have a database programmer 

who works one on one with us depending on the situation or what we need 

done.

We have an evaluation team so different funders require different types of 

evaluation. And I’m all for evaluation. You want to prove your worth.

We are hosts. We have the server is hosted so we have support that way. We 

have interface with other organizations that provide external support for us as 

well as the - we have needs of funders that are also pushing us to just like our 

external customers.

Next slide, and how are the results used? So basically as we’ve talked 

anything we’re doing that’s an intervention were doing pre and post data or 

annual data.
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We need to report to our funders especially on those United Way types of 

projects. We have to report to stakeholders. So at AAA will require us to have 

certain statistics and data that we need to report to them. So having this 

database is very, very important.

Of course the data adds validity to what you’re doing. We can also benchmark 

ourselves now against other agencies or other Meals on Wheels programs or 

compare ourselves to different types of health programs and see how we are 

doing especially when we’re using those evidence based tools like the Healthy 

Days.

We can reproduce the data. We can share among like agencies. So with our 

United Way funding we all have the same tools that we’re using pre and post 

so we can benchmark ourselves against those other funded agencies of United 

Way.

And then the more you use these tools the stronger our message is. And then 

of course data equals results. And I guess that’s why I’m here talking to today 

because we do collect so much data that we’re able to show results.

And it’s and if I can say anything to you programs out there it’s, you know, 

start small, start collecting your data in small doses. And as you continue to do 

that process you can just grow and continue to layer it and become more 

sophisticated with your gathering and input of data.

Next slide, okay that’s all I’ve got so Alan is next and I want to thank Linda 

for my little crown there.

Lauren Solkowski: Okay. Dr. Stevens you’re welcome to start.
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Moderator: Lauren Solkowski

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Dr. Alan Stevens: Hi. Thank you. And I have had the pleasure of working with Sherry and her 

staff at the Tarrant County Meals on Wheels Incorporated for I guess about 

three to three years now or slightly more. And we have we worked together on 

a number of different evaluation efforts to look at the data that they’re

collecting.

As Sherry just described it’s a very rich and robust data source that they 

developed and have primarily used to implement their services and to expand 

their services from meal delivery to other nutrition based interventions.

And given the level of complexity and the level of programs complexity in the 

number of programs that they provide and sheer quantity of the number of 

clients they serve that database has served them very well in terms of really 

reaching and touching homebound folks in Tarrant County.

So we were, you know, delighted not only to see what a wonderful service this

was to the community but also to realize that perhaps we could work with 

them to find ways to analyze their data and produce reports both for internally 

to their organization plus also as our role as an external evaluator to the 

Tarrant County United Way.

So we work together on a number of different initiatives. Some of them as I 

said are externally initiated. But to their credit many of them are internally 

initiated which I think is also a very telling of the organization that Sherry 

runs there in that they want to know not just to serve others but they are to 

please others that they want to know for themselves how they’re doing. And 

that’s I think that’s a great attribute of how their organization is set up.
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Today I just want to talk about one of the programs that we have worked with 

them on. And that is the Expanding the Vision grant which was provided by 

the national Meals on Wheels Association to Tarrant County.

And on Slide 2 please there’s basic information there about the grant and the

period and the funding source. It was basically through March 2013 through 

March of 2014.

Now I’m going to ask actually if we can now skip to my Slide Number 7. 

Great.

Lauren Solkowski: Is this it?

Dr. Alan Stevens: Thank you. That’s - Sherry has already given you a lot of background about 

organization so I’m going to skip forward to say specifically about this Vision 

grant.

It was a collaboration with key individuals in the area in Tarrant County 

including the Area Agency on Aging, the United Way of Tarrant County 

which is also the funder of another larger initiative called the Healthy Aging 

and Independent Living Initiative.

And we have one hospital system listed here. They actually worked with 

multiple hospitals throughout the county to identify their target audience.

Next slide, really key to the success of this project was Sherry and her staff 

early in the design phase of when they were writing their application is that 

they wrote the application in a way that set both output and outcome goals.
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And so and output they were referring to the shear process of delivering 

nutritional services. So here they set a goal of providing 1800 meals to a 

minimum of 120 recently discharged patients.

And so some key information here, not only is the number that there’s serving 

a certain number of meals but they identified the number of actual clients that 

they wanted to serve.

And this was based upon their rich history of knowing approximately how 

many meals they would be serving, approximately what was the need that 

somebody would experience.

And importantly because their organization and some larger initiatives within 

the county were interested in reducing 30 day preventable readmissions to the 

hospital they targeted individuals who were recently discharged from a 

hospital or had had an emergency department visit but not hospital 

hospitalized.

So targeting here is the message that I think you should take from this is that 

there will always be probably a larger need than any organization can provide.

But what Sherry has shown here is the ability to identify a target population 

that is of high need and then develop a strategy to beat those I need 

individuals.

Next slide. The second part of their grant development was the setting a 

specific outcome goals.
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So not only did they want to deliver 1800 meals to 120 people who were high 

need because of their recent healthcare utilization they wanted to track the 

impact of the meals on some health indicators for that group of individuals.

So they set goals in both what we would call health outcome utilization which 

would be how many people would be readmitted to the hospital during the 

time that they were during the next six months.

And what would - how would the clients look based upon the evaluation of 

their basically comorbid conditions or their chronic diseases that they were 

managing based on the emergent care assessment score at the end of the meals 

program?

They also were interested in making sure that their services of the 

organization were coordinated in ways that made sense given the target 

population.

So again the target population is not only those who are homebound and need 

meals but have recently had a hospitalization or an emergency room 

encounter.

They have another program called Home Meds which helps people they - in 

which someone works with the client to review their medications, they’re 

analyzed including on a evidence based software platform and then alerts or 

what would be thought as threats that to the person’s health based upon the 

medications that they were taking were then addressed by a pharmacist or a 

pharmacist technician as any kind of medical alert would be addressed within 

30 days meaning addressed meaning feedback given to the individual of what 

the alert was and then some assistance in working through how to remediate 
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that alert or to basically remove that contraindication of their medications as 

they were taking them.

So that I start with as all that was done before the grant was even submitted 

and I think that’s really an important part of this story of Meals on Wheels of 

Tarrant County is thinking through what did they want to achieve when they 

rolled out a new program?

Next slide, so this is what they did achieve. They met their goals of providing 

the number of meals that were expected within their funding period. And they 

met their goals for the number of people they actually served.

So again their use of their data, their historical data I think led to their ability 

to estimate goals and output goals here that were not only fundable that they 

received a grant but they were actually feasible because they achieve them.

Next slide, the degree of specificity in their data collection allowed us to then 

take the clients that they served and the data on the meals and break it out into 

what kind of meals were provided.

So this bar graph shows that the total number of meals and then the types of 

meals that were provided, noon meals as you might expect making up the 

majority, a number of breakfast meals as well.

Sherry mention the fact that at times there are situations in which it is difficult 

to reach someone’s home because of ice storms or other kinds of natural 

situations that prevent people from delivering a hot meal.
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There are these other alternatives which can be available from frozen meals to 

shelf stable meals that were also included but as the majority - or noon meals 

and breakfast meals are included in their 1800.

Next slide, the average number of meals was 131 per the 120 clients that were 

served. And importantly the length of the program is hundred - the average 

length of time that someone was receiving meals was 132 days.

That’s a really key data point that we’ll come back to and talk about at the end 

in terms of where are we going next with the use of their data and what are 

some interesting data points that we want to look at.

So remember that, that 132 days is the average length that people are on 

meals. And if for most of you this is not your first Webinar and you’ve heard 

a lot of people talk about health interventions and talk of about six month 

outcomes.

Well look at this number again. We’re less than six months of service 

delivery. But most of the time we hold people accountable for their six month 

follow-up assessment.

So they’re not even providing meals the entire time. There’s some lag here 

between the meals when the meals end and when six month data collection is 

occurring.

Next slide.

Lauren Solkowski: Just one quick question. This is Lauren. So you had referenced that the 

goal was 18,000 meals but your when you’re speaking you’re saying 1800.
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Dr. Alan Stevens: Oh I’m sorry. I’m sorry, 18,000.

Lauren Solkowski: Okay, just wanted to just to clarify. Thank you though.

Dr. Alan Stevens: Thank you. Sorry Sherry. So demographic characteristics of the population,

you’re as you would expect there or an older population average age of 71 but 

a wide span here of age youngest patient being 42, 60% female, white 75%, 

Hispanic 6% and black African American 19%.

These numbers of race and ethnicity are generally reflective of the patient of 

the entire population of Tarrant County.

Next slide, as you recall that we were having the - one of the real assets of this 

program was targeting individuals who had recent health care encounters.

So here we show you the number of clients who were served. And 105 of 

them had at least one hospitalization and 20 of them had had an ER visit at the 

intake of the program. That means the - at the beginning of being signed up 

for the meals program.

Next slide, so they’re reaching their target population is the point of that slide. 

Sherry and her colleagues set a goal of say of the - based upon hospital 

readmissions.

And this goal was based on the sum of their data that they had from other 

projects and from their meals programs that they had been collecting for a 

number of years.

Some of it was based upon data that they had gotten with working with other 

community organizations that look at health care utilization data.
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So they set a target of 50% of the clients which were 60 serve would not have 

another hospitalization during their project period. So for six months from the 

point of meal service to six months later that 50% wide not have a 

hospitalization during that period of time.

As you can see on this slide they more than achieved this goal with only 24% 

or 22 of the total number of people served had a hospitalization within three 

months and 19% had a hospitalization at six months.

So again this is a significant finding in that they set a goal and they achieve 

that goal. We’re working now with some other data, other individuals looking 

at data collection that are collecting overall health care utilization data.

And we are now going to be able to go back and look at this data from actual 

hospital claims data. This is self-report data.

Self-report data has been proven to be very reliable. But we also now are 

working to go back and confirm it against actual hospital claims data.

Next slide, again a return to an ER or use of an ER was also a target. And 

again they weigh more than achieved their outcome there. Their target goal of 

50% or more would not experience these events.

As you can see almost both three months and six about 10% of those that we 

collected data on at those two time points had experienced an ER visit so very 

- a very low number, lower than you would expect for a homebound 

population, multiple chronic diseases and individuals who had been 

previously hospitalized or had an ER visit prior to receiving meals.
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Next slide, they also the emergent care assessment is an evidence-based tool 

that again summarizes the number of chronic illnesses that an individual have 

has and the number of risk factors that they have that might lead to a 

hospitalization.

So their goal here are the hypothesis was the providing meals and home med 

services to an individual would help them improve their overall management,

the management of their overall health and would lead to an improvement on 

emergent care assessments at six months. And that indeed was achieved as 

well.

Next slide, as I said earlier some not all of the patients also - patients, the 

clients also received a home med’s intervention. And so this is the 

intervention which all of the person all of the client’s medications were 

entered into an evidence-based platform.

Alerts were generated and then any alerts were consulted with a pharmacist or 

pharmacist tech and then reconciled with the patient.

Ninety-three of the clients enrolled in the home med program. So that’s, you 

know, a big majority of those who are in the meals program also got home 

meds.

51% or 55% of them had a medication alert and the mean was 2. So that’s

50% of the people we worked with who were getting meals because Sherry’s 

ability to integrate programs. Also these folks we were able to identify 

medication alerts that we thought needed to be investigated.

Now the severity of those alerts do vary. Some of them are minor, others are 

very significant. But I think the point here is that when we’re servicing a 
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client, a homebound person who has a need for meals these data suggest that 

that same patient population also can benefit from having the additional 

services of the home meds program.

Next slide, so here just to summarize very quickly they - the program in 

particular this unique program of Meals on Wheels - excuse me my slide - my

screen just went blank okay, were successful in the way they developed their 

project to target a population, to target outcomes, to target outputs and they 

achieved all of - all three of those aims.

And as this slide shows I think really of importance to this project is that they 

targeted a high risk group, people who had recently been admitted to a 

hospital or had an ED experience.

And I think we are learning a lot from working with organizations that are 

able to target individuals who not only have a need but have a need at a high 

risk point or a high risk transition in their overall health course.

Next slide, and again just to summarize I think the meals program plus the 

home meds program adds value in terms of the amount of resources that the 

organization is dedicating to the individuals they serve.

Adding some of these programs together combining programs where it makes 

sense does seem to leverage that investment into some meaningful health 

outcomes.

Next slide, we are we’ve used the, as I said what we basically are presenting 

today are the utilization data and the self-report data that were collected by 

Sherry and her staff at Meals on Wheels.
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We’re now building and have actually built already a collaboration with 

something called the DFW Hospital Council Foundation which is a repository 

for health care utilization data in the Dallas-Fort Worth area.

And our partnership with them will give us access to the actual utilization data 

or the claims data filed from hospitals. It will be impatient data but includes 

ER data from the hospitals in their county.

The DFW Hospital Council Foundation is remarkable in that they capture 

approximately 95% of all health care utilization in the Metroplex or DFW 

area. So it’s a very, very rich powerful repository of data.

Most communities don’t have such a thing but it’s a unique aspect of the 

Dallas-Fort Worth area that we’re leveraging in our partnership.

The partnership to investigate this will be us, the Hospital Council Foundation 

and Meals on Wheels. The question always here is how do you get around 

patient privacy or client privacy issues?

And we’re able to work that out by using de-identified data by creating 

personal identifiers. So basically think of Meals on Wheels who is the owner 

of the data and who’s - have clients that they’re responsible for.

They control access to all personal identifiers but as playing kind of the 

middleman between us and the hospital foundation we’re able to get claims 

data, match it to the meals data that Meals on Wheels has and never 

jeopardize a person’s personal information or personal identifiers.

And we’re using a health economist to help us in with this data too because 

we can take data like that Healthy Days, the CDC’s Healthy Days and it can 
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be converted into a metric that will allow health economists to do return on 

investment or savings from the actual intervention.

Next slide, and I think that’s all for me so I think we have maybe a minute for 

a few questions?

Lauren Solkowski: Yes. And thank you so much Dr. Stevens for your presentation and to 

Sherry.

Before we go to the next presentation we wanted to do Q&A. So operator if 

you could please provide instructions for asking a question via the audio line 

that would be great.

Coordinator: Thank you. We will now begin the question and answer session. If you would 

like to ask a question please press Star 1, make sure your phone is unmuted 

and you must record your first and last name slowly and clearly to introduce 

your question.

To withdraw that request you may press Star 2. Once again for a question or a 

comment please press Star 1 and record your name, one moment while we 

stand by for questions or comments.

Lauren Solkowski: Great thank you. And so while we wait for some questions to come in we 

do - we did have a question comment to chat. And Sherry I think this would 

be directed towards you.

So the question is can you run a report for all meals delivered in a period of 

time to all people with a specific disease or meals for people over a certain 

age or income?
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Sherry Simon: Absolutely. If it’s a data field then we can do it. So we collect diagnosis 

information. So if we wanted to just know how many clients have congestive 

heart failure I can do that, that we serve.

If I wanted to know how many clients have diabetes and also get our no 

concentrated sweets diet that we offer I can do that. So wherever we collect 

data we can generate a report.

Lauren Solkowski: Excellent, thank you. Okay I’m just running through the list here. I don’t 

see any more questions via chat. Are there questions that have come in via the 

phone?

Coordinator: Yes we do have a question from the phones. Our first question comes from 

(Mary Kayshack). Your line is open.

(Mary Kayshack): Hi. My question I guess has to do with the outcomes they were really, really 

impressive and it was great to see outcomes and outputs presented.

I was just wondering if any of the clients that were involved were also 

involved in any other interventions for, you know, care transitions or hospital 

re-admissions?

And if you guys looked at all if there was any difference between the clients 

that received the meals and the home meds or perhaps or the combination or 

one of the interventions individually to see if there was any difference in like 

the combined approach working best to reduce hospital readmissions?

And then one last question is what you kind of already went through but just if 

you even if not on the Webinar but could share examples of some of the other 

pre and post data that you collect to help maybe inform others on examples of 
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data that they should be or could be collecting to help get at some of this think 

that would be really helpful?

Dr. Alan Stevens: Okay. Sherry you want me to take a start and you can follow up?

Sherry Simon: Sure.

Dr. Alan Stevens: Your first question is a good one and one that Sherry and I debated at the very 

beginning of this project.

The short answer to your question is no we haven’t done that kind of deep 

dive into the data to split people up and look at total dose of support they’re 

getting from Meals on Wheels. We just selected these two for now because 

this was our initial interest based upon the project aims.

The deeper part of this question is that to answer your question the most 

cleanly from a scientific standpoint yes we should have said let’s - this group 

of people make sure that we control their dose of support and we’re only 

going to allow them to roll in this project or this project.

That’s how we would do it in a more in a randomized clinical trial.

Sherry and I decided differently. We decided to say, you know, this is a 

community driven proposed project and let’s just go with it. Let’s just serve 

people as you normally would Sherry is what I - is what we ended up saying 

and let us figure it out in the end.

So that deeper dive of figuring out the dose that people get is an important 

one. We just haven’t gotten to, completely to it yet.
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I suspect that well I can guarantee what we have done is made sure that we 

have included the individual most likely to overlap with meals and that is 

home meds.

We’ll have to do a deeper dive to look at the other programs especially a 

nutrition counseling program.

And your second question is I think, you know, that the outcomes that you 

choose should be really carefully thought about in terms of what’s meaningful 

to your organization, to your community, to your stakeholders in general.

What we have found to be important to the stakeholders in Tarrant County is a 

- some measure of quality of life. We’ve used different ones EQ5D and now 

we’re using CDC healthy days.

Some measure of health com utilization, a self-report of health com 

utilization. And we’re using the measures as Sherry said that really allow us to 

track number of hospitalizations, number of days and number of ER visits in 

the past six months.

And then generally I always say to an organization pick an indicator that 

really you used to know that you’re doing a good job.

You know, so I think it’s important to not always be driven by what other 

people tell you but have some introspection to say I’ll know we’re serving 

people right when.

And whatever that when is let’s whatever that is let’s objectify it and come up 

with a measure for it.
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So in another one of Sherry’s programs it’s goal attainment that they are 

working, they know they’ve done a good job when X percent of their clients 

report that they have achieved their health goal. That’s a really important 

indicator for one of their programs.

So again those are the where there. There’s just some of the top thoughts that I 

would have let go for some standard measures. But don’t be totally driven by 

outside sources. Look internally at what’s important to your organization and 

stakeholders and make sure you cover that as well.

Sherry Simon: And if I can just add in I think it’s important to realize that what we’re doing 

here at Meals on Wheels this is not - we’re not - our purpose is not research.

Our purpose is to serve the clients the best way we can to make sure that 

they’re able to stay in their home as long as possible.

And that is something, you know, when we first talked with Alan that is 

something I kind of, you know, he’s always educating me but I think that’s the 

one point I educated him on that it wasn’t ethical to say this group we’re 

going to give these interventions to and this group we’re not.

We can’t do that in a community setting right. That’s we want to provide the 

best care, service possible to our clients so that we can help them maintain 

their health in their home as long as possible.

And the other point I wanted to make is that Alan and I have had many 

conversations and one of the reasons why we are moving forward with our 

collaboration relationship with the Dallas-Fort Worth Hospital Council 

Foundation is because we want to get to the point where we’re looking at each 

layer of our services and how that impacts hospitalization.
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So this we’re - that’s where we’re moving towards. We’re going to look 

exactly at what does a meal provide, what does the dietitian in-home

intervention provide, what does the home meds provide in regards to hospital 

and ED utilization?

That’s where were moving towards and that’s our goal right Alan?

Dr. Alan Stevens: That’s right.

Lauren Solkowski: Great. Thank you both so much. So I think with that we’ll - we’re going to 

move on to our next presenter. And I know there was a couple more questions 

that came in. We’ll get - come back to those after Dr. Thomas’s presentation 

so we’ll turn it over to her.

Dr. Kali Thomas: All right thank you. I wanted to think ACL and the National Resource Center 

for the invitation to present some work I’ve been doing looking at the role of 

home delivered meals and low care residence in nursing homes.

Next slide, please. So just to give you to see what’s on the menu for the next 

few minutes I’ll describe briefly this population of low care residence that as a 

health services researcher interested in home and community-based services 

and quality of care is a really important population of study and interest of 

mine.

I’ll present some findings from the initial study that was conducted to look at 

the relationship between spending on home delivered meals programs and this 

population of residents in nursing homes.

I’ll then present some information about the financial impact on states that we 

found through increasing home delivered meals and thereby reducing the 
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number of low care residence in nursing homes and provide some suggestions 

on how you can utilize this information and how these national estimates that 

we’re calculating can be used more at a local level and then give you a little 

bit of a teaser about some current work and future directions that we’re 

undertaking.

Great, so since the Olmstead decision in 1999 there has been an increase in 

home and community-based services to serve individuals with disabilities in 

their home and communities where they prefer to be.

And with this increase in the numbers of individuals utilizing HCBS we’ve 

also seen an increase in the acuity of nursing home residents as many of these 

individuals who may not necessarily need that nursing home level of care 

transition to HCBS.

But despite these increases in programs there’s still an alarming proportion of 

nursing home residents in the US that have low care needs.

And this is a population that’s so important to focus on and in fact is included 

as a measure of the quality of this - of states long term care systems. It’s 

included on the AARP and Scan Foundation Quality report card and is a good 

measure of long-term care quality.

Next slide, please. So who are these low care residents? We use the minimum 

data set which is the federal resident assessment information from nursing 

homes.

And we identify these folks as individuals who do not require any assistance 

in the four late loss ADLs. So this is bed mobility, toileting, transferring or 
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eating and also if they do not fall into the lowest functioning rugs categories 

which are clinically complex or if they require special rehab.

And so with these definitions we assume that these individuals have these 

functional and clinical capacity to be cared for in a less restrictive setting like 

their homes.

Next please. So in terms of how big this issue is there has been a decrease in 

the upper portion of nursing home residents that were classified as low care 

over the decade of the 2000s.

However there in 2009 there was still about 13% of nursing home residents 

that were identified as low care.

Next slide, please. So previous research has examined why they’re there. 

We’ve found in previous work that Medicaid long-term care spending is 

related to a smaller proportion of low care residents.

More assisted living - more assisted living facilities were related to fewer low 

care residents, more nursing home competition.

But what was really missing from this literature was an examination of other 

HCBS programs like the Older Americans Act Services to low care residence.

Next please. Next slide, great. So the objective of the first study was to see if 

the we hypothesize that higher per capita state expenditures on older 

Americans Act Title III services would be associated with a lower percentage 

of nursing home residents with low care needs.
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Next slide, please. And we used data from ACL’s aged database which 

includes information from all of the state program reports that are submitted, 

census data, AOA survey data. And specifically we use the older Americans

Act expenditures for the following programs listed here and we adjusted those 

per older adult age 65 and older in the state.

Next slide, please. And we merged those data with a information that we’ve 

compiled here at Brown University LPC focus.org which is a publicly 

available data set and includes information on nursing home characteristics, 

long term care market characteristics as well as the number of state policy 

variables that are related to the long term care system.

Next slide, please. And we found that out of all the programs we looked at 

including Medicaid home and community based services increased spending 

in home delivered meals was the only statistically significantly associate 

program associated with decreases in the proportion of low care residents in 

nursing homes. And that finding was published in Health Services Research in 

2012.

And so to put these results in context we found that for every $25 that states 

spent on their home delivered meals program per year was associated with a 

decrease in the low care nursing home population of 1 percentage point.

So in the paper we provide you the example that a state like Washington that

spent approximately $8.10 per older adult aged 65 and older would have had a 

low care population of around 17%.

But a state like Wyoming which spent the most on this program would’ve had 

a low care population of about 13.8%.
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Next slide, please. So we wanted to do a follow-up analysis that would 

provide sort of a roadmap and guideline for states to understand the 

relationship between not just spending on the programs but the actual program 

capacity and how many older adults were served in the state with home 

delivered meals and the relationship to locate a residence.

And from this from these models we were able to calculate the potential 

savings that states would recognize by increasing their proportions of older 

adults served by these programs.

Next slide, please. And in that paper we found that every 1 percent increase in 

the proportion of older adults served was associated with a .2% decrease in the 

proportion of low care residents.

And our data using Medicare claims and enrollment records we were able to 

identify that the majority of low care residents are duly eligible meaning that 

Medicaid fits the bill for the majority of these folks.

So we were able to then calculate if a state were to increase their capacity for 

providing these services what their potential savings would be by decreasing 

the proportion of low care residents and not therefore paying for their care.

And we found that if states were - that if states were to employee just an 

across the board 1% increase that 26 states would have recognized savings in 

2009 based on these estimates.

And those were primarily states with a high proportion of low care residents, 

high Medicaid per diem and a low population of older adults in the state.
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And the remaining 22 states presented here might not see immediate 

increases. But because our estimates were very conservative we hypothesize 

that in the future it could be possible for them to also recognize savings. And 

these findings are presented in health affairs and you can read more about 

those discussions and limitations.

Next please. So in conclusion from those national studies we found that 

decreases in low care nursing home residents in the US coincide with 

increased HCBS spending over the past decade.

However increased spending on home delivered meals was and the increased 

prevalence of older adults who received these meals are related to decreasing 

proportions of low care residence.

So up and above these temporal trends we’ve seen over time the home 

delivered meals program is related to a decrease in low care nursing home 

residents.

And we would believe this to be true because as I’m sure all of you know on 

the call that home delivered meals services provide more than just food to 

vulnerable older adults.

We as drivers and volunteers are often the safety check. We’re the eyes and 

the ears, we’re in the home, we report changing needs. And these services in 

addition to just food may be key to allowing older adults to remain 

independent and in their homes.

Next slide, please. So with all this information it’s important to me as a 

researcher to make sure that these estimates and these models and these 
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numbers and figures can actually be utilized by providers and practitioners 

and people in the field.

So I hope that these papers and these findings are - can be used in legislative 

testimony. We’ve had people include them in letters to elected officials.

They’ve used these arguments and these findings in grant writings. And I like 

to encourage all of you to visit ltcfocus.org. There you can find local low care 

figures and population characteristics for your area. And you can also go to 

aged for the state program report data.

They have the National Survey of Older Americans Act participants and 

census data so you can calculate the, for example the proportion of individuals 

with an independent living disability and the proportion of those who receive 

home delivered meals in your area.

So there’s all types of ways you can use these data to make the argument and 

the business case that home delivered meals really matter.

Next slide, please. But in addition to just sort of the funding and the cost 

savings we’re also interested in the quality of life differences in the 

improvements and isolation.

So we current - I’m currently involved in a project funded by AARP 

Foundation to Meals on Wheels Association of America.

And we have eight programs across the US. We’ve surveyed 620 older adults 

who were on waiting list for programs.
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We provided hot meals to 200, frozen meals to about 200. And we employed a 

pre and post survey 15 week survey for these individuals and were evaluating 

not only the effectiveness of home delivered meals but also the home 

delivered meals modality so whether hot meals or frozen meals improve 

quality of life, social isolation, healthcare utilization after 15 weeks of service.

So that research is currently underway and we hope to have exciting results 

for everyone soon so next slide, please.

So I would like you all to stay tuned. There is more to come and feel free to 

contact me and follow-up with any questions we might not have time for in 

the little remaining time we have left.

Lauren Solkowski: Great. Thank you so much Dr. Thomas. Okay. So since we do have a few 

more minutes operator if we could open it up again for question and answer if 

you could please provide instructions for asking a question on via the audio 

line.

Coordinator: Thank you. And we’ll have another question and answer session. And if you 

would like to ask a question it’s Star 1. Make sure your phone is unmuted and 

record your name slowly and clearly.

Your name is required to introduce your question. And to withdraw that 

request you may press Star 2. Once again for a question or a comment press 

Star 1 and record your name at this time. One moment while we stand by for 

questions or comments.

Lauren Solkowski: Great, thanks. We do have a question showing in chat but this might have 

been from the previous presentation. It’s asking if you could explain a bit 
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more about the PAM coaching what kinds of training is involved, what tools 

are used, et cetera.

Sherry Simon: Okay. I guess that’s a question for me Sherry. The PAM model is the Patient 

Activation Measure and is a questionnaire developed by the people out of the 

University of Oregon.

There’s many health care facilities and insurance companies that use that and 

it’s basically a measure to see someone’s activation in their healthcare.

And then based on the finding of that questionnaire people, coaches can then 

determine what are the needs of the clients. They can - there’s certain scripts 

so if they have nutritional issues, there’s some coaching done with the 

nutritional issues -- that kind of thing.

The way we do it here at Meals on Wheels is that our case managers are 

basically the gatekeepers and they let us know when someone is very 

overwhelmed with their healthcare. And then we send in a community health 

navigator.

The community health navigator here at Meals on Wheels basically have 

come from our volunteer base. We advertise the position. We trained those 

volunteers on how to be community health navigators. We train them on the 

PAM program. We talk about boundaries so we do our own in-house training.

I have a dietitian who is in charge of this program and is basically the 

supervisor over all the community health navigators.
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We have about 15 community health navigators. We’ve divided them up in by 

territory of Tarrant County. I have one that is Spanish-speaking I also have 

one that is Vietnamese speaking so obviously they take those clients.

And they basically work with the clients in teaching them how to fish instead 

of giving them the fish. So they are teaching them how to make those phone 

calls, how they can access other resources -- those kinds of things and then 

utilize that the PAM model and questionnaire.

And actually we here at Meals on Wheels we are told by the developers of the 

PAM program that we have the best results of any other organization using 

the PAM questionnaire in the world because it’s used in Europe as well.

So we have the best pre-and post-data results. So we’re very excited about 

that.

Lauren Solkowski: Great, thank you, Sherry. And I think we have time for one more question. 

Are there any questions that have come in via the phone?

Coordinator: I’m currently showing no questions or comments at this time.

Lauren Solkowski: Okay. Well since we are at the very end of our session I just wanted to 

thank all of our speakers again for your presentations. And thank you to all of 

our presenters for your questions.

Again if you do think of any additional questions after the Webinar please feel 

free to email them to me at lauren.solkowski@acl.hhs.gov. Again my email 

address is listed here on the chat box. And I can and I’m happy to forward 

those to our presenters.
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And so with that we will conclude our Webinar and thank you for joining us.

Coordinator: That concludes today’s conference call. Thank you for your participation. You 

may disconnect at this time.

END