The Dashwood screening is carried out 
daily by our disease at Westmead.

We can have a range between 200 to 
220 category one into patients.

Per day.

Out of this.

It is expected that we see about 60

to 70 Category 1 and 2 DEA patients.

With the help of onsite 
health she dieticians.

We have now managed to narrow 
down this criteria and are able

to identify patients who will 
benefit most from a DEA visit.

But due to feasibility issues we end up

saying only about 5 patients per day.

However when staffing levels are adequate

at Westmead we will have a full day

shift per week allocated to dashboards

which can see about 40 to 50 patients.

Most involved.

Part of the screening process is.

To identify the patients just see 
first taking you through the steps.

Frankly.

The DEA and 98 protocol 
patients are first filtered

by transferring data onto 
an Excel spreadsheet.

The clear fluids and fluids are excluded.

Patients are then categorized into 
category one category two groups.

Priority is given to Category 2 patients.

Those having low intake first.

And lastly long length of 
stay the longest days.

Patients get priority.

Once a spreadsheet is printed we go on to

the wards and discuss with 
the patients about their

particular low income low 
supply we preferences

to see if the patient is 
consuming the extras.

And if not make alternative.

Their likes and dislikes are discussed.

And.

Moved from home or other 
sources get an ACIM pamphlet

on nutrition in the New 
South Wales hospitals.

We then returned to the office and amend

the MFC notes and seaboard preferences.

And finally notify the ward dietician.

There are some limitations as 
to why the meal intake cannot

be conducted by the food 
service assistance such as.

If we have seaboard issues 
and the train tickets are

printed on A4 paper instead 
of the automated printer.

Or if the meal intake.

Can only be done if it's 
been from properly promoted

to the final stage of 
the life food choice process.

So for instance when a train ticket is

printed it needs to be pushed through to

plating stage to reach 
those stage delivery

and then finally the pick up stage.

So if there is a place 
that's been missed the FSA

is then counting the final 
intake for the patient.

Recently we also found that 
the shortage of iPods and Wi-Fi

connectivity issues caused a 
delay in data connection.

Collection.

Additionally we have found that 
once a day code has changed.

Multiple meal intakes need to be carried

out by the food services system.

This leads to corrupted data.

So I'll show you on the next slide.

In room service you can see 
that this patient has

changed giant codes 
after the cut off time.

The train tickets were 
printed three times.

That.

10 0 6 eleven twenty two 
and eleven twenty five.

And two of these tray 
tickets were identical

as you can see on the bottom screenshots.

This means that the moves to where

the food service stack went to collect

the meal tray they were required to 
take three separate meal intakes.

The food service then conducted 
the meal intake on the first meal.

As you can see by the green dots.

And.

For the old following meals placed in any

or the recent code food or tray missing.

We are still unsure how this data is

then interpreted into the dashboard

because there's two separate mailing 
texts for the same patient.

Another feature of the document 
we're still unclear about

is how the NH option affects 
the overall data quality.

Says now had mentioned that we also have.

Patients who have had a 
enter during meal intake.

When you do do that it prompted 
you to put in a recent

code and some of the recent 
codes are on the second.

On the right so it can be due to diet

change which is a popular one for us.

If she kept tray or food 
or if the food items are missing.

It is important that I 
mentioned that we all see

the NRA as a reason for 
the UNC unaccounted data.

At Wesley.

Some of the challenges we face 
in the Indonesia shouldn't dash

or daily the long list of 
category one patients each day.

Approximately 200 patients.

And since the dashboard has 
so much data in it it can be tedious

and time consuming to be 
filtering out on a daily basis.

We also find that 
the color coding the red

and green is this in 
the analytical data section is

the same for the reason 
code and the default

meals so it can get a 
bit confusing at times.

Lastly the risk category does not

necessarily identify patients at risk.

We found that most of our Category 
1 and 2 patients indicate that

they're consuming adequate meals 
from home or from other sources.

However the intake does 
make account for this.

>> Passing on so much.

Thank.

You.

>> Thank you.

So.

I'll just speak about 
the some findings of

the student project conducted last year.

So there were specific errors 
that we had. The first was to

review the quality of the nutrition 
additional data and display.

Analyze the rate of missing data.

And we also analyzed 
the rate of different news as

was indicated by 
the nutrition dish at the time.

The third aim was to 
assess the usability of

nutrition dashboard data 
and clinical practice.

And the third was to assist in

the mobility 
and the relevance of nutrition.

>> Meal data over three consecutive 
days or nine main meals were

analyzed and then an average was 
calculated for each category.

>> Was accounted for.

>> So we discovered that nutrition Deshpande

displayed many reasons for quality data.

We knew about the first three reasons 
which were that patient kept tray

of food item tray of food item was 
missing and patients refused meals.

However we did know that.

That poor quality data was 
also reflective of all

the changes computer system 
errors and also where

food service staff mentally 
entered reasons such as

food item missing or when 
the tape was not done.

So.

What we found in in particular 
we found that the neuro gastro

and surgical cardiothoracic wards

averaged the highest poor quality data.

And the reasons where their patients kept

their tray of food item 
away and it was by

choice the cardiology 
and the strong wards

demonstrated the highest quality data.

There were some computer system errors

that contributed to the quality of data

at the time and this was specifically

specifically identified in three wards.

This was reported to share for 
rectification at the time.

Then we also looked at 
the range of different builds

as was indicated by 
the nutrition dashboard.

This time we studied 
the items selected in that.

And where a rare segment indicated 
patients receiving default meals

and the Green Square indicated no issues

but to our discovery a blank section.

Indicated.

That patients did not select a meal 
but also did not get a default.

This was not known prior to this study.

And Hilscher was consulted 
for advice again.

So we found that there was a default 
rate of 30 percent which was

different to the health share 
report that we usually would get.

And I think if it will agree with me 
we get about 15 to 16 percent of

default after Michael choice was 
implemented for Westmead behind you.

Neurology and the trauma wards 
have the highest default rate.

Incidentally we also 
discovered that two out of.

That two out of three study days are

few wars according to the nutrition

dashboard did not receive any meals 
nor did they make any selections.

We later found that this was a system

error and nominal indeed was conducted.

For the mentioned wards.

Now moving on to the staff survey.

So we surveyed about eight 
dietitian assistants some open

and close questions were asked 
such as whether the data used.

Nutrition dashboard if they understood

the nutrition dashboard functions

the reasons why they 
used it and if standing

of the risk category that was correct.

We found that 100 percent of 
the dietician assistance used

in nutrition dashboard as 
part of their work routine.

However 30 percent misinterpreted 
the risk category.

Similarly we surveyed the diet 
conditions and in addition

we investigated 
if the dietitians correctly understood.

The reason he.

Will map at patients meal consumption.

We found that almost 80 percent of

the dietitians used a 
nutrition dashboard of which.

80 percent.

Viewed intake analysis.

Seventy five percent looked 
at the data quality.

Only 25 percent viewed meal selection.

And 8 percent.

Only 8 percent looked 
at the risk category.

We also found that 50 percent 
indicated that nutrition

dashboard assisted with 
identification of nutrition risk.

50 percent did not find it to be a time

consuming so time saving tool but I found

it helpful for pictures from not picking

the crown or the geriatric portions.

Of 80 percent indicated 
that nutrition digital

dashboard did not assist to prioritize

debt and 75 per cent of the dietitians

made incorrect interpretation of the meal.

Indeed about.

About 50 percent also did not refer to

the reason he called Map and subsequently

were unable to make an interpretation

of the red amber and the green squares.

There was some discussion that came 
out of this project and there

were that milk consumption data 
quality is a complex issue.

Energy and put in consumption on.

Nutrition dashboard may 
be underestimated. High

quality milk consumption 
data does not affect.

Patient consumption.

There may be some computer system around

and it was difficult to decipher

the reasons why a patient did not 
select a meal not provided with one.

So.

The recommendations that were 
made out of this project

again was ongoing training for 
full service systems and.

Communication of food consumption 
standards with patients.

Integration of nutrition dashboard.

Seaboard empowerment chart.

For dietician assistance to 
be trained to include data

collection to collect data on 
specific patients assigned

by the dietitians maybe 
and some comprehensive education

on all segments of nutrition 
dashboard for dietitian.

And dietitian assistance.

Again there were some limitations 
so not all the boards

were included in this study due 
to the limited time frame.

>> It was difficult to validate the results.

It was also difficult to 
draw conclusions between

rates of milk consumption 
data and specific boards.

And.

I've.

>> With my time.

So in conclusion the study 
results demonstrated some of

the liability issues with 
the quality of data that was displayed.

In.

Training with particular 
focus on clinical practice

and user visibility in large 
hospitals like Westmead.

May put in shared some enhancement 
and improvement of patient outcomes.

And I would like to say not 
blind our practices at

Westmead should be 
considered as best practice.

>> So our final presenter today will 
be tracing Patrick's who's a hero.

He's a head dietician of Coffs Harbour

Hospital in the mid north coast LH day.

>> Already unfortunately was on 
leave today so we were very

appreciate appreciative of 
her preparing the slides.

We're also very grateful to 
Tracy for agreeing to step in.

Today for us she's up tracing 
presenting on how the train might

and dashboard data is used a small 
city with limited dietitian

hours against a different perspective 
on how it's used to benefit

clinical practice and we say 
Tracey for joining us to do so.

>> The nutrition dashboard 
and tray monitor are

used routinely at Maxwell 
district hospital to

assist with the management 
of the dietetic

caseload and in 
the nutrition care of patients.

I'll give an overview of 
their use and potential

benefits that other sites 
so Mexico is one of

our smaller facilities 
in the cost clinical

network of Mid North Coast 
Local Health District.

It's a level 3 48 bed facility about 60 K

south of coffee so about 
a 40 minute drive.

Today having a look at Maxwell today

there's 36 patients in Macksville today

so about 75 per cent 
capacity and two thirds

of those patients over 65 years of age.

The patients there there are a few acute

but mostly they're subacute 
patients mostly rehab

and recovering from 
surgery or complicated

extended hospital stay 
hearing costs or waiting.

Residential aged care facility placement

Brody commenced at Macksville in

the beginning of 2016 with the brand new

position so she's built 
it from the ground

up and done an amazing job and as we've

seen on the wall has a wonderful

close relationship with food services

and they work extremely well together.

Next slide please.

Okay so the first My Free Choice 
Program and nutrition dashboard use

at Macksville Brody uses that in 
a number of ways for triaging

MSP patients for screening patients 
not referred via MSF T for

nutrition risk and for triaging 
conventionally placed referrals.

So for the three out of M S T 
patients like most places due to

limited dietician hours we need 
to try out our patients and many

of the patients referrals at Macksville 
are automatically generated

referrals from an MSA team 
completed by the nursing staff.

So the nutrition dashboard is helpful

for Brody to filter through those M.S.

to refer patients to see 
what else may be going on.

So having a look at today's list 
there are three three new referrals

three M S T two patients and of 
those three to have an M S T.

Oh sorry.

There are three Category 1 patients 
and 6 Category 4 patients.

Nothing in between and two of those in

those Category 1 patients are don't have

any m t completed and one of those

Category 1 patients have an M S T of 2.

So Brody would you the nutrition 
dashboard to have a look at those Ms t

patients particularly the two and use 
that further nutrition dashboard

data to treat those patients for 
the screening of nutrition risk for

patients that don't have any Misty 
referral or any other referral.

Again Brody can have a 
look at the nutrition

dashboard and see which 
again the risk category

1 and 2 patients and place 
a referral herself

and see those patients as time permits.

>> For conventionally placed referrals.

Again Brody can use 
the risk categories to

determine who are 
the higher priority patients

and who might be a little more complex

and make time and try out 
those patients as well.

Another way that Brody uses 
the nutrition dashboard is

to use the estimated energy 
and protein intake again to

help him form her nutrition 
assessment along with all

of the other data collected 
from a variety of sources.

The other system that Brody uses is

the train monitor a wall crime monitor

is conventionally used by food 
service staff to manage workflow.

It can be a really valuable source of

information for the dietitian as well.

So there's two applications in train 
monitor that proteins will use at

Macksville and that includes 
the mobile intake data and export control.

>> The next slide.

>> Yeah so you can see there with 
a monitor which we have a

link to connect to which I'm 
sure everyone's familiar with.

We can have a look at the reports

and the mobile intake data 
so the mobile intake data.

First up on the next slide is used to

check me or Camille what patients are

ordering to check 
if patients are consuming

supplements or other nutritious food

or drink items that the dietician might

have implemented 
and to see which patients

are declining meals 
or if meal choices are

being made without the patient's input.

So I find it useful to cross-check this

data also with 24 hour recalls with

patients particularly those who may be

poor historians or a little confused.

Also we use that here it costs 
to check on consumption meal by

meal to make sure that items that 
the patient enjoys has been

chosen and two to check that 
patients are consuming those

items that we might have discussed 
and implemented with them.

Another thing that we use to try 
and take data for was to do

an intake data audit which students 
conducted for us last year

so they gained access to the to 
their train take data and use

that within their audit which 
I'll discuss in a little while.

So they monitor reports are often 
run at Macksville to assess

the intake of patients that have been 
admitted for less than three days.

As we know the nutrition 
dashboard kicked in after

patients have had data 
collected for three days.

So for both patients who are 
in the first three days

of their admission 
and the majority of patients

at Macksville are in for 
greater than three days

they have an average 
length of stay of 13 days.

So because BART is only 
there two days a week.

Often you know she'll be referred

patients within those first three days.

So the thing the train modelling 
data is really useful

until the nutrition dashboard 
information kicks in.

So those reports are really useful to 
evaluate not just in a GM protein

but to also look at any other nutrients 
that you might want to consider

for patients whether that be carbohydrate 
distribution or fiber intake

fluid exchanges or any of 
the electrolytes or vitamin intake as well.

>> Next slide.

Thanks.

>> So we very interested as well to 
have a look at thin accuracy

and the reliability of the data within

tray monitor and the nutrition dashboard.

So last year we asked our food 
service students from Newcastle uni

to do an audit for us and have a 
look at the accuracy of the data.

The guys have my fair choice.

Of course Brad was hesitant to rely 
too much on the data as we were

unsure of the accuracy being in 
the early days of my food choice.

So we were really keen to get a bit of a

reflection of how accurate that data is.

So that said last year students 
from Newcastle uni conducted

an intake data audit for us 
and Macksville got the gold star.

They were rated at 80 per cent 
86 per cent reliability.

So above the 80 per cent benchmark set

by health share the overall reliability

of the data for cost clinical network 
was 81 per cent but I think Matt

Max feels good data pushed this up a

little bit because costs was overall

seventy seven per cent Burlington 
or so a very commendable 80 per cent.

And as I said gold star to Macksville 
86 per cent so that improved.

Di dietician confidence in in the data.

But of course you know it's it's part of

a lot of different data that we use for

assessment and monitoring and evaluation

not just ourselves source of data.

So how was that good result achieved.

As I said borrowed the dietician down

at Macksville since then instigation

of the position in the beginning in 
2016 and has a great relationship

with food services down there 
and she conducts regular in services

and consults you know weekly where 
food services staff she made

sure that that the that the good 
results of this particular audit were

relayed back to food service staff 
and so food services staff you

know they know the importance of being 
accurate with this data and they

understand that they're also 
an integral part of great patient care.

Dan Maxfield.

>> Great nutrition care and having that

understanding of 
the importance of the role

that they play and that they have a very

important part to play in nutrition care

>> I think he has continued not 
only the great relationship

road has vested services 
but the reliability of that data.

Next slide please.

So yeah we see hospital wide benefits of

the tray monitor 
and nutrition dashboard data.

It allows folks limited time to be 
efficiently used in the third to

to trash priority patients by having 
a look and cross checking with

the key referrals the regular 
referrals and those patients are not

referred at all by cross checking 
with nutrition dashboard data.

We can zero in on those patients in most

need within a limited time and limited

FTE it assists with estimating oral 
intake of the patients and gives a

quantitative methods 
that perhaps we haven't

had the intensity of that information

before and it decreases their reliance

on nursing staff to complete C chart.

There's a pretty high nurse to 
patient ratio down at Macksville

so anything that we can do 
to assist in alleviating

their workload demand to also 
help to improve working

relationships between 
dietetics and nursing staff.

So lastly I think.

It's ongoing.

Party continues to work very 
closely both with food

services staff and ward 
staff and ensure that

the kitchen staff are 
empowered and feel that they

have an important role 
in the care of patients.

And we would like to properly 
implement annual audits to

ensure that the accuracy of 
the data remains as high

and perhaps to set a 
benchmark for the rest of

the cost clinical network to 
run to meet Maxfield results.

So putting a bit of a 
challenge out there between

our facility and even 
if the data isn't accurate.

What we can consider is 
is using train monitor

to check what the patients are ordering.

If nothing else to better inform our

nutrition assessments and to also use

the nutrition dashboard to flag those 
patients who are on the ordering.

That's it for me.

>> Thank you.

Thank you Tracy.

Appreciate that.

>> Please say thank you to all that for this.

Well that's the end of our presentation

session today and I'm sure you'll agree

that there was lots of different

perspectives provided and I think 
that demonstrates that the data from

the dashboard and from 
tray monitor is just

not one solution as to how you can use it.

>> You can customize it to 
your own facility. You

can make it fit your 
workflow as you think

is most appropriate and most practical

and sometimes implementation 
is quite challenging.

So there's some hurdles 
you need to get over

but I think it's also really reassuring

that we've got lots of departments in

the state now who have 
who are utilizing it.

You've had experience and I'm 
sure would always be very well.

>> JJ any tips or tricks 
or advice or or you would just

be a shoulder to cry on 
if you need it so reach out

and talk to your colleagues 
especially our presenters

today I'm sure that I'll 
be happy to contact you.

>> So after some pressure we 
still got 10 minutes left.

I've received a couple 
of questions through

slideshow and email which I can lead with.

So if you've got any questions 
I'd like to share.

By the way I can I can raise that.

So the first question I 
received by e-mail.

Was.

From Caitlin.

So a question if no one else is us 
is there any concerns regarding

the quality of the per cent 
consumed data being entered.

If there have been concerns that 
this may not be accurate estimates.

Have you had any strategies 
to manage this.

And I feel that this is a large barrier

to using the dashboard so I might

open that up to one of our presenters 
to contribute to that response.

If you have something to say.

I guess with us that's something 
that we want to work with.

So.

That we sort of continue doing 
ongoing training and ongoing.

>> Compliance checks because 
there is a lot of

interpretation when you actually 
go to pick up the food.

It's all well and good when 
it's in the prepackaged meals

and all the protein and the veggies 
and everything all set up.

But once you actually go 
to collect the meals

and all the food is sort of 
mashed up together it's

hard to sort of determine 
which portion of

the veg which portion of 
the protein has been eaten.

So there's a lot up to interpretation

and that's why we kind 
of take the dashboard

as face value and then go into our own

investigation to find out whether that is.

Accurate or not.

Any other presenters like to add to that.

I think.

>> Like to do it.

It's definitely a concern 
and it's something

that we're looking into investigating

as a project because I wouldn't think

it is a lot of work that can be done.

So nothing that we've done yet.

But.

We have our eyes on it.

>> So if I could just reflect 
on the presentation

from Tracey it sounds like Brody's done

a lot of work in that space to try to

assure the quality of 
the data is accurate.

And I know that he'll share 
in-house training programs

for their staff to do that 
but also keep in mind.

What did nursing staff do before 
when they recorded a food chart.

They've been having different 
challenges or the same challenges.

So I think it's great that we've.

>> This process in place and yes it could be

improvement strategies that going forward.

But.

Great.

Thank you.

The next question we have is that if.

We're.

Providing a supplement to the patient

and they move out of 
categories Category 1

is there any evidence to show that

consuming more and not just ordering more.

>> Yes.

So on the dashboard at 
the bottom this some options.

And one of them is intake analysis.

So when you open that up on.

My.

Side.

I.

Just pull the sign up so I can talk you.

Kept.

Coming.

Up.

Well.

Yeah.

So looking at that side there.

So that's the.

Protein and energy contribution 
the red part of the bars is the.

Contribution from the supplement.

So if you open up the patient's 
file you can actually

see how much of the supplement 
they are consuming.

So for that particular example 
that I had the day I did

offer the sausage and it did 
provide more nutrition which.

Had.

Allowed the patient to move out a 
Category 1 but what had actually

happened is they were then 
Category 2 because they weren't

actually eating enough of energy 
and protein but these other

processes in place like embassy 
screening and the dieticians using.

The dashboard for what screening 
was also being present

in empty ts in hope that 
they will pick up a patient

like this to do further 
intervention and investigation

but yet generally can investigate 
how much they drink.

So.

>> Thanks.

We have a comment from Shannon 
Singh from he'll share

that it was interesting 
learnings from all sides.

And thanks so much for sharing everyone.

It's great to see that 
the dashboard is being used.

I agree.

That is good news.

>> I haven't received any other question.

A question I want to throw out there.

>> Making it easy or easier or better

or enhancing your bill be a clinician.

>> I think it's definitely 
enhanced our workflows.

I think previously you know if we wanted

some detailed information around patient

consumption you would 
have to implement some

food chart for the nursing staff to to do.

And I was always a fan 
of using the escapes

me in Cebu and you could turn on.

A.

Calorie count that's it.

Sorry.

Thank you.

But then you would need 
to bring the food cart

back from the board 
and input the percentages.

And you could print some reports 
out doing that if you wanted to

get you know I think called report 
around patient consumption.

But again you know you 
were relying on nursing

staff to be accurate and we all know that

the food the food charts 
by nursing staff were

rarely completed the way 
we would like them to.

So I think it's just really handy 
to be able to have access to that

data through either train monitor 
or the nutrition dashboard.

And I guess it's helped workflows 
and workload from that

perspective for both nursing 
staff not having to keep

the the food carts 
and the dietician not having to come back

and put those those percentages 
into the calorie counts.

So that's a bit of an advantage I see.

So malamute with me I would say that it

doesn't help all of them but as I said.

Some dieticians to.

>> Jewish patients.

So someone just.

>> Thinks that to me I as a clinician 
I have found it very valuable

and useful because you can use trained

well I tend to get that intake data

but myself I'm quite a visual person

so I like the the graphs and the picture

tutorial patients with the intake to

investigate the trainings of what's

happening and I think workflow wise 
maybe it hasn't completely helped

me because it does take more time 
talking but like I'm quite enjoying

investigating the point 
of what's happening

and trying to understand what's

happening with this admission and just

do a more comprehensive assessment.

>> Thank you.

I think just from my past 
experience and using it

it's not providing you all 
the information that's

providing a part of the puzzle to start a

conversation to look maybe 
in a different direction.

And I think anything you.

Add to that making the assessment more

comprehensive I think is valuable.

Just up on the screen now 
is the contact details

of the position so we're 
coming up to the time.

So I really like to thank again 
every presenters for their talk.

If it is apparent today I'd 
also like to thank all of

these innovations or practices 
that you'd like to share.

Please be in touch with me and we can 
work out a way of disseminating

it through the network because 
I think there's lots of gold

everywhere out there and what you 
would do it might really help some

colleagues improve a process or do 
something better somewhere else.

So thank you to everybody.