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.