Now that you’ve carefully planned your patient safety and quality improvement project, the real work can begin. This course will introduce students to the unique challenges encountered when implementing, maintaining, and expanding a patient safety and quality initiative. Students will learn to apply lessons learned from the 4 E model and TRiP into developing specific aims for their QI project. Additionally, students will develop a plan to address the adaptive and technical challenges in their projects including whether their initiative needs to be submitted to an Institutional Review Board (IRB). Finally, students will develop plans to grow their local QI project into a system-wide project.
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Destrezas que aprenderás
Risk Management, Project Sustainment, Plan Implementation
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4.8 (22 calificaciones)
- 5 stars19 ratings
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SS
May 23, 2018
Fantastic course content and marvellous mentors. I am very grateful to both mentors and Coursera.
NV
Sep 29, 2018
Very informative good quality lectures. Recommend to others also to do and gain knowledge
De la lección
case story: technical work meets adaptive work
In this module we will introduce you to a quality improvement project that we implemented in two adult Intensive Care Units, to reduce Central line associated blood stream infections. The learner will develop an understanding of using the Translating Evidence into Practice model into action in developing a technical component to improve patient safety. Learners will become familiar with the Comprehensive Unit Based Safety program (CUSP) and the adaptive work used to implement the quality improvement initiative and change management methods that help achieve success.
Impartido por:
David Thompson DNSc, MS, RN
Associate Professor
Hi, I'm here to talk to you today about the technical work and
the adaptive work that we've used in quality improvement.
They really have to be done well together.
And I think, after you listen through this session,
you'll be able to take what we've learned in our journey for
the last 15 years and put it into good clinical practice.
So just a little bit of background,
we all know about the the Harvard study,
that 44,000-98,000 people each year die,
and many believe that that is an incredible underestimate.
One of the more recent facts is that preventable harm,
that harm that we cause within the hospital,
is the third leading cause of death,
which is quite shocking.
That's greater than cancer and many other things that were here to prevent.
So preventable harm, just so that we have a feel for what we're talking about,
is anything that you don't need to be harmed by.
So, putting in a central line or by turning a patient,
all of the things that we do within a hospital that should not cause harm,
and yet they cause not only harm but they cause death.
So up to 30 percent of our patients suffer some type of preventable harm.
This can be in the type of an adverse event to fall.
Things that we're very familiar with ubiquitous receiving the wrong medication.
And 30 percent is actually quite a lot.
It was probably a lot more before we began looking really intently at quality and safety.
There's also the problem of the 60 percent of our patients report that they were
not either respected or that their wishes were not heard.
Now what this says to us is that,
the lack of respect is actually a type of harm because we don't want to be paternalistic,
we want our patients to have a say,
we want them to have the outcomes that they wanted to have.
And more and more, we see that it's important that we report patient-centered outcomes.
As we move forward,
we'll see that a lot of things within
the last two decades or since the IOM report came out,
to err is human.
And then Crossing the Quality Chasm.
And those things are the things that we'll be talking about today,
things that we can do to prevent preventable harm.
In the US healthcare system,
one-third of all healthcare spending
is spent on things that don't work well for our patients.
We don't improve our patient outcomes.
There's a lot of reasons that's a little bit different than in other healthcare systems.
One is our need to continue to order tests,
because we fear liability and malpractice.
But another is because we worry that we're going to miss a diagnosis.
And in medical school,
with nursing school, we're all taught to be perfect.
The problem with that is,
is that nobody's perfect, we're all fallible.
And if you look at the literature it says that,
"At any given time,
we can remember three plus or minus four things."
Which means, as good as we can be at multitasking,
there's always going to be something that we're going to forget.
And that leads us to the next bullet point that I wanted to point out that, on average,
about $9,000 is spent on these therapies per household in the United States,
whether they are deemed effective or not.
And this has really put us in an awkward position,
because not only are we spending unnecessary dollars,
we're not getting the patient care outcomes that we would like to see,
not as clinicians but also not as
patients and the families that love their family members.
So, what I thought I would do today to kind of
explain the difference between technical work and the adaptive work,
and how they come together to really illuminate quality improvement,
is to talk about a case study that we did here at Johns Hopkins.
And it really involves just a couple of units to start with.
And we had what we would consider
a significant problem with central line associated bloodstream infections.
That led us to believe that there had to be methods out there that we could
impart and get our frontline providers to participate in.
The problem that we saw was that
a lot of the structural models were not meant for healthcare.
So in addition to having these problems,
we had to find a way to both implement and identify both the technical work,
that part that is supported by science,
as well as getting people to do what they're supposed to do.
And it's not like we expect that our providers
come in and purposely don't do what they should be doing,
but they're not always aware of the evidence,
and I think that's what was really important.
So, as I explain this case study,
you'll be really looking to see how we adapted
our work using the adaptive mechanisms that we talk about,
but also how we got it implemented.
And you'll see that even though it seems like a really simple thing to implement,
infection control bundle into units,
you will actually see that it took multiple steps.
And the biggest part of this was not pulling all the literature together,
it was addressing the adaptive components.
But we'll show how we work with those together.
So here we are.
As you can see, this was quite a long time ago.
But as you can also see,
for those of you that are familiar with
the NHS Data or the National Hospital Surveillance Data,
the goal for a CLABSI rate is zero or less than one is what we would like to say.
And as you can see,
in the 1990s and 2000,
it took us a long time to get where we needed to go.
But it was wholly unacceptable and untenable that we could not prevent this harm.
And as you can see,
our rates when we started were 10 per 1000 catheter days,
up to almost as high as 20 per catheter day depending on what unit we looked at.
And this is an aggregate of two of the units that we placed most of our focus.
And you can see that we have spikes and we have faults,
and those are things that are normal with any project.
And the goal is to have a baseline at the end that is showing no change over time.
There's always going to be a blip,
there's always potentially a patient that
you won't be able to prevent to have an infection,
but those should be very rare.
And I can tell you now after going through this,
we've had many of our units celebrate several years,
as many as four years,
without any type of central line associated bloodstream infection.
But as you can see, the work ahead of us was hard because
our rates were significantly higher than the national average.
And certainly, they needed to be addressed,
even though most providers that we talked to felt that
a central line associated bloodstream infection was almost expected,
just like they expected some patients would develop sepsis.
If we do everything correctly,
we followed the evidence,
all of this preventable harm can be diminished over time.
And that's what we're going to show you today.
So, how do these errors happen?
Well, every system is perfectly designed to achieve the results it gets.
And one of the first things that I wanted to point out was that when we began to look at
our process in one of the units that we worked in,
one of the ICU's that we worked in,
there were eight different places that the residents had to
go to collect all of the equipment that they needed to place a central line.
So we began to focus on percutaneous placement of central lines.
So the system was incredibly flawed.
We did not make it easy.
Some of the things were locked up.
You had to get a key to access the central line kit.
Some of the things were in a Pyxis system,
so you had to know what you were looking for.
And if you were a resident,
not all Pyxis systems we found were labeled with the same equipment.
So, although they had the same equipment,
they might be called something different.
So it took a lot of time.
And when anything takes a lot of time and when you're a busy unit,
one of the things that you're going to try to do is,
you're going to try to have a workaround or you're going to not
participate in every one of the steps that your policy and procedure would guide you to.
The other thing that was really important to know,
not only were we not set up to do a good job with
the central line associated infection reduction,
but getting people to admit that we're fallible, all people.
And as I said earlier,
we can't multitask as well as we think we can.
And everybody, no matter who you are,
how high ranking you are,
you have the potential to make a mistake.
So for all of us that say to ourselves,
"I don't make mistakes."
Think about it. You've made one mistake at least in your life and probably many more.
Some of them have no complications and they really don't mean a lot.
But other ones have significant complications.
And we must look at how we develop
our Quality Improvement Project so that our health care delivery is more scientific,
that it's based on evidence rather than just how we've always done it.
In fact, that's one of the big push backs.
Well, this is how we've always done it.
Yes, but that is because we focus on bench research,
so, what is the cure,
and clinical research, how do we get that out of the patient,
without any focus really on how to best implement that for the patient and their family.
How do we do that without causing harm to the patient?
What is the best way to do that?
Those were some of the things that weren't addressed for many, many decades.
And it's been within the last 20 years that we began to look at things like that.
So, we need to engineer the systems that we work in to really catch the defects.
The big reason for that is,
of course, before they reach the patient,
there may be near misses as opposed to adverse events,
but we don't want preventable harm.
In fact, we've pretty much proven after this project that
a lot of harm that occurs to our patient is wholly preventable.
There's no reason anybody really needs to
suffer a central line associated bloodstream infection.
Now, if we look at these three principles,
they mean a lot to our work.
Not only do we want to standardize care,
we want to standardize care
in a way that's evidence-based so we don't want somebody to say,
this is the way I've always done it and this is how I plan to do it.
No, it's what does the evidence say.
You standardize care as often as possible so that patients,
when they present to an emergency room,
that you know they're getting evidence-based care.
And that we're just not doing a lot of different tests and
treatments that somebody were actually doing what we need to do for them.
Standardized care pretty much eliminates the possibility that the patient wouldn't get
the appropriate care unless there is a diagnostic error and that does occur.
The other thing is that creating independent checks.
Having two sets of eyes allow us to look at the picture from a different perspective.
Two different sets of eyes looking at the same order.
The example I like to give is when I work clinically,
people would say, "Would you check my insulin dose?"
And they would walk up to me and they would raise up and they would
show me their insulin syringe and how many units they had.
That is not an independent check.
An independent check would require that I actually
look at the MAR and see what the range is.
Let's say their blood sugar was 300 and it said,
give 10 units and notify the house officer.
Well, not only would I need to see the MAR to see what they were doing,
I would also need to see what the glucose level reading was itself.
I needed to see the glucometer, look at the MAR,
and then work with the nurse to make sure that that dose.
That is an independent check,
two sets of eyes doing the same thing.
We do that in most high reliable organizations.
We want to focus on patient harm.
We want to focus on doing
independent checks to make sure that we're not letting things slip through.
And then lastly, as most high reliable organizations focus on their defects,
that is what we need to do in health care.
Focusing on a defect doesn't mean that we fix it and we move on.
We have to really understand how it happened,
why it happened, and what were the system factors that were the cause.
There are many.
I can think of at least 15 system factors in any given hospital.
You have things at the organizational level.
You have things that are also at the hospital level, at the unit level.
Does it involve teamwork and communication?
Does it involve training?
Is it related to the person performing the procedure?
All of those things go into looking at the defect.
As I've said numerous times now,
our defect that we were focusing on was going to be clumsy.
Really, the difference in the work that you do,
the technical work is all based on science and
the adaptive work is based on the culture that you work in.
It's about the people,
how they view the work that they're doing and their perspectives.
Do they believe the work is important?
Because that's what really needs to change.
For those of you that have not seen it,
this is what we call translating evidence into practice or the trip model
that we had been using probably since early 2004 and published it in 2008.
And the whole goal of this was to be able to identify what we were going to fix,
make sure that we were using the best evidence that we had.
And then, a step-wise process to make
sure that it met all the criteria that we wanted it to meet.
That includes walking the process.
Before we ever implement something unit-wide or institutional-wide,
we would set up reviewers.
We would do the literature review.
We would assign partners.
We would look to make sure that the variables we were looking at were the same.
We looked to see how much of the evidence was of adequate size,
that it was generalizable.
We would come up with our framework for implementation.
Once that was done,
that was piloted in the units to clinician champions,
it was usually a physician and a nurse.
But also, it was to see what did they
believe were the barriers or roadblocks to implementation.
That could be something that was completely adaptive,
something that was related to the culture within that unit.
And we'll get more into the trip model to the implementation phase which,
as you see are the last two phases there,
but very important that there is this process out there to help
you with the technical component and the adaptive component
we have into the work so that we can make sure that not
only is the work going to go over well and we're going to have a success,
but that we're going to have buy in from all the appropriate people.
One of the things I think is most important is,
as we move forward into the technical and adaptive is,
it's extremely important that we do more than just sign off on the work.
If you were an ICU director or you're the CEO of a hospital,
and you say, "Yes, of course,
I want you to do this work."
We don't want you to just sign off.
We want you to be a stakeholder.
We want you to realize the value in the work that's being done.
We want you to be informed about it.
We want you to ask questions when we're not getting to where we need to be,
we're not meeting our goal.
We want to address those.
Everybody must be a stakeholder.
They all have a role to play in order to have
the best outcomes for our patients when
we combine both our technical work and our adaptive work.
Summarizing the evidence is what we're going to talk about now.
The reason this is so important
is people think of a literature review and they think, "Oh, how painful."
But really, if you set it up and what we did was we paired a couple of different people,
I think there were 10 people,
two sets of five,
and we would review the same abstracts
and if the abstracts had the same variables that we were looking for,
we would pull them.
We would look at the literature to see,
did it meet our criteria?
Was it powered high enough?
And if not, could it be matched with other research that we could do a meta analysis?
That was incredibly important because later on,
you have to prove to the people that you're working with that there
is actually science that supports the technical work that you're doing.
Equally as important is that it's available for them to see.
Because there are a lot of people that don't fear change,
what they fear is the loss of control.
Loss of control, we kind of say, well, "No,
we haven't been doing it this way but this is what the evidence says all the time."
If you're really good about this,
you're also going to continue to summarize the evidence when
new articles come out that would be pertinent to what you are going to do.
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