Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network. We will explore perspectives of clinicians like dentists, physical therapists, nurses, and physicians in all sorts of practice settings worldwide. Emerging technologies, telehealth, gaming, simulations, and eScience are just some of the topics that we will consider. Throughout the course, we’ll focus on creativity, controversy, and collaboration - as we collectively imagine and create the future within the rapidly evolving healthcare informatics milieu. All healthcare professionals and IT geeks are welcome!
Standardization - Part 1
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From the course by University of Minnesota
Interprofessional Healthcare Informatics
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From the lesson
Data Exchange and Interoperability
This module explores interprofessional aspects of healthcare data exchange and interoperability. By the end of this module, learners will be able to: describe information exchange and interoperability and analyze interprofessional aspects of information exchange and interoperability in healthcare.
Meet the Instructors
Karen Monsen, Ph.D., RN, FAANAssistant Professor
School of Nursing
Welcome. I'm Connie White Delaney from the
University of Minnesota. I serve as Dean of the School of Nursing
and also had biomedical health informatics for the Academic Health
Center. And, what you'll discover in our time
together is my absolute passion for biomedical health informatics.
And I have focused most of my career on the topic we're going to be talking
about, which is standardization. A key element of infomatics and
essentially forms the foundation for all interoperability and exchange.
But this is my real passion for informatics.
You and I have the ultimate opportunity and empowered opportunity to ensure that
families, communities, and in fact all of us in the global community, are
represented within the electronic health records, electronic databases, in our
research, in their fullness. And what I mean by fullness is We can
have diagnostic data about patients and families and communities.
We can have demographic data, but what really matters to the people we serve, is
what they think about their patient experience.
Getting home being able to interact with their family, having appropriate support
systems, being a full part of their communities.
And if the time and when the time comes, transition into a natural supportive and
peaceful death. So my foundation and passion for
informatics and for the topic we are talking about standardization Is always
fundamentally grounded in the people we serve, and my family.
So, let's share some thoughts as we deal with this topic of standardization.
The first place I would like to start when we think about our healthcare system
and the electronic Foundation that you and I are helping to create is
represented by a large initiative in the United States entitled the Continuously
Learning Health System. Our vision for that system is that we
will learn from the system, it will support our learning, it will support our
patient care and from those learning's also we will improve the system.
So, the continuously learning health system as you see here will generate and
apply the very best evidence, the best practice.
For you and I, and, and in supporting healthcare choices and provider.
It will drive the process of new discoveries.
And that will be a very natural outgrowth of the care process.
Whether it be patient, families, or communities.
And most significantly, to us as well is. A system that ensures a continuous
process of innovation, quality safety, and assuring value and healthcare.
You see a quick picture that captures all the elements at a very high level that
contribute to create a continuously learning health system.
You'll notice. That policy and technical infrastructure
are the core foundation as is privacy and security.
And an area that you and I spend a lot of our time on is how do we determine the
meaningful use and support the meaningful use of health infromation technology.
So, standardization comes in, in all three of these levels.
The continuously learning health system in the United States is supported by a
clearly defined Federal health IT strategic plan.
This is the plan for 2011 to 15. And you see the pattern of thought,
better technology, better information. And therefore we have transformed
healthcare. There are five fundamental goals.
We'll start with number one. Achieving adoption and information
exchange through the meaningful use of information technology.
And then you can follow the goals two through five that build upon this
fundamental information infrastructure. It's this fundamental infrastructure that
you and I are talking about at this time. And ultimately it empowers people through
IT to improve their health and to improve the healthcare system.
And then, helping us acheive a rapidly learning and technologically advanced
Information system and learning health care system.
So let's take a look at some fundamental concepts that relate to standardization.
A standardization that assures that we can exchange data information and
knowledge. I'm going to focus my comments on the
nursing minimum data set, the nursing management minimum data set, and an
international initiative, the international nursing minimum data set.
I'm simply using nursing as an example of essential data.
There are many other examples related to medicine in the other healthcare
professionals, and other providers. I'm focusing on nursing, we have one of
the most advanced and local to internationally articulated essential
data set works in the world. And again, the fundamental purpose of any
of this work in nursing minimum data set or essential data, is always grounded in
having the ability to most fully, deeply represent our patient's families and
communities. The decisions they make.
The decisions that providers make and the full experience of health care delivery,
meeting our health goals, safety goals, and of course, cost and efficiency goals.
So let's take a look at each one of these minimum data sets.
Again, the three that I'm going to focus on are focused on nursing simply as
exemplars. They include the US Nursing Minimum Data
Set, the Management Minimum Data Set, and the International Nursing Minimum Data
Set. Let's look first at the purpose of the
essential minimum data sets. Of course, they are designed to meet
information needs of multiple users, whether that be the provider, the
patient's families, pairs, policy makers. They are intended to be minimum, core,
essential data that captures the, care experience, the care delivery.
And minimum data sets enable the collection, the management.
manipulation and communication of data for many many purposes.
Of course those purposes relate back to the information needs of multiple users.
So let's look at the US Nursing Minimum Data Set.
That data set was actually derived in the 1980s.
One of the most famous developers associated with the US Nursing Minimum
Data Set is Harriet Orley. The data set consists of 16 elements.
They're organized into three large categories, and you're going to see a
similarity as we progress through the review of these three minimum data sets.
The first is nursing care elements for every patient, family and community that
we care for it's essential that we capture the nursing diagnosis.
And yes, that is different than the medical diagnosis, nursing interventions
nursing outcomes and something called the intensity of nursing care.
You and I can think about that as the resource related to people and time
required to deliver this nursing care. It also contains a second category of
essential data that we need to know about each patient, family, or community we
serve. For patients, personal identification,
date of birth, gender, sex, race and ethnicity, and the residence.
And then the service elements, some information about where the care was
provided. The facility or agency number, unique
health record. The unique number of the principle
registered nurse provider, when the care started, when it ended, what happened to
the patient or client, did they die, did they go transfer to skilled care, were
they able to go home? Who is the expected payer of the bill?
Many of these elements have been collected in the United States for 50, 60
years under something called the Uniform hospital discharge data set.
Why I highlight the UHDDS data collection is for those of you interested in
studying healthcare delivery and transformation over time.
This represents humongous data set that would support your scholarship.
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