Hello my name is Adam Rule and it's my pleasure to present work that I've been
doing with colleagues at Oregon Health and Science University looking at the
tools clinicians leverage in electronic health records to help them write
clinical notes. While we'll be talking about a particular tool used in a
particular context my hope is to help paint a picture of how clinicians
increasingly use programming to write clinical notes. To lay some groundwork
let me start with a scenario. This is Samantha, she's an ophthalmologist, that
is an eye doctor, and it's her clinic day. That means it's one of the days where
she sees patients and she'll have 15-minute appointments every hour for
eight hours across the day so that she'll see 24 patients in a typical
clinic day. Now that's a lot of patients to see and so Samantha often enlists the
help of technicians, nurses, and scribes to help with particular parts of the visits like
rooming patients or performing routine eye exams.
However on top of this clinic load Samantha also has a documentation load
where for each patient she needs to write a note that's used as a legal record
of what occurred during that visit, it's used for billing and reimbursement
services provided during that visit, and is also a communicative document to
help her either talk to her future self or to other clinicians taking care of
this patient down the road about what happened during the visit. Now this is a
lot of documentation to generate and many clinicians like Samantha are now
relying on tools in their electronic health records to help them document at
scale. One of the tools that clinicians are increasingly using is copy paste or
copy forward. That is they can look at the note that they had written for this
patient's last visit and copy some or all of that into the note for the
patient's current visit and edit from there. Another tool clinicians
increasingly use is templates where they can have boilerplate text and data
from the record automatically imported into a template note that they can then edit.
Now on top of that many clinicians are now using a team-based documentation
model where they get scribes or nurses or technicians to start the note for
them to pull in some of the standard data that might go in that note
and they can edit it later with their clinical reasoning and their plan for
care. Now each of these tools is really helpful in saving clinicians time and
maintaining some consistency in how they document but using them also has side
effects that have been discussed widely in the clinical literature.
One of those is note bloat where clinicians increasingly report the
feeling that notes that they use to document care have gotten longer and
less informative. What I'm showing here is a typical note for ophthalmology, that
is eye doctors, in our context at Oregon Health and Science University. It's four
pages long and much of the note is actually bulleted lists or tables of
information like medications, or the patient's problem list, which may not be all
that relevant for the particular visit being documented here. A related problem
is that of note redundancy, that is of text not changing between notes and so new
notes being not all that informative. For example if we look in this current note
and say how much of the text in this note can we find in the note for the
patient's previous visit we find that actually three-quarters of the text is
exactly the same across the notes used to document these two visits and only
one quarter of the text is really new and maybe all that informative.
So there's some side effects to using these documentation aids and in fact there
have been a number of studies looking at how it is that providers use copy forward
and copy notes. However what I'll focus on this study and what has been
less studied is looking at how providers use note templates or collaborate
with members of their team to generate documentation. In particular I want to
talk about a type of note template known by many is dot phrases. So going back to
our scenario with Samantha documenting patient care let's say she's working on
this particular note and she's already written into the note her assessment of the patient's
cataracts, cloudiness in the lens of their eye, and
her plan to followup with the patient in the future about this care. Now she's at a
part of the note that's typically known as the chief complaint, just a one
sentence summary of who the patient is and why they're here today. Now she can
go to different parts of the record, look up the spelling for the patient's name,
copy it into this section. Or she can use a dot phrase.
and in this case one that's typed .oneliner. So you can see dot phrase often
used to refer to the syntax of these phrases starting with a period. And when
she hits enter after typing this phrase the medical record will look at the
specification of that phrase including these kind of bolded data links that
will then pull in data from the record and then interpolate that data with the
boilerplate text to put a blob of text into note. Now if you were to go
and ask just a random clinician on the street odds are they would say yes I'm
familiar with dot phrases or I even use them widely in my practice but we have
very little data about how they're being used. So my colleagues and I sought to
provide a little bit of evidence by asking how is it that dot phrases are
used at least in our context to document ophthalmology visits, eye doctor visits, at
Oregon Health and Science University. More specifically we're interested in
things like what are these phrases typically look like, are they kind of used
to build up a new section by section as we showed before or are providers
dropping in an entire note all at once? How often are these being used, are they used
every visit or just rarely? Who creates these phrases is it hospital or
department administrators who create a single phrase or single template for the
entire department to use, or are providers creating them or even staff
members creating their own? Who invokes or calls these functions in these
phrase,s is it mostly providers or are they delegating to their staff members
to use them to generate notes? And lastly what impact is this having on
documentation, in particular how much of a final note can we attribute and say
came from using one of these dot phrases? In order to get evidence to answer some
of these questions we examined dot phrase use in the ophthalmology
department at Oregon Health and Science University across two years. We pulled
EHR metadata on the dot phrase use and we looked at this metadata for 48
different providers and the hundreds of staff who worked with them. This covered
about two hundred thousand outpatient visits and in the end about five
thousand unique dot phrases that were used
over 600,000 times across those 200,000 visits, so about an average of three of
these phrases being used each visit. Now to our first question of what do these even
look like, when we manually coded all 5,000 unique phrases we found really
three broad categories. The first are what we're calling helper phrases and I'm
showing an example here .VA which becomes the text visual acuity. These
really didn't pull in any data from the record they just saved typing a few
keystrokes for phrases like visual acuity that providers write over and
over again. A second type of phrase that we saw really commonly was attestation or
signature phrase, and this is really more of a workflow phrase. When a provider has
written a note or their staff members or technician has put in a portion of
text in the note they need to then sign and say I attest that this portion of
the note that I just edited is correct. So after editing it a technician or a
provider might use a phrase like this to drop in a phrase that say I technician
so-and-so or what provider so-and-so attest that this information is correct.
Lastly, one of the most widely used categories of phrases we saw were really full note
templates. As opposed to the example before where you might build up a
note section by section, what we actually saw was wide use of these full note
templates that would use dozens of these data links embedded in boilerplate
headers and text to generate a near-complete note all at once that the
provider can then go in and edit manually to put in things like their assessment
and plan. So these were the three broad types that we saw but how often were
they used? Well when we looked across the 200,000 visits that our dataset was
covering we found that over 80% of those visits ended up using one of these full
note templates. Somebody whether a staff member or the provider had invoked one
of these phrases while generating the note. Less-common was use of these
attestation phrases or signature phrases or the helper phrases which were only
used in about 50% of visits. But if we just say what percent visits had any type
of phrase used at some point in writing the note, that's about 95 percent which is the
vast majority of visits. In fact when we looked at those five percent of visits that
didn't have one these dot phrases used while documenting, we
found often these were short stubs of notes, things like patient didn't show
today that weren't the typical documentation flow. One other interesting
thing we were looking at is customization phrases who created them and what we
found is that almost 3/4 of the phrases that providers ended up invoking while
writing notes were ones they had created or customized. So it wasn't the case that
they just got one from administrator or even used a default one built into the
medical record, they had created and customized the phrase. Now this was different
for staff members, whereas staff members only 41% of the time when they invoked a
phrase was that phrase one they had created. More often it seemed the case
that they were using phrases made by other people administrators or the
providers that they worked with. Now we also looked more specifically these full
note templates and found that there was a lot of customization with those types of
phrases and in fact one out of every three providers so that would be 16 out
of the 48 providers in our data set had a full no template that they used and
their staff used but no one else used. They weren't sharing it across other
providers who maybe saw similar cases. Now moving on from customization of the
phrases we looked at who actually invoked these phrases and we found that
providers and staff invoked them to varying degrees. So if we look across all
phrases most of the time 58% of the time it was a provider who had invoked and
called that phrase to help generate the note. But this differs drastically by the
type of phrase so for example for those full note templates more often it was the
staff member who was invoking that whereas for the short helper phrases
more often it was the provider invoking that. So we begin to see this workflow
between this data and the customization data that shows maybe providers creating
a custom template but then having their staff member be the ones who invoke it
during the visit to help generate a template note and then the provider
going in and using helper phrases later as they fill out the assessment and plan
with details of a particular patient's case.
Lastly we were able to use some metadata to find that dot phrases and the data
links buried in them account for most note text.
So when we look here we estimate that 70% of text in the typical note is
coming from these dot phrases and only 30% is either copied in or manually
added. We can break that down further and say almost half the note, 43 percent,
it's being populated by data links bringing in things like medication list
problem lists. And about a quarter of the note is this boilerplate headers that
you might see in these phrases. Now we've shown a fair amount of data about the
use of dot phrases in one context and you might rightly be left asking, so what?
Providers use note templates is that really all that insightful? And I think
there's a couple of discussion points or implications both for practice and
researchers coming out of this work. For practice it shows maybe where some of
this note bloat and redundancy is coming from. If so much of the note up to 70% in
our particular context was being generated by these dot phrases and templates
maybe when we're trying to address note bloat and note redundancy we should be
looking at the design of those phrases in coaching administrators and providers
on phrase design, note template design, while still giving them the tools and
power to customize and localize those templates for their particular clinic.
On. the research side I think it's interesting to note how this data begins
to show how providers are using programming to write clinical notes, and
particularly end-user programming which has been differentiated as the process of
programming primarily for personal benefit rather than widespread public use.
So providers creating these templates
for their own use and those by their staff members but not really for others.
Now as soon as you begin to think of clinical documentation as a practice of
programming I think it leads to a number of other implications. One is the thought
that these dot phrases and the embedded data links are really application
programming interfaces and we might want to think about best practices for a APIs and
how to structure and guide use of these dot phrases. So for example encouraging
naming conventions or verb-action first naming on the name of these dot
phrases. Providing clear documentation so providers can search for existing
phrases that have been created by other people. Currently that's very
difficult to do in many electronic health records. Or providing developer
tools to scaffold and guide providers as they create these phrases noting where
there might be some sources of redundancy or redundant data links that
are just going to pull in the same data twice in a single template.
For researchers I think this, this particular study begs the question of how we might
develop programming paradigms that let providers leverage the power of both
narrative and structured text in the same document in the way that data
scientists are beginning to use computational notebooks to have a
narrative and interactive data analyses in the same document might there be more that we
can do to support providers working with both narrative text in clinical data
in the same document. Here at the end I want to thank all of my colleagues in the
Ophthalmic Informatics lab at Oregon Health and Science University
particularly Michelle Hribar and Michael Chiang, my advisors. With that, thank you all for
listening. I hope this has been at least somewhat thought-provoking for you. Thank you.