John Wilbanks: So, I’m going to cover a slightly different
topic.
Feel free to look us up at sagebase.org.
We’re a nonprofit based in Seattle at the Fred Hutchinson Cancer Center, and what we
do is we try to connect groups of people who have data and would like to share data with
groups of people who like to analyze data.
And so, we have a set of different systems inside the organization, ranging from a data
use and version control platform, for the sort of people who really like to analyze
data from command prompt.
We have about 8,000 regular users there, and we’ve just started branching into actually
running observational studies through mobile devices.
Each of which -- the first two have been approved to enroll up to 100,000 people, and so we’ve
had to develop a whole set of other governance capacities that let us enroll people in a
way that we think is informing.
So, I’m going to focus on that piece and we can talk about some of the other stuff
on the panel.
So, if you’re going to enroll 100,000 people in a study that is only mediated through the
mobile device, simply rendering the consent document as a PDF is not a very informing
choice to make.
So, Sally alluded to interaction in persona-based design, and that’s actually what we spent
most of 2014 doing.
We did about 35 interviews in conjunction with Academy Health and the Electronic Data
Methods Forum with a variety of stakeholders and did persona creation to see, “What are
the kinds of things we can do to make informed consent more of an informing process than
just a static document given that we’re not going to have the experience of the participant
talking to a clinician and having them hand them a form?”
And what we came up with was very much inspired by the way software design works; it was to
think about, “What’s a process that you enroll someone over the course of, using their
phone, that actually informs them enough about the study to make some choices?”
And so, the way that it works is, you download an app on your phone.
One of the studies is in Parkinson’s symptom variation; the other is in post-chemotherapy
cognitive impact, and one of the key ideas from the interview was, “Well, if it’s
on my phone, I don’t want to just swipe right or tap on everything.”
There needs to be something that brings the experience of the study back to the participant
before they enroll in the study, so one of the things we do is we record sensor data
on the phone during very specific tasks.
All right, so if you have Parkinson’s disease, you have hand tremor; you have gait disabilities.
Well, we have an enormously powerful way to measure that by saying we’re going to send
you a notification and ask you to walk 20 feet in one direction and walk twenty feet
back, and we record the accelerometers and the gyroscopes on the phone to get a quantitative
measure of your gait.
We similarly ask you to say, “Ahhh” into the microphone for 10 seconds at a time to
get the muscle tone of your voice box.
Now over time, over the course of the year, which is the timeline for the study, this
gives us an incredibly quantitative picture of the progression of the Parkinson’s symptoms.
We’re also doing surveys, right?
So, the idea was you, during you’re actual consent on the phone -- and we’re not going
to assume that everyone understands that there’s censors on their phone that can be recorded
this way, so you have to shake the phone at that point in the consent process to activate
the censors rather than tap and continue to move forward, all right?
-- we have an animation that is icon based that shows you, as you’re going through
a survey, that you don’t have to answer all the questions if you don’t feel comfortable.
And we came up with about 11 core screens that were generic to informed consent, in
our opinion, for a low-risk, observational study on the phone.
We use the same exact screens for two very different studies.
One is, you know, the post-chemo cognitive impact; one is Parkinson’s, but the interface
layer is consistent because they’re very similar studies structurally.
And, indeed, we’ve now been able to work with three other institutions who are designing
similar style apps. to say -- there’s actually a chance for convergence at the interface
layer for informed consent in a way that makes it more informing, in many ways, than even
talking to a clinician because clinicians are often in a hurry and just hands you a
form and says, “Sign this or you’re not in the study.”
What we’re hoping comes out of this -- and we’ve released all of these things on our
website as an open-sourced tool-kit.
I mean, it’s just a methodology.
It’s just a language that uses iconography instead of text to communicate, and it thinks
about the process that you move through, so it’s not something that we want to proprietize
-- but what’s out of this is, from the geek’s perspective, if you start to stabilize on
a set of icons and screens -- as these are sort of a baseline, 11-screen consent interface
-- first of all, that makes it easier to do inoperability analysis because you can start
to see, structurally, if someone inserts a weird piece of information or requirement
that hurts later integration of the data, but it also gives the patient communities
a vocabulary for what kinds of studies they want to be involved in, and that’s a vocabulary
that’s been very difficult to create using traditional legal text methods.
If you can actually say, “These icons,” right?
“These restrictions or freedoms or kinds of data that we are comfortable with, this
is what we want as a community” -- it can be a very powerful way to start signaling
out to researchers, so you can get some of that matching done ahead of time.
And one of the reasons that I wanted to bring this up was Jason’s point earlier about
failed relationships being sort of something that are really important to anticipate, and
we’ve had -- I see.
We’ve had a tough relationship with a patient advocacy group, and the problem was that we
were going too slow, right?
We were developing sort of on a research timeline, you know, going through a design process in
a way to build something we thought would be much more effective for them.
But it took so long that they just got really angry.
Really, really emotionally angry with us, and we didn’t hear that until so late in
the process that it was really hard to pull it out.
So, my hope is that there’s real benefit to treating consent as a process, not sort
of a static moment where you say yes or no to a document, but the reality is, when you
design a really large study, you have to have that cohort be analyzable; the data need to
be distributable so you can verify the sorts of predictive models that get built on it,
but you can start to create signals so that someone who is going through the process understands
that it matches their individual values, and you can create a vocabulary so that communities
can declare their values in advance.
I think that’s going to help build relationships that fit because the sorts of uses that we
make of data at Sage really require fairly broad, long-term consent because we want to
build predictive models, file those predictive models with publishers, and have the data
that led to the conclusions that were published be replicatable and re-analyzable.
So, it’s really hard to offer people the opportunity to come back and delete their
data or delete their consent and be consistent with the scientific process that we’re taking
forward.
So, it’s really important for us to be able to connect with communities and know at the
beginning that the values that they have match with the scientific processes that we have
because there’s implicit values buried in the ways that certain types of science get
done, specially large-scale data science, that are not going to be comfortable to all
communities, and I think it will help all of us if we can do some of that impedance-matching
up front.
And I think that I have, like -- what?
One minute left or am I done?
[inaudible]
John Wilbanks: Okay, so -- just the last piece of this, which
is that we think a lot of people are going to do these sorts of app.-based, longitudinal,
observational studies because they’re easy, right?
We’re standing up, too, and we don’t have any funding.
That’s how cheap it is to roll this sort of stuff out and we’re going to be making
all the source code, all the web-services, all these things available to other people
who would like to run such kinds of studies, but the thumb that we’re going to put on
the scale -- the tacks we’re going to put on the scale -- is that no one’s going to
be able to use the architecture if they don’t return all the data to the participant on
demand in an exportable format.
All right, so we’re making this sort of unitary demands on the cohort from a science
perspective, but the deal is, if you want that, you have to give complete access to
the data back to the participant and not just as a downloadable tar ball, right?
What’s more important, you have to be able to push the data to a third party, like PEER
[spelled phonetically] or some of the other platforms we’ve heard where you can manage
your data as a participant once it’s gotten outside of that clinical research context.
I’ll stop there.
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