New Clinical Research Paradigms

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16 Φεβ 2014 (πριν από 3 χρόνια και 3 μήνες)

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March 5, 2013: I. Sim

What Next for Health and Research Informatics?

Epi 206


Medical Informatics

Ida Sim, MD, PhD


March 5, 2013



Division of General Internal Medicine, and

Center for Clinical and Translational Informatics

UCSF

New Clinical Research Paradigms

Copyright Ida Sim, 2013. All federal and state rights reserved for all original material presented in this course
through any medium, including lecture or print.

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Interim Summary


Health system is highly fragmented, information systems
are patchwork and support transactions rather than
knowledge work


Computing challenges include


naming data (e.g., ICD
-
9
vs

SNOMED)


decision support (e.g., rules, probabilistic reasoning, different kinds of
decision and reasoning problems that need solving, NLP)


workflow integration impeded by closed/siloed systems


EHR adoption is increasing (driven by Meaningful Use
payments), but CDSS adoption is low, and clinical
research informatics usage is early


Health care and research are poised for disruption by
digital technologies


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Outline


Plateau of Productivity: The Learning
Health(care) Syste
m


The Uneven Present


new models of care


the Digital Divide


The Uneven Future for Research


Web X.0 research paradigms

March 12, 2013:
I. Sim

What Next?

Epi 206


Medical Informatics

Ideal Health (Care) System


Because we don’t already know how to do
everything…


A “learning health(care) system”



that is designed to generate and apply the best
evidence for the collaborative health care choices
of each patient and provider; to drive the process
of discovery as a natural outgrowth of patient
care


(IOM Evidence
-
Based Medicine
Roundtable)


Friedman, et al. Achieving a Nationwide Learning Health
System. Sci Transl Med 2010; 2(57):57cm29

March 12, 2013:
I. Sim

What Next?

Epi 206


Medical Informatics

What Learning Occurs Now?


Studies are expensive, difficult to conduct, 30
-
40% of studies
never accrue enough patients


Studies take years to answer limited questions in limited
populations


Study designs and results are heterogenous, limiting ability to
pool findings or make summary interpretations


Research questions don’t address combination treatments
(e.g., ACEI and amlodipine)


Research questions often don't answer front
-
line clinical needs


little data on mid
-

to long
-
term effectiveness of
antidepressants


Overall lack of relevance, generalizability, and sustainability


Moss, et al. NEJM 2011; 364(9):789
-
761

Crowley, et al. JAMA 2004; 291(9):1120
-
6 etc
.

March 12, 2013:
I. Sim

What Next?

Epi 206


Medical Informatics

What Learning is Needed?


Population
-
level efficacy and effectiveness


for endpoints, not
only intermediate
outcomes


for patient
-
centered outcomes (symptoms, side effects)


Predictive precision (
e.g., depression
, asthma for
this

patient)


model
-
based learning of biophysical medicine


Therapeutic precision (best therapy for
this

patient)


informed by, but not limited to, genomic info


learning from experience (e.g., outcomes research)


How to promote and sustain behavior change


What are prevalence, natural
hx
, etc. even of rare diseases?


How to enable patients, families, communities, and clinicians to
maintain wellness and manage chronic illness together?


etc. etc
.

Five Rings of Human Health

Schatz, BR, et al. Healthcare Infrastructure: Health Systems for Individuals
and Populations. Springer, 2013.

The Uneven Future


Tech, biomedical, and macro factors driving a
radically different health(care) future


Eric Topol:
Creative Destruction of Medicine

and
TED
talk


Personalization of consumer experience will be
expected in health too


Goal is a “learning system” based on big data


Puts premium on intelligent data analysis of open
and disparate data


New research paradigms open up


But first, where is the Uneven Present?

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Outline


Plateau of Productivity: The Learning
Health(care) Syste
m


The Uneven Present


new models of care


the Digital Divide


The Uneven Future for Research

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Web X.0


Web 1.0: web of
links

to static information with simple
links between them


e.g., Wikipedia, NYTimes.com
1


Web 2.0:
people

are as important as computers in
the network


Facebook, Twitter, Google +, Instagram, Tumblr…


Web 3.0 (Semantic Web)


each
data
item is

tagged


with ontology terms so computer
can

understand


everything on the web


I.e., the contents of HTML

buckets


are standardized, using
RDF (Resource Description Framework), OWL (Web
Ontology Language), etc.


Web +1 web of
things


1
except http://www.nytimes.com/projects/2012/snow
-
fall/?hp#/?part=tunnel
-
creek

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Web 2.0 Principles


User
-
generated content


Harness power/wisdom of crowds


Openness


Architecture of participation


Niche markets

(P. Anderson, What is Web 2.0? JISC Tech and Standards Watch, Feb 2007)

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

User
-
Generated Content


Anyone anywhere is a source of content


YouTube, Flickr, Wikipedia, Instagram, Tumblr, citizen
journalism, blogs, e.g.


http://PatientsLikeMe.com/


http://www.ganfyd.org/index.php?title=Main_Page



Exists in parallel with Web 1.0 hierarchical
information sources


NIH MedlinePlus


WebMD.com


February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Power/Wisdom of Crowds


Tapping into distributed intelligence


wikipedia (as accurate as Encyclopedia Britannica)


www.intrade.com


stock market



Google Flu
,
HealthMap


Use distributed machine and people resources


parallel computing for cheap:
Einstein@home



FoldIt

for protein folding


Crowdsourcing:


633,200 questions in health

http://wiki.answers.com/Q/FAQ/431



February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Openness


Dimensions of openness


open source code: community improvement (e.g., VistA VA
EHR system)


open access: no restrictions on use or distribution of content


open participation: everyone can participate


communal management, flat hierarchies, emergent decisions


Allows

mash
-
ups


of freed data

-
e.g.,
Community Health Data Initiative


-
http://www.googlelittrips.com/GoogleLit/Home.html

for Aeneid,
Grapes of Wrath, user
-
generated road trips...


February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Architecture of Participation


Network externalities:

the service automatically gets
better the more people use it


e.g.,


fax machines, cell phones...the more the better


Google search:
the more

link paths


people tread, the richer the
data for the Google search algorithm


Amazon book ratings, Netflix ratings


How important is anonymity for this in healthcare?


http://www.curetogether.com/



http://whoissick.org/sickness/



better epi data if everyone contributed to public health data


1
-
3% refuse to share clinical data for research


February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Niche Markets



The web


is unlimited resource


can service even extremely small market niches


Shape of the web: the

long tail



where traditional focus is

with infinitely long tail, majority of action is here

market niche/things being done

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Niche Markets in Health


Rare diseases


PatientsLikeMe


Geographic, ethnic, other niches


Russian
-
speaking boy scouts with ADHD in rural
Montana


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Online Care


Cognitive behavioral therapy


for sleep:
www.shuti.net


15 mins. of Cognitive Bias Modification vs. hours of talk
therapy



all it requires is sitting in front of a computer and using a program that subtly
alters harmful thought patterns


(Economist, Mar 5, 2011, p. 85)


Counseling


http://www.liveperson.com/experts/professional
-
counseling/


Virtual MD visits include live video chat and instant
messaging (defunct now)


https://platform.hellohealth.com/PublicPortalServlet/DoctorsList.jsp



Non
-
Traditional Health Players


CVS Minute Clinics


ZocDoc

Open Table for booking doctors


Castlight

price transparency for expenditures


Aetna bought iTriage, part of new Consumer
Platform


AT&T ForHealth platform


@Walmart, Cisco, Intel …



March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Outline


Plateau of Productivity: The Learning
Health(care) System


The Uneven Present


new models of care


the Digital Divide


The Uneven Future for Research


Huge growth in
Internet use across
all segments


Race/ethnic and age
divide on usage


interaction with
income and education

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Action is in mobile


Majority of Internet
users access via
mobile


No race/ethnic
difference

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics


Mobile is preferred
or
only

way of
getting online by
more


youth


minorities


low income

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics


About a third of
mobile users
overall access
health information


More use in


youth


minorities


higher income


higher education

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Digital Divide Still Exists


M
inorities with higher cell usage, more cell
-
only households, more social computing


Language is strong predicator


foreign
-
born Latinos much lower use of Internet,
English
-
speaking Latinos equal to whites


Also health literacy


low health literacy predicts lower e
-
health use
(Sakar, J Health Commun, 2010)


Don'
t automatically apply old
assumptions/data from the

real


world to the
virtual world


February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Summary of the Present


Lots of new models of care, new players


Social computing coming into play


Digital divide exists in non
-
traditional ways


is
increasingly about
how

technology is used, not
whether

it is available


overall trend to going online via mobile not
desktop


Uneven availability and uptake


Internet and broadband use lower in elderly, rural,
low income, and chronically ill


February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Outline


Plateau of Productivity: The Learning
Health(care) System


The Uneven Present


new models of care


the Digital Divide


The Uneven Future for Research

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Web X.0


Web 1.0: web of
links

to static information with simple
links between them


e.g., Wikipedia, NYTimes.com


Web 2.0:
people

are as important as computers in
the network


Facebook, Twitter, Google +…


Web 3.0 (Semantic Web)


each
data
item is

tagged


with ontology terms so computer
can

understand


everything on the web


I.e., the contents of HTML

buckets


are standardized, using
RDF (Resource Description Framework), OWL (Web
Ontology Language), etc.


Web +1 web of
things


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Web

1.0 Research


Websites that collect information, deliver video, etc.


U
-
Can
-
Poop
-
Too Study


http://ucp2.bht.virginia.edu/interest/study


Stop Smoking


https://www.stopsmoking.ucsf.edu/



"Web 1.0" Resources at UCSF


Building websites, with templates, etc.


http://drupal.ucsf.edu/


Distributed trials


Mytrus
: e
-
consent, randomization, online data
collection


Mobile data collection


RedCAP, Qualtrics, etc., see
http://ctsi.mobiledata.sgizmo.com/s3

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Development Decisions


The “specs” (specifications)


what is your system supposed to do? for whom?


what specific functions will it have?


do use case scenarios (step
-
by
-
step, storyboards, etc)


Basic technical choices



form factor

: kiosk, desktop, laptop, notebook, tablet, phone…


operating system (e.g., Mac vs PC, or Android vs iPhone vs mobile
web)


check browser and platform
usage statistics


Find a developer


internal: UCSF Mobile Services or
Telemedicine


external: contact Tuhin.Sinha@ucsf.edu in ITA for referrals and
standard contracts


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Agile Design


Traditional approach


design a website or system; pilot it on a few users, improve it;
run RCT; analyze data; publish (over 2
-
3 years)


Agile design approach


user interaction design


rapid cycle iteration with qualitative and quantitative user
studies


Why wait till end of RCT to find out that

the system


didn

t
work or wasn

t used, and have little idea why?



user engagement a critical problem for digital health
interventions, need to explore methods

User Interaction Design


The practice of designing interactive digital products


more than user interface, is user experience, ie how iPhone
feels different than Android


User interaction design expertise


http://www.coroflot.com/public/individual_search_results.asp?k
eywords


contact Beth Berrean
BerreanB@MEDSCH.UCSF.EDU
,
UCSF
Mobile Services


Participatory design


involve your users in design right from the beginning


e.g., test out different
data visualizations
,
http://www.visualizing.org/


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Rapid Cycle Field Testing


Qualitative


surveys, interviews, video recordings, “talk
-
aloud
protocols”


Quantitative


user analytics


track app launches, clicks, dwells, scrolls, links to web and
back…e.g., Flurry.com


Google launched 450 search engine improvements in 2007,
each one tested rigorously

through real
-
time user analytics


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Web 2.0 Research


Games and simulation for health


http://www.gamesforhealth.org/
,
http://healthcaregames.wisc.edu/



http://secondlife.com/?v=1.1


PatientsLikeMe.com on lithium for ALS


observational study prompted by a small Italian study,
negative results
published

in Nature Biotech


Crowdscience


http://diygenomics.org/

correlating personal genome with
outcomes of personal interest (e.g,. empathy)


mining Twitter, GPS locations, online social status for
predictors of health
, real
-
time
GermTracker



Ethics and informed consent are
evolving




February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

The Internet of Things


http://www.youtube.com/watch?v=sfEbMV295Kk

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Health Things

February 26, 2013: I. Sim

What Next?

Epi 206


Medical Informatics


FitBit
: steps, distance, calories burned


Sleep:
Zeo
, SmartAlarm app


AliveCor ECG


Wearable sensors


Corventis Piix: holter sticker


Sensing Tattoos

for blood glucose, oxygen, sodium levels


Nike+ shoe, Smartex clothes


Mood sensors:


Affectiva

skin impedance, voice stress analysis


Xpression

200 millisecond long acoustic snapshots for voice stress
analysis
(
calms, happy, sad, angry, or anxious/frightened)


Embedded, distributed sensors


in the home:
Kaiser Garfield Innovation Center



March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

24/7/anywhere/everyone

Care/Research


Small, cheap, highly networked devices, distributed
everywhere doing everything (
everyware
)


e.g.,
GreenGoose

tags


Near
-
patient testing


Ucheck

checking urinalysis via your iPhone and camera


iBGStar

glucometer


Environmental mapping of symptoms


asthmamd.com

mapping of PEFR of thousands of users in
real
-
time during Icelandic volcanic explosion

Web n.0 Research


Asthmapolis

and their SpiroScout GPS
-
wifi enabled
inhaler


allows you to "quantify the burden of asthma in a community,
explore environmental exposures and how they correlate
with asthma symptoms, and identify spatial and temporal
patterns of disease."


Health eHeart

(Jeff Olguin, Mark Pletcher, UCSF)


a virtual Framingham for cardiovascular research


CalIT2 projects


Quantified Self


overview:
http://www.economist.com/node/21548493








March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

Larry Smarr story


UCSD computer science professor


overweight, arrived in SD in 2000


Quantified his four "pillars of health" (
TicTrac

displays together)


nutrition: can use
LoseIt
, many others


exercise: can use
FitBit
,
FuelBand
, etc.


stress management: GPS4Soul,
etc


sleep:
Zeo
, Up band,
SmartAlarm
, etc.


Biomarkers


from consumer labs, e.g.,
www.yourfuturehealth.com


February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Larry
Smarr

story

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Larry
Smarr

story


Lost weight, exercised, slept better, optimized
omega
-
3, DHA scores, AA/EPA ratio, TG/HDL,
etc.


But CRP was high, and had suddenly doubled
over a year


presented with acute diverticulitis, took antibiotics


CRP came down, but was still higher than normal


carotid artery plaques growing despite optimal
lipids and "anti
-
inflammatory diet"



Quantified his stool



February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

Larry
Smarr

story

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics


Stool
lactoferrin

correlated with
serum CRP levels


and IBD?


Got scoped


inflammation seen,
doc said it wasn't IBD


Rescoped

and
bx'ed


Crohns
, rare late
onset (5% are > 60y)





Larry
Smarr

story


Genomics


23andMe

SNP profile


had 80% increased risk of
Crohn's

with rs1004819
SNP37 located in IL
-
23 receptor gene


Stool flora and
microbiome


he had much lower stool flora diversity, took long
time to replenish after antibiotics for diverticulitis


now exploring stool
microbiome

(see e.g.,
uBiome
) correlating stool
metagenomics

with
clinical
Crohn's


February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

February 26, 2013: I. Sim

Research Informatics

Epi 206


Medical Informatics

The point of this article is that the combination of trend
-
revealing
graphs of time series of individual biochemical markers, with
population
-
wide comparisons to people with different health
outcomes, is transforming biomedical research, and ultimately
clinical care, into an entirely new paradigm. In this new world, we
become personally responsible for monitoring our bodies,
noticing deviations from trends, and making appropriate
changes. Use of this paradigm will allow us to avoid many of
today’s chronic disease states. In coming decades, the new
model will be “maintenance of wellness” rather than “treatment of
chronic illness.”

http://lsmarr.calit2.net/repository/092811_Special_Letter,_Smarr.final.pdf

Summary: New Research Paradigms


A “flat” world, blending health and healthcare
unbounded by place or time


Lots of data, lots of things, everyone is “in”


many non
-
traditional health players


Challenges will be


aggregating smaller data into Big Data (and back
into personalized small data)


analyzing Big Data in appropriate clinical, social,
environmental, etc. context


drawing scientific conclusions, showing validity


March 12, 2013: I. Sim

What Next?

Epi 206


Medical Informatics

February 5, 2013: I. Sim

Overview

Medical Informatics

Next Class


Research
methodology in
the Digital Age