Cochrane PICO: Using linked data technologies for evidence...
Transcript of Cochrane PICO: Using linked data technologies for evidence...
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Trusted evidence.Informed decisions.Better health.
Cochrane PICO: Using linked data technologies for evidence curation
Chris MavergamesHead of Informatics & Knowledge Management/Chief Information OfficerCochrane Central Executive
UCL, July 2017
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This talk is about
how …
• finding evidence
• synthesising evidence
• disseminating evidence
… are changing
and what it means for you.
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Some key concepts
• Metadata curation
• Linked Data
• Data re-use and provenance
• Role of machine learning and
crowdsourcing
• Living systematic reviews
• Beyond the PDF and publications
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Credit: Nova Spivack
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The present situation
• Current evidence processes very manual
• Machines and machine/human not optimally
utilised
• Organising human effort not optimised
• Tools not yet fit for purpose and connected
• Data not "smart”
• Outputs not optimised for use (by humans and
machines) and impact
• Solving “today's problems"
• Preparing for tomorrow's challenges
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Direction of travel
• Less manual work, more focus on data curation,
synthesis, and “reflection”
• Structured, “PICO-fied”/computable data
• Audit trails, provenance, re-useable data
• Machine/crowd assistance
• New models of participation
• Tools fit for purpose and integrated
• More evidence synthesized; Outputs have greater
impact
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The emerging "ecosystem"People + Process + Technology
optimized for the task
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Cochrane operational projects
Changing how we store & manage our content
Linked dataPICO ontology
PICO annotation
Changing the review production process
Evidence pipelineCentralised search
New production models
Increasing production capacity via new models of
community participation
Crowd sourcingTask exchange
Improving production efficiency using
technology
Author support toolsText mining
Machine learning
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Improve usability & utility of Cochrane data
Production efficiency
Quality & standardisation
Revenue protection & generation
Improve contributor engagement & experience
Objectives
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Getting outside the
review/article “container“
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Cochrane Reviews
• Have always been electronic
• Summary of a research project, not really an article
(actually a database of results)
• PICO framework (but not consistently structured)
• Follow standard process
• Many of the key components buried in the document:
Forest plots, Risk of Bias assessments, etc.
• Continuously updated when new studies are reported
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PICO
Population
Intervention
Comparison
Outcome
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Ilkka Kunnamo
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Document view
XML <?xml version="1.0" encoding="ISO-8859-1" standalone="no"?>
<COCHRANE_REVIEW DESCRIPTION="For publication"
DOI="10.1002/14651858.CD008440" GROUP_ID="HIV"
ID="589309120202025823" MERGED_FROM=""
MODIFIED="2011-05-06 12:29:46 +0100"
MODIFIED_BY="Rachel Marshall" REVIEW_NO=""
REVMAN_SUB_VERSION="5.1.1" REVMAN_VERSION="5"
SPLIT_FROM="" STAGE="R" STATUS="A"
TYPE="INTERVENTION" VERSION_NO="2.0">........
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Key components
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Linked data
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The “age of pointing at things“- h/t Tom Coates, 2005:
ttp://www.plasticbag.org/archives/2005/04/the_age_of_pointatthings/
The realization [behind creation of the [Internet] was, "It isn't the cables, it is the computers which are interesting".
[World Wide Web] the realization was "It isn't the computers, but the documents which are interesting". Now you could browse around a sea of documents without having to worry about which computer they were stored on.
Now, people are making another mental move. There is realization now, "It's not the documents, it is the things they are about which are important”.
-Tim Berners-Lee, inventor of the World Wide Web
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“The problem is not information
overload. It‘s filter failure.“
- Clay Shirky
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Current web = Web of
documents
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Docs are linked not data (things) in docs
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Machines aren‘t good at reading web
pages and documents
• Data on the web is meant for human
consumption
• Machines need the data to be structured
• Then, information can be more easily
shared within and across datasets and web
pages
• Interfaces and APIs can be built to allow
better (and programmatic) access
• The article could evolve into an interface
onto a “web of data“
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Reviews, studies, references,
analyses
thing thingthing
thing
thing
thing
P
P
P
P
P
P
I
II
I
I
I
C
C
C
C
C
C
O
O
O
O
O
O
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Graphs of knowledge
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drug
condition
sideEffect CR:ID#
CR:ID#
CR:ID#
study
study
study
study
study
study
studystudy
study
Start anywhere, go anywhere
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Chart: Linn Brandt/
DECIDE Project
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Access points
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Access points
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Linked Open Data
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…breathe…
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Linked Data ProjectPICO Annotation and PICOfinder
http://linkeddata.cochrane.org
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• Enrich our content and data with metadata using controlled
vocabularies (SNOMED CT, etc.)
• Construct knowledge models and structures (ontologies)
that will allow re-use of this metadata (annotations) for
both downstream (dissemination) and upstream
(production) use
• Become more interoperable with other projects, products,
datasets, and systems
• Improve production (“smarter data”) and dissemination of
evidence (“unlocking the evidence”)
• http://linkeddata.cochrane.org
Linked Data: Overarching goals
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Controlled terminology sets
(vocabularies)
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Existing Cochrane databases
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A new Cochrane PICO database
PICO annotations:
- Reviews (question, studies,
analyses)
- CRS/CENTRAL
- Data sets (Covidence, EPPI-
R)
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Each review and included study receives its own PICO
PICO Annotator: Annotation of PICO’s
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Ensuring annotated PICO Data is fit for purpose and correct
QA Dashboard: Ensuring High Quality PICO
Data
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Curating the Cochrane vocabularies
Linked Data Editor
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Understanding what a term means and where it’s used
Data Discovery
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Flexible search for combinations of Population, Intervention, Outcome
Exploring PICO
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PICO AnnotatorAnnotating Cochrane Review content
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PICOfinder demo interfaceExploring, filtering, and visualizing
Cochrane evidence using PICO
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PICOfinder demo user interface
• Allow exploration of Cochrane content
(Reviews, studies, forest plots, etc)
using PICO
• Allow display of selected portions of
Cochrane content in a flexible manner
• Allow linkage to relevant content
produced by others
• Foundation for future Cochrane
Library interface and derivative
products
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https://data.cochrane.org/pico-finder
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Linking to other resources
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Adverse effects of drugs – from LAERTES
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Adverse effects of drugs – from LAERTES
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Linking to
adverse effects
Lisinopril RxNorm
ID#....
Laertes data set on
AEs
Lisinopril RxNorm ####
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Integrating with external Apps
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“Enabling” technology
• New interfaces and products for Cochrane evidence
such as:
• Dynamically-generated topic portals and interfaces
• Improved discoverability
• Comparator tools
• APIs for third-party systems and data feeds
• Facilitating:
• Data re-use and repurposing
• Review production efficiency and intelligence
• Living sys reviews into living guidelines
• Creation of standards (PICO) for interoperability
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…refresh...
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Project TransformPeople + Process + Technology converge
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Project Transform
4 components:
• Evidence Pipeline: uses machine learning and text
mining to make study identification more efficient and
semi-automated – including Centralized Search
Service
• Getting Involved: uses crowdsourcing to get more
people involved in tasks (URL coming soon!)
• Task Exchange: Platform for brokering tasks
(taskexchange.cochrane.org)
• Production Models: New models of organising human
effort in review production
• More info at cochrane.org/transform
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CENTRAL
PubMed
Embase
Clinical
Trials.gov
LILACs
Korea
Med
CINAHL
The CSS is about
increasing the number
of sources searched in
the way that Embase is
searched
Candidate sources:
ClinicalTrials.gov,
CINAHL, LILACS, and
Korea Med
The CSS in close partnership
with Project Transform’s Pipeline
and Getting Involved
components
Centralized Search Service
(CSS)
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LILACs
Why?
Endgame: Just search CENTRAL
Time saved searching
Time saved screening
Reduction in duplication of effort
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http://community.cochrane.org/tools/project-coordination-and-support/transform
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Using crowdsourcing to perform complex annotations as a series of micro-tasks
CROWD-Based Annotation
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Using machine learning to identify and filter evidence prospectively
Machine Curation
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The wider contextRemaining relevant in an expanding
marketplace of evidence
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"Next generation"
Cochrane?• Big data
• “Diverse” data
– IPD (Individual Patient Data)
– ~omics
– Device, systems
– Data from different study designs
• Activity to date:
– Meetings
– Various conversations happening but nothing definitive yet
– Discussions mainly what role Cochrane should play
– Ida Sim Cochrane lecture in Vienna
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"Next generation" Cochrane• How can we move towards…
• “living” systematic reviews
• and dynamic curation of evidence in real-time
…that can incorporate methods and data from "diverse"
sources?
• Vivli.org
– Project to build a clinical trial data sharing platform
– Will include IPD, CSRs, and vision is eventually imaging data,
-omics and other data sources
– Analytical tools, mechanisms for de-identification, privacy
– Launching next year
• OpenTrials
• Cochrane has a role to play (lead, partner, or other?)
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Insert iodine screenshot
"The Yelp of medicine is here" : /
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"The Yelp of medicine is here" : /
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...nearly there...
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Summary
• People + Process + Technology are converging in
new and innovative ways to aid evidence synthesis
• Ramping up of the machines, platforms, and
structured, linked data (tech)
• Change management: people will need to adapt
(process)
• Helps Cochrane and other evidence producers to
"scale"
• We can produce more high-quality evidence for
health care decision making
• So systematic review efforts can remain competitive
and relevant
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Demo: Cochrane linked data tools + Q & A