Health Analytics in
Canada – A Blueprint
for Gaining Clinical
Buy-in and Creating
Value from the Bottom
up
eHealth 2013 Conference
Presented by:
Alex J Mair, Director, Emerging
Technology Group
May 27, 2013
Faculty/Presenter Disclosure
•
Presenter: Alex J Mair
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Relationships with commercial interests:
—
Nothing to disclose
2013 Canada Health Infoway Inc.
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Agenda
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Overview of Health Analytics Blueprint
Health Analytics Key Concepts
Opportunities and Challenges
Roadmap for Success
2013 Canada Health Infoway Inc.
Presented by
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The Infoway Blueprint - “Key Enabler”
-Used to define and scope over 353 EHR-related projects across
Canada
-Representation of the conceptual Blueprint for interoperable EHR
Solutions in Canada
-Jurisdictions use this Blueprint and underlying concepts to adapted
to their specific implementation of EHR solutions
-Concept of Service Oriented Architecture (SOA)
-Registries, Domain Repositories, HIAL, DW
-Privacy, security, change management implications for it’s use
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Health Analytics Blueprint – Extends Infoway
Blueprints
•
Depicts Health Analytics at systemic level:
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Across point-of-service applications (EMR, CIS, etc.), care
settings and organizations
With bottom up emphasis on serving clinician, patient and
governor needs
Support for all categories of use (clinical programs, health
system performance, health of public and research)
Support for all levels of use (individual, organizational,
regional, jurisdictional, across disciplines or specialties, and
pan-Canadian)
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HealthRetrospective,
Analytics
- Future
Ad-hoc,
preformatted
reports, State Architecture
sophisticated
EventPredictive
based nearAnalytics
real real-time
and
business
rules
that
go to
against
an the end
indented
inform
analytics,
provided
in context,
close
forecasting
future
values,
or
ODS
(operational
datastore)
or
user
about
a
specific
to near real-time
be daily,
events by (could
calculating
the situation.
limited
dataset.
(on
a regular basis).
probability
of occurrence.
weekly,
monthly),
Example:
Business
rule
for anthe that a
Example:
Alert that
predicts
Example:
determining
Example:
a search
or
query
for
assessment
plan
for
a
patient
which
probability
of readmission
specific
group
of and
individuals
pointing
out
an
increasing
trend
of
is triggered
when
several
conditions
feeding
it
back
to
clinicians
for
with
heart
failure
appear to
hospitalization
due
to congestive
or events
for who
that
patient.
An
at riskoccur
patients
are
showing
have
a higher
hospitalization
failure.
alert characteristics
orheart
notification
to
provider
of
chronic
rate
– individuals who
(e.g..diseases,
self-care
recommendations
to reside
prior
to discharge so
in
rural
areas
and
live
more
PHR,
notification
that
they can to
putprovider
in place
than
200 measures.
km from
their primary
depending
on adherence
to care
preventative
plan.) care provider.
Predictive
Analytics
High Precision
Analytics
Aggregate
Transactional
(Near realtime)
Sourcing and querying data Unstructured
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Health Analytics Future State Key Concept Linkage of Data Sources
Clinical data
Administrative
(HR, Finance)
Research data
Islands of information
Claims data
Provider
Disease
Filters for context and
metadata (disease, condition,
risk factor)
Patient
Condition
Context
Program/population data
Information contextualized into knowledge
Senior decision maker
Researcher
Data analyst
Health system
manager
Health system planner
Patient /
client
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Quality improvement Lead
Clinician / provider
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Information Value Chain
Future
Capability
Present
To predictive
and collaborative
prevention, monitoring
and management of
population health
Digitization, growing
network of EHR / EMRs
based around patient
centric longitudinal
records
Past
From paper based,
unstructured, silo’d data,
and isolated decision
making
Clinical and Business Value to Health System
Health Analytics Blueprint value proposition is supporting our stakeholders make the transition to the more mature
state where information value increases significantly
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Health Analytics – Bottom up design
Reporting
• Reports
• Retrospective
Analyze
• Score
Carding
• Local
Monitor &
Forecast
• Best
Practices
• Measure
Outcome
Plan &
Predict
• Alerts
• Quality
Improvements
Advise &
Optimize
• CDS Options
• Patient &
Provider
•
Standards,
Outcome,
Contextualized,
Privacy enhanced,
Aggregation
based
processes
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Advice/
reminders to
patients,
Alerts, CDS
analytics, quality
improvement
analytics to
providers
Performance
management
dashbaord/
alerts to
governors
De-identified
data for
researchers
Use Case - EMR Primary Care Analytics for use in Diabetes Management - Collect once, create new
2013 Canada
Health
Infoway
value and use many times across categories
and
levels
of Inc.
use.
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Health Analytics Example
Benefits
Use
Capability
Data
Predictive Clinical Analytics
uses data in data warehouse
to score patients based on
proven risk models for
patient.
EMR data extract provides
data daily to Data
Warehouse
Providers are able to interact
directly with CDS system
from their EMR with patients
to assess risks, determine
appropriate interventions, to
reduce risks to patients
2013 Canada Health Infoway Inc.
Patients see impacts of realtime interaction with data:
• Re-admissions are reduced
• Negative outcomes
avoided
• Evidence from analytics
further informs other
components of the system
best practices, quality
improvement effectiveness
or outcomes (programs,
administrators).
Kaiser Permanente
Primary Care CDS
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The time is right
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EHR & EMR investments
Health industry focus on information, driven from
bottom up
Privacy and security, standards, governance as
enablers
Information management concepts and
frameworks (data quality, master data, metadata)
Data model and dictionary, health indicators
Enterprise architecture, SOA, event driven
architecture
Solutions moving from retro-spective to
predictive
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Analytics in Health Care
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Lack of understanding of how analytics can
improve business
Management focus or attention
Internal Skills
Data Availability
Culture of Sharing data
Data Stewardship
Executive Sponsorship
Concerns with data
Lack of understanding of benefits
Case for Change
Don’t know where to start
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But it won’t be easy ….
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Culture, governance dialogue
Health legislation & policy
Stakeholder engagement and change
management
Information governance, technology,
architecture and standards alignment
Data acquisition and data quality
Technologies and stakeholders still need to
catch up
HIT/PoS systems & Data Warehousing /
Business Intelligence (DW/BI) legacy
investments
Enterprise architecture, SOA and DW/BI
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Health Analytics …. A Roadmap for Success
Build Capacity
& Capability
• Analytics strategy &
roadmap
• Plan frameworks &
interim states
• Plan & build capacity
• Establish governance
• Communications &
education
• Roll out and
Experimentation
Deploy Frameworks
& Prove Concepts
• Build frameworks
• Governance
• Evolve and build
architecture and
capacity
• Change management
and benefits
• Experiment and
prove solutions
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Build, Deploy
And Replicate
• Build and optimize
capabilities
• Governance
• Change
management
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Emerging technology resource documents:
https://www.infoway-inforoute.ca/index.php/resources/presentations/emerging-technology
Discussion & questions?
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