Health Analytics in Canada – A Blueprint for Gaining Clinical Buy-in and Creating Value from the...

Health Analytics in Canada – A Blueprint for Gaining Clinical Buy-in and Creating Value from the Bottom up

Alex J Mair, Director, Emerging Technology GroupPresented by:eHealth 2013 Conference May 27, 2013

Faculty/Presenter Disclosure

• Presenter: Alex J Mair

• Relationships with commercial interests:— Nothing to disclose

22013 Canada Health Infoway Inc.

Presented by

Agenda

• Overview of Health Analytics Blueprint• Health Analytics Key Concepts• Opportunities and Challenges• Roadmap for Success


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


Health Analytics Blueprint – Extends Infoway Blueprints• Depicts Health Analytics at systemic level:

• 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)



Health Analytics - Future State Architecture

Sourcing and querying data

High Precision Analytics

Transactional (Near realtime)

Aggregate

PredictiveAnalytics

Unstructured

6

Predictive Analytics and forecasting future values, or

events by calculating the probability of occurrence.

Example: Alert that predicts the probability of readmission and feeding it back to clinicians for

at risk patients who are showing characteristics of chronic

diseases, prior to discharge so that they can put in place preventative measures.

Retrospective, sophisticated

analytics, provided in context, close to near real-time (could be daily,

weekly, monthly),

Example: a search or query for pointing out an increasing trend of hospitalization due to congestive

heart failure.

Ad-hoc, preformatted reports, indented to inform the end

user about a specific situation. (on a regular basis).

Example: determining that a specific group of individuals with heart failure appear to

have a higher hospitalization rate – individuals who reside in rural areas and live more than 200 km from their primary care

provider.

Event based near real real-time business rules that go against an

ODS (operational datastore) or limited dataset.

Example: Business rule for an assessment plan for a patient which

is triggered when several conditions or events occur for that patient. An alert or notification to

provider (e.g.. self-care recommendations to PHR,

notification to provider depending on adherence to care plan.)


Research data

Researcher

Health system manager

Senior decision maker

Quality improvement Lead

Administrative (HR, Finance)

Clinical data

Program/population dataClaims data

Islands of information

Information contextualized into knowledge

Context

Pati

ent

Pro

vid

er

Dis

ease

Con

dit

ion

Filters for context and metadata (disease, condition,risk factor)

Health system plannerData analyst

Health Analytics Future State Key Concept - Linkage of Data Sources

Clinician / provider

Patient / client

7


Information Value Chain

Clinical and Business Value to Health System

Cap

abili

ty

PresentDigitization, growing network of EHR / EMRs based around patient centric longitudinal records

PastFrom paper based, unstructured, silo’d data, and isolated decision making

To predictiveand collaborativeprevention, monitoring and management of population health

Future

8Health Analytics Blueprint value proposition is supporting our stakeholders make the transition to the more mature state where information value increases significantly

Health Analytics Blueprint value proposition is supporting our stakeholders make the transition to the more mature state where information value increases significantly 8


Health Analytics – Bottom up design• CDS Options• Patient &

Provider

Advise & Optimize

• Alerts • Quality

Improve-ments

Plan & Predict

• Best Practices

• Measure Outcome

Monitor & Forecast

• Score Carding

• LocalAnalyze

• Reports• Retro-

spectiveReporting

• Advice/ reminders to patients,

• Alerts, CDS analytics, quality improvement analytics to providers

• Performance management dashbaord/ alerts to governors

• De-identified data for researchers

Standards,Outcome, Contextualized,Privacy enhanced,Aggregationbased processes

9Use Case - EMR Primary Care Analytics for use in Diabetes Management - Collect once, create new value and use many times across categories and levels of use.

Use Case - EMR Primary Care Analytics for use in Diabetes Management - Collect once, create new value and use many times across categories and levels of use.

Predictive Clinical Analytics uses data in data warehouse to score patients based on proven risk models for patient.

Patients see impacts of real-time 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).

Data

Use

Benefits

CapabilityProviders are able to interact directly with CDS system from their EMR with patients to assess risks, determine appropriate interventions, to reduce risks to patients

Kaiser PermanentePrimary Care CDS

EMR data extract provides data daily to Data Warehouse

Health Analytics Example


The time is right• 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


Analytics in Health Care• 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


But it won’t be easy ….• 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/BI132013 Canada Health Infoway Inc.

Build Capacity & Capability

Deploy Frameworks& Prove Concepts

Build, DeployAnd Replicate

• Analytics strategy & roadmap

• Plan frameworks & interim states

• Plan & build capacity• Establish

governance• Communications &

education• Roll out and

Experimentation

• Build frameworks• Governance• Evolve and build

architecture and capacity

• Change management and benefits

• Experiment and prove solutions

• Build and optimize capabilities

• Governance• Change

management

Health Analytics …. A Roadmap for Success


Emerging technology resource documents:

https://www.infoway-inforoute.ca/index.php/resources/presentations/emerging-technology

Discussion & questions?

2013 Canada Health Infoway Inc. 15



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