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Health Analytics in Canada – A Blueprint for Gaining Clinical Buy-in and Creating Value from the Bottom up Alex J Mair, Director, Emerging Technology Group.

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Presentation on theme: "Health Analytics in Canada – A Blueprint for Gaining Clinical Buy-in and Creating Value from the Bottom up Alex J Mair, Director, Emerging Technology Group."— Presentation transcript:

1 Health Analytics in Canada – A Blueprint for Gaining Clinical Buy-in and Creating Value from the Bottom up Alex J Mair, Director, Emerging Technology Group Presented by: eHealth 2013 Conference May 27, 2013

2 Faculty/Presenter Disclosure Presenter: Alex J Mair Relationships with commercial interests: — Nothing to disclose 2 2013 Canada Health Infoway Inc.

3 Presented by Agenda Overview of Health Analytics Blueprint Health Analytics Key Concepts Opportunities and Challenges Roadmap for Success 3 2013 Canada Health Infoway Inc.

4 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 4 2013 Canada Health Infoway Inc.

5 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) 5 2013 Canada Health Infoway Inc.

6 Health Analytics - Future State Architecture Sourcing and querying data High Precision Analytics Transactional (Near realtime) Aggregate Predictive Analytics 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.)

7 2013 Canada Health Infoway Inc. Research data Researcher Health system manager Senior decision maker Quality improvement Lead Administrative (HR, Finance) Clinical data Program/population data Claims data Islands of information Information contextualized into knowledge Context Patient Provider Disease Condition Filters for context and metadata (disease, condition, risk factor) Health system planner Data analyst Health Analytics Future State Key Concept - Linkage of Data Sources Clinician / provider Patient / client 7

8 2013 Canada Health Infoway Inc. Information Value Chain Clinical and Business Value to Health System Capability Present Digitization, growing network of EHR / EMRs based around patient centric longitudinal records Past From paper based, unstructured, silo’d data, and isolated decision making To predictive and collaborative prevention, monitoring and management of population health Future 8 Health Analytics Blueprint value proposition is supporting our stakeholders make the transition to the more mature state where information value increases significantly 8

9 2013 Canada Health Infoway Inc. 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 Local Analyze Reports Retro- spective Reporting 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, Aggregation based processes 9 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.

10 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 Capability 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 Kaiser Permanente Primary Care CDS EMR data extract provides data daily to Data Warehouse Health Analytics Example 10 2013 Canada Health Infoway Inc.

11 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 11 2013 Canada Health Infoway Inc.

12 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 12 2013 Canada Health Infoway Inc.

13 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/BI 13 2013 Canada Health Infoway Inc.

14 Build Capacity & Capability Deploy Frameworks & Prove Concepts Build, Deploy And 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 14 2013 Canada Health Infoway Inc.

15 Emerging technology resource documents: Discussion & questions? 2013 Canada Health Infoway Inc. 15

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