1. Building the HIT Infrastructure for the Patient Centered Medical Home and Accountable Care OrganizationsCharles DeShazer, MD VP, Quality, Medical Informatics & Transformation Dean Health System, Madison, WI2012 Accountable Care and Health IT StrategiesSummit1/17/2012

2. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 3. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 4. New Care Models He who is first to battle is at ease; he who is late to battle isat labor Sun Tzu Move early to the next battleground, late entrants will notsurvive Patient-Centered Medical Home Health care model that aims to provide structured, proactive andcoordinated care for patients. Accountable Care Organizations Medical Home Neighborhood Group of health care providers (e.g. primary carephysicians, specialists and hospitals) that have entered into aformal arrangement to assume collective responsibility for the costand quality of care of a specific group of patients and that receivefinancial incentives to improve the quality and efficiency of healthcare. Payment Driven Models Bundled payments Pay for Performance Case rates Capitation 5. ACO model represents a shift of COST RISK toProviders through payment mechanisms 6. Population vs. Costs vs. Interventions Example of 100,000 People in a Population% of % ofCost Population Complex Case Management 1% 100025%Lives Disease/Demand14% 14,000 LivesManagement50%15% 15,000 LivesHealth 15% Mgmt70% 70,000 Lives10%Approximately 75% of costs are due to chronicconditions 7. Population Management bySegment 8. Impact of Healthy Behaviors 9. Healthcare Information Technology (HIT)RequirementsPCMH ACOs Care Coordination Cross Continuum Chronic DiseaseMedical ManagementManagement & Member EngagementComplex Case Clinical InformationManagement Exchange Population Health Quality & PerformanceManagement (espReportingregistries) Predictive Modeling & Patient Engagement & AnalyticsActivation Administrative and Evidence-based Financial RiskMedical Practice Management systems Real-time connectivity 10. EHR is necessary but notsufficient In "Associations Between Structural Capabilities of Primary CarePractices and Performance on Selected Quality Measures," MarkFriedberg MD, and colleagues examine how a range of primarycare practice attributes, including having an EMR, may impactphysician performance on quality metrics. The research profiled 307 practices in Massachusetts across 2007. Across the practice characteristics and HEDIS metrics, theattributes correlated to a practices higher-quality performance ondiabetes and prevention metrics included: having an EMR, frequentmeetings to discuss practice quality performance, and physicianawareness of patient experience. EMRs were specificallyassociated with higher performance on two diabetes metrics (eyeexams and nephropathy monitoring) and three prevention metrics(breast cancer, colorectal cancer, and chlamydia). Key insight: The key transformative aspect of the EMRs role inthe practice was shown to be providing information to supportdecision-making (Clinical Decision Support)--not just servingas a repository for data. Workflow et al, Annals of Internal Medicine, 2009; 151:456-463feedback, creating andFriedberg, M., redesign, providing performancemonitoring registries and EHR optimization are critical success 11. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 12. Continued Evolution of the Medical Care Genomics New Technology Aging Population Consider Implicationsfor PCMH, CDS forproviders ANDpatients ACO, predictivemodelingimplications for riskmanagement &population healthmanagement 13. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 14. Meaningful Use & ICD-10 Meaningful Use Driving increased adoption of EHRs in-patient and ambulatory Penalty starts if not meaningful user by 2015 Infrastructure for ONC vision and robust Clinical Decision Support(CDS) ICD-10 One of the most comprehensive regulatory changes in the history ofhealthcare in the US Unlike MU, it is an unfunded regulatory event Replaces 30 year old ICD-9-CM, which is outdated and lacks clinicalgranularity Provides granularity to diagnostic information that shouldgreatly enhance predictive models Improved ability to specify and measure healthcare services Enable better integration of predictive modeling and clinicaldecision support Richer data structures for research 15. ICD-10 Asthma Codes More granular clinicalinformation willenhance predictivemodels as well asenable real-timeprogram referralsespecially whenfollowed serially andcombined with otherdata. 16. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 17. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 18. Data Management LifecycleData Collection (QA) Data Extraction (ETL) Avoid GIGO Critical Integration Step Collection workflows Data Governance & Clarity of where to enterMaster Data Management data to be reportableData warehouse & marts Coding consistency and Single source of truth conventions (ICD-10) Create Predictive &Analytic Models Establish accountabilityLeverage Analytics for and feedback mechanisms Insights that drive Link with Lean effortsdecisions and processes Identify gaps and new Testing and Validation requirements Formatting for ACTION Learn from reports & Visualization of data change collection process Delivery medium incl. CDSImprovement Initiatives Information Delivery 19. Key Technical Infrastructure to support thePCMHEHR is necessary but not sufficient. The next level of quality management willrequire an INTEGRATED Health Information Technology (HIT)ecosystem especially a robust analytic infrastructure. Standalone EHRmay not be able to provide all of these functions.Focus AreaKey Technical InfrastructureCare Coordination HIE, Workflow Management, Shared Care Plan,Referral trackingChronic Condition ManagementCRM, Workflow Management, Shared Care& Complex Care Management Plan, Predictive Modeling, CDS, Telehealth,RegistriesPopulation Health ManagementCRM, HRA, Predictive Modeling, WorkflowManagement, CDS, Population analytics,RegistriesPatient Engagement & Activation CRM, Shared Decision Making, Telehealth, PHREvidence-Based Medicine CDS, Workflow Management, PopulationPracticeanalyticsReal-Time ConnectivityHIE, Telehealth, mobile technology, unifiedmessaging 20. CSC ACO Maturity Stages 21. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 22. Big Data Analytics Recent IDC research on digital data indicates that in 2010, the amount of digitalinformation in the world reached beyond a zettabyte in size. Thats one trillion gigabytesof information. To put that in perspective, a blogger at Cisco Systems noted that azettabyte is roughly the size of 125 billion 8GB iPods fully loaded. The increasing velocity, variety and complexity of data is overwhelming traditionaldatawarehouse tools, techniques and infrastructure. Healthcare has a particular need to manage data well as EHRs become common, use ofdevices increase, integration of multimedia and imaging becomes important, integrationwith social networking resources becomes useful and genomics data becomes essentialfor decision-making. New high performance hardware, software and techniques are emerging to address thisissue called Big Data Analytics. Gartner contends that terms like "big data," "real-time data" and "linked data" signal anew era in which the economics of data (not the economics of applications, software orhardware) will drive competitive advantage. What does this mean? It doesnt matter which EHR you have from a competitivestandpoint. Competitive advantage will come from (1) the quality of the data youcollect, (2) how you integrate the data and provide analytics to drive insights and(3) how well you use these insights to drive customer experience/relationships andbusiness results. 23. Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor Data Integration &Distribution Big Data Analytics Key Strategies & Tactics 24. Leverage Meaningful Use as a SpringboardCriteriaOpportunityProblem ListDefine system-wide standards and policies,improve accuracy of documentation, infrastructurefor CDS, use for shared care planAVS & PHR Enhance quality, consistency and usefulness ofcontent (esp. for chronic condition management),fully operationalize PHR, enhance patientengagement, use for shared care plan, leverage toengage family & caregiversMedication List Improve medication reconciliation andmanagement of transitions of care.Patient Lists & Enhance analytics, create robust registries andStructured Data dashboards, infrastructure for CDSClinical Decision Create governance structure, establish standards,Support focus them on key areas of improvementopportunity, avoid alert fatigueQuality MeasuresExpect to be held accountable for results, create 25. Key Tactics & Strategies Implement & Optimize your EHR Consider "Big Data" Analytics Develop an effective data governance and master datamanagement strategy Develop your Clinical Analytics unit Enhance your CDS infrastructure Decide on and commit the organization to an improvementmethodology, this is the cultural change tool Invest in workflow optimization (good use for Leantechniques) Docs should manage by exception Consider how you will create a Shared Care Plan (SCP)to ensure all providers and the patient are on the samepage Create enterprise and community infrastructure for healthinformation exchange and CRM at the ACO level 26 Develop approaches to activate consumer/patient & family 26. Thank You! Contact Information Charles DeShazer, MD VP, Quality, Medical Informatics & Transformation Dean Health System, Madison, WI Charles.deshazer@deancare.com Twitter @hctransformed