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High Risk patient Groups presentation 20150123.1

  1. High-Risk Patient Groups: Integrating Data for Population Health Management January 26, 2015
  2. 2 • Dignity Health Clinical Integrated Networks – Organization Background – Mission Statement – Clinical/Business Requirements for High Risk Patient Management – Technology Framework • PHM Supporting Data & Technologies – Population Health Management Technology Approach – Data & Analytics Obstacles – Data Integrated for a Patient-Centric Stratification – PHM Conceptual System Overview – Summary Agenda
  3. 3 • Mr. Brent Bizik, Executive Director Population Health Management – Population Health Management Business Strategy, Information Technologies, and Operational Activities for Dignity Health and its established Clinical Integrated Networks/ Accountable Care Organizations – 15+ years serving in health care IT leadership roles, managing projects resulting in increased business efficiencies and improved customer care – Served in management positions with Arizona’s Medicaid Program, the Arizona Health Care Cost Containment System (AHCCCS), planning, creating, implementing, and managing projects, policies, and procedures – Served as interim Chief Operating Officer (COO) for a $200M Medicaid managed health plan, overseeing complex health care transition projects, managing third-party/vendor transition teams – Reputation for sound organizational leadership skills and proven ability to successfully manage and coordinate multiple concurrent projects, gain consensus, think strategically, motivate employees, and build teams – Masters in Business Administration in Health Care Management Regis University—Denver, CO – BS in Business Administration, Finance University of Arizona—Tucson, AZ Brent C. Bizik, MBA
  4. 4 • Mr. Dennis Sweeney, Acting Program Director – Supporting Dignity Health as Program Director for strategy, architecture, design, development, implementation of the Dignity Health’s Ambulatory Information Management (AIM) clinical intelligence and analytics solution – Supporting the technical aspects of Dignity Health Clinical Integration / Accountable Care Organization initiatives – Principal with Tellogic Inc. – provides consulting on Healthcare data management, expertise in IT data strategies, design, development, and implementation solutions – 20+ years experience formulating enterprise-wide healthcare technology strategies, managed multi-million dollar data warehouse and business/clinical intelligence projects, and provides critical technical expertise to healthcare organizations – Masters in Business Administration (MBA) from Adelphi University, Executive Masters in Business Administration (EMBA) from ULCA Anderson School and his Bachelors in Chemical Engineering (BSChE) from Rensselaer Polytechnic Institute Dennis P. Sweeney, MBA
  5. Dignity Health Background: Founded in 1986, Dignity Health is one of the nation’s five largest health systems Mission: We are committed to furthering the healing ministry of Jesus. We dedicate our resources to: • Delivering compassionate, high-quality, affordable health services; • Serving and advocating for our sisters and brothers who are poor and disenfranchised; and • Partnering with others in the community to improve the quality of life. FY14 Community Benefits and Care of the Poor (Including Unpaid Cost of Medicare): $2 billion Statistics: Fiscal Year 2014 HQ: San Francisco Net Operating Revenue (FY14) $10.7 Billion Acute Care Facilities: 39 Employees: 56,000 Acute Physicians: 9,000 Care Centers: 380 Acute Care Beds: 8,500 Skilled Nursing Beds: 700
  6. Dignity Health’s Clinical Integrated Networks 1400 2647 6408 Clinical Integrated Physicians Physicians in Employment/ Foundation Independents in CI Independents not in CI • 45 Hospitals • 7 Clinically Integrated Networks 6 North State TBD* SQCN 155* SCICN- Ventura 257* VIPN TBD* SRQCN 700* ACN (Includes Abrazo facilities) 2400* SCICN-Inland Empire 135* *note: Each Clinical Integrated Network’s approx. count of participating providers as of December 2014
  7. 7 Through an integrated Population Health Management Strategy, Dignity Health will provide health care that improves the well-being and quality of life for the individuals and communities we serve. Mission • To transform patient behavior and health outcomes through the implementation of innovative Population Health Management strategies. Vision • To empower consumers through new Population Health Management care models consistent with our healing ministry Shared Values & Beliefs • Provide whole-person, patient-centered care to patients and their families • Build compassionate clinically-integrated care management teams to improve access and quality of care and excellence in patient experience • Offer technology and resources to ensure information access, effective communication and coordination of care • Develop innovative solutions to engage and empower patients to manage their health wherever they are along the continuum • Provide high-quality, evidence-based health care to improve overall health of the communities we serve Population Health Management
  8. 8 Population Health Management Key Pillars Patient-Centered Health Care Self- Management Clinical Integrated Care Management Evidence Based Healthcare Healthcare Cost Reduction while Increasing Outcomes • Secure communications: Care Giver / Provider / Provider / Patients • Self Service Access: • Clinical information • Schedule appointments • Targeted Invention tools based on personal health history • Alerts on Gaps in Care • Patient Centered Healthcare Data storage • Care team alerts on patient encounters • Alerts on Gaps in Care • Shared information on Patients clinical care, payer / product, and network attribution at all points in care delivery • Longitudinal Patient Record access • Analytic Engines on High Risk Patient Stratification • Patient Centered Healthcare Data storage • Clinical Decision Support / Clinical pathways based on each patient personal history • Alerts on high cost patients & encounters • Alerts on Gaps in Care • Analytic Engines Patient Stratification (High Risk) • Predictive analytics on high risk patient and recommended care • Patient Centered Healthcare Data storage • Analytical applications for Financial analysis • Predictive analytics on patient costs • Predictive Analytical Applications for Financial analysis • Provider Profiling / Performance • Collect and store patient hospital cost information to support financial algorithms • Patient Centered Healthcare Data storage
  9. Information Layer Parsing – Validation- Routing- Privacy & Security- Filtering- Indexing- Notification Routing Payer Claims Master Patient & Provider Index Normalization/ Semantic Interoperability Clinical Data Repository (CDR) HIE Module Technology Framework Supporting Population Health Clinical Tools Communication Clinical Portal Consumer & Patient Portal Clinical Applications Analytics, Metrics Protocols, Pathways Aligned Care Team Clinical Interactions MobilMD Orion Rhapsody Payer Claims
  10. PHM Supporting Data & Technologies 10 Dennis P. Sweeney
  11. 11 Population Health Management Technology Approach Needs Assessment: Identified PHM Business Requirements Determined Function, Data, and Technical Requirements Performed Vendor Market Scan & Data Landscape Identified Data Challenges and Potential Solutions Vendor Assessments & Pilots and Internal Development • Business Driver Sessions & Use- Cases • Determined biggest Value for Dollars ($) • Use-Cases identified Data requirements • Identified technical needs • Conducted multiple vendor product reviews & demonstrations • Vendor marketplace is immature • Gained understanding of the Data: • Availability • Access • Quality • Have a Unique Environment • Over 120 different EMRs • No obvious source of truth for clinical data • Our Environment is Unique • Over 120 different EMRs • No obvious source of truth for clinical data Determine gaps that vendor solutions didn’t support
  12. 12 National ACO Benchmarking – Data & Analytics Obstacles 52% 66% 73% 74% 76% 80% 83% 88% 100% Access to data within my organization/network Lack of trained staff Applying analytics into action and practice Data quality Data liquidity Lack of funding and/or return-on-investment Workflow Integration Integration and blending of disparate data Access to data beyond my organization/network Surveyed ACOs reported nine key challenges: Data Source: eHealth Initiative (eHI) 2014 Survey of ACO’s Five of the Nine challenges are directly related to Data
  13. PRIMARY DATA Administrative Data • Med / Rx claims • Eligibility • Provider files • Consumer data Clinical Data • Lab values • Biometric screenings • EHR integration • ADT feeds Survey Data • Health risk assessments • Patient activation • Patient experience • Physician referral PATIENT PROFILE Data Integrated for a Patient-Centric Stratification Clinical rules engine, predictive models and clinical judgment to identify patients for care advising Medical Costs Risk Scores Utilization Trends Chronic Conditions Medications Demographics Biometrics / Labs Engagement Gaps in Care Health Status Clinical Judgment Predictive Model Clinical Rules
  14. 14 PHM Conceptual System Overview Enterprise Data Warehouse Claims Service Exchange Portals Provider Rx RBM 6. Payer Admin Platform and patient engagement applications Payer Provider Network 7. Provider network affiliation data management with credentialing / contracting workflow Care Coordination 5. Performance dashboards and reports Portals Care Browser Care Mobile 4. Drives mobile and desktop population health applications Rules Engine 3. Data is run through a configurable rules platform Data Exchange/ Clinical Data Repository 1. Aggregates a broad clinical and financial data set from health system partners and payers HRA Data Hospital ADT Data EMR Data Biometric Data Payer Claims Case Notes Pharmacy Data Lab Results 2. Patient-centric Data Warehouse Analytics Cal Index
  15. The Jury is Out 15 Leveraging commercial vendor solutions Versus Internally building Challenge is: • Commercial vendors solutions are in development and still immature to fully support PHM needs • PHM Business Models are rapidly evolving
  16. Every Organization may have a different Population Health Strategy 16 Needs to be based on each PHM Organization's situation *Key factors Participating Providers and Data is: • Centralized • Federated
  17. But key to PHM is Data!! 17 Data Availability, Access, and Quality
  18. Thank You
  19. Examples of Data Sources supporting Business Needs 19 Data Source Type of Data Supports Claims Data ICD-9 / ICD-10 Determining patient Registries (i.e. CHF, COPD, Asthma, etc.) Claims Data CPT4 (Encounter Codes) Quality Metrics Denominator criteria Claims Data CPT II (PQRS Statistical Codes), if Available Quality Metrics Numerator Data Lab results Clinical Values Quality Metrics & Care Coordination support EMR data Vitals, Problem lists, lab results, Registry information, Medications Quality Metrics, Gaps in Care Pharmaceutical Medications Fulfillment Quality Metrics, Determining patient registries