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High-Risk Patient Groups: Integrating Data for Population Health Management
January 26, 2015
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
• 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
• 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
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
Dignity Health’s Clinical Integrated Networks
1400
2647 6408
Clinical Integrated Physicians
Physicians inEmployment/Foundation
Independentsin CI
Independentsnot 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
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
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
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
PHM Supporting Data & Technologies
10
Dennis P. Sweeney
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
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
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
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
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
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
But key to PHM is Data!!
17
Data Availability, Access, and Quality
Thank You
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