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 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
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