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