Data Analytics in the Military Healthcare System Reorganization

April 15, 2015

Col Albert (Al) Bonnema, MD MPH Chief, Information Delivery Division in the Defense Health Agency's Health IT Directorate

DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.

Conflict of Interest Albert Bonnema, MD MPH Col, USAF, MC Has no real or apparent conflicts of interest to report.

© HIMSS 2015

Learning Objectives

• Describe the translation of new strategic plans into analytics

requirements for a reorganizing healthcare system • Describe the benefits of a new Analytics Capability in

executing Military Healthcare System's requirements • Examine the analytics technology modernization in the midst

of an EHR modernization • Discuss the development of a Performance Management

System that supports the MHS Strategic Plan

Change 1.0–Health IT Legacy Portfolio

• Sustainment Costs > Budget

• New requirements exceed IT staff capacity

• Development costs exponentially increase due to complexity

• Difficult to define a modernization or innovation starting point on 20 yr old legacy systems

• Functional Owners and Product Managers fear change – “at least the old stuff works”

Change 2.0–Medical System Merger

• Congress legislates Military Health Care System to consolidate common missions

• On October 1, 2013, the Defense Health Agency is established

– Tricare Management Activity (TMA) stands down

– Army, Navy, Air Force, and TMA aggregate common functions like Pharmacy, Logistics, Research, Health IT into Shared Services

• Simultaneous establishment of new governance, mobilization of 1000’s of employees, realignment of budgets and resources, and consolidation of duplicate functions

Change 3.0 – Everyone Wants ‘Data’

• Demand for data/information to support MHS modernization exceeds analysts and data marts capacities

• 20 years of legacy data marts, tools, and analysts could be described as “feudal kingdoms”

• Analysis of data objects of 10 largest data marts show >70% duplication

• The work of a core group of analysts scattered among data marts can be described as outstanding to ‘cutting edge’ health services research

• Meticulous quality control and HIPAA protection processes

Building MHS Analytics Capacity

• Data Governance • Business Intelligence Governance Governance

• Skills • Types of Analysis • Cultural/Data Literacy

Analysis

• Business Intelligence Architecture • Data Sources/Currency/Latency • Data Models • Analytic Tools/Infrastructure

Analytics

Analytics Maturity Model from Advisory Board

Strategic Re-Alignment of the Health IT Portfolio

3rd+ Gen EHR Core

Medical Devices

PACS

Content Mgt

Trusted Data Services – Health Information Exchange

Partnered Data Services – Health Information Exchange/Health Information Service Provider

Data Warehouse &

Analytics

Applications

Network & Security Infrastructure

Internet

Patients Eligible Providers Hospitals Business

Associates

Firewall

Work in Progress

1. Acquire new EHR 2. Acquire HIE 3. Rationalize

Applications 4. Consolidate Medical

Networks 5. Modernize Analytics

MHS Analytics Requirement Scope

• The Military Healthcare System is more than a Hospital System – it is also an insurance plan, health promotion, research, military mission support, disability system, occupational health, humanitarian, public health, etc.

• MHS leaders and managers want a single “view” of their mission • Major implications for the new EHR, Portfolio Rationalization, and

Health System Modernization

1 2

3 4

Direct Care System - ~35%

Purchased Care System - ~ 65%

Top Ten Success Factors for MHS’ Analytics Modernization

• Leadership

• Joint Governance

• New EHR

• Analysts Workflow

• Data Governance & Management

• Health IT Shared Service

• Analytics Operations and Service Offering

• Analytics Service Catalogue

• Technology Investment

• Scalability and Usability

Leadership – High Reliability Organization Mandate

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Better Technology

Better Information

Transform Health Care

Goal 1: Achieve Adoption & Information Exchange through Meaningful Use of IT

Goal 2: Improve Care, Pop Health, and Reduce Costs through the Use of IT

Goal 3: Inspire Confidence & Trust in Health IT

Goal 4: Empower Individuals with Health IT to Improve their Health and Healthcare System

Goal 5: Achieve Rapid Learning & Technological Advancement

•“By July 15, 2015, I want a report that clearly demonstrates the PMS capability to drive system wide improvement for the identified common executable goals against common standards and for the dashboards to have measures identified in all areas

covered by the MHS Review.” (SECDEF Memo, 1 OCT 2014) Demonstrating PMS Capability to Drive System-Wide Improvement: Governance (upper circle) selects focus areas for improvement, informed by PMS support. Once approved, focus areas are communicated to the Execution components (lower circle). In addition to selecting focus areas, governance decides roles and responsibilities, and what elements of change package should be developed centrally (e.g., evidence based guidelines, simulation, communications). PMS provides Governance and Execution customers with information to monitor improvement. Approved 30 Core Measures with 5 initial Focus Areas Action Plan groups own the implementation and dissemination

Leadership – Partnership for Improvement (P4I)

New Governance – Functional Owners

Medical Operations

Group

Partnership for Improvement Steer Cmte

Business Analytics Council

Clinical Analytics Council

Enterprise Intelligence Steer Cmte

Data Management

Board

-New Joint Committee structure with decision authority

-No longer dependent on portfolio boards

New EHR • Today, the MHS operates 6 different EHRs with many

different instances. –Aggregating the data for analytics and interoperability

is a negatively impacts latency, processing, and storage

–Data governance practices work for the local EHR instance but not for enterprise use cases

• Future, the MHS should have a single patient record –Data governance will be implemented from the

beginning –Data exchange will benefit from modern data

exchange and virtualization technologies

New Analysts Workflow

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Analysis Workflow Process c/o SAS

Current – most “data work” is completed by “Super Analysts” and completed “by hand” monthly

Pros – deep understanding of data; meticulous Cons – little automation; large storage volume; proprietary SQL code; reduced ad hoc availability

In the Future – discovery measures are automated when governance approves Pros – experts in ELT/ETL, modeling, BI automate; cost/measure decreases; more ad hoc and special studies Cons – disconnects between analysts/IT; “data quality” unknowns

• The DHA Data Manager resides within the DHA HIT Information Delivery Division and is organizing the catalogue of service offerings.

• The Data Services Branch is organized into four Sections: Governance, Architecture, Acquisitions, and Operations

• MHS data activities have been fragmented and ineffective as evidence by portfolio duplication, numerous failed IT projects, duplicate patient issues, and millions of non-standard terms in EHRs.

• Data Management is a critical core mission capability and every strategic initiative is dependent on its management – EHR, HIE, Interoperability, Portfolio Rationalization, P4I, and Analytics

New Data Management & Governance

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“Governance and process issues are far greater impediments to success than the technical issues that must be confronted during the process of creating shared services.” Gartner - Shared Services in Government: Critical Success Factors, Kost, Published: 10 August 2012

New Health IT Shared Service

• Defense Health Agency’s Health IT Directorate is the consolidation of IT resources from the Services and TMA. Mr. Dave Bowen, SES, is the HIT Director/CIO.

Army

USAF

TMA

Navy

DHA HIT

Shared Service

New MHS Analytics Service Offering

Data Services

Web Strategies & Collaboration

Enterprise Intelligence

Health Information Exchange

Registries

Information Delivery Division

New MHS Analytics Service Offering

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Wisdom

Knowledge

Information

Data Data Services

E-Intelligence

E-Web Strategies

Modernization Governance Interoperability

Analytics Measures Reporting Decision Support

Functional Communities

Collaboration Web Platform Office Workflow

Function Activity Target

Presentation Layer

Logic Layer

Data Layer

UNCLASSIFIED

Data

New Analytics Service Catalogue

20

Better Technology

Better Information

Transform Health Care

Goal 2: Improve Care, Pop Health, and Reduce Costs through the Use of IT

Goal 3: Inspire Confidence & Trust in Health IT

Information Knowledge Action

CDS Surveys

Analytics

Research

Goal 4: Empower Individuals with Health IT to Improve their Health and Healthcare System

New MHS Analytics IT Requirements

Visualization Data Drill Down

Data Quality Data Discovery

Data Latency

Analytic Tools

Analytic Logic

New EHR Alignment

New Infrastructure for Scalability and Usability

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Enterprise Data Warehousing and Big Data

MHS Enterprise Portal approved for HIPAA Data

MHS Enterprise Health Information Exchange

Reporting, Business Intelligence, and Advanced Analytics

Enterprise Registries for Research, Population Health, and Immunizations

MHS Cloud Computing

Questions? Col Albert (Al) Bonnema, MD MPH Chief, Information Delivery Division Albert.h.bonnema.mil@mail.mil O: 703-681-6243