targeted analytics: using core measures to jump-start enterprise analytics

Targeted Analytics:Using Core Measures to Jump-Start Enterprise

Analytics

About Perficient

Perficient is a leading information technology consulting firm serving

clients throughout North America.

We help clients implement business-driven technology solutions that

integrate business processes, improve worker productivity, increase

customer loyalty and create a more agile enterprise to better

respond to new business opportunities.

PRFT Profile

Founded in 1997

Public, NASDAQ: PRFT

2010 Revenue of $215 million

20 major market locations throughout North America— Atlanta, Austin, Charlotte, Chicago, Cincinnati, Cleveland,

Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Minneapolis, New Orleans, Philadelphia, San Francisco, San Jose, St. Louis and Toronto

1,500+ colleagues

Dedicated solution practices

500+ enterprise clients (2010) and 85% repeat business rate

Alliance partnerships with major technology vendors

Multiple vendor/industry technology and growth awards

Perficient brings deep solutions expertise and offers a complete set of flexible services to help clients implement business-driven IT solutions

Our Solutions Expertise & Services

Business-Driven Solutions• Enterprise Portals• SOA and Business Process

Management• Business Intelligence• User-Centered Custom Applications• CRM Solutions• Enterprise Performance

Management• Customer Self-Service• eCommerce & Product Information

Management• Enterprise Content Management• Industry-Specific Solutions• Mobile Technology• Security Assessments

Perficient Services End-to-End Solution Delivery IT Strategic Consulting IT Architecture Planning Business Process & Workflow

Consulting Usability and UI Consulting Custom Application Development Offshore Development Package Selection, Implementation

and Integration Architecture & Application Migrations Education

Our Speaker

Michael Faloney

• Healthcare Director responsible for development and delivery of business intelligence and analytics solutions

• Responsible for engagement delivery and improving data solutions for Perficient's healthcare clients

• 20+ years progressive professional experience across technology, business, and process domains

• +18 years in the IT fields of data warehousing, business intelligence, project/technical management, and applications development

• Significant experience in developing enterprise data strategies, data architecture, data governance, data quality, data integration, master data management, metadata management, reporting and analytics

• Held technical and management positions focused on delivering data warehousing and business intelligence solutions to the healthcare, financial services, and telecommunications industries

• The Case for Healthcare Business Intelligence

• Options for Healthcare Business Intelligence

• The Targeted Analytics Approach

• Core Measures Example of Building an Enterprise Analytics Platform with Targeted Analytics

• Next Steps

Today’s Agenda

Healthcare Business Intelligence

The Case for Healthcare Business Intelligence

Competitive Pressure

Regulatory Pressure

Cost Pressure

Quality of Care

Innovative Research

Financial Effectiveness

Operational Efficiencies

Regulatory Compliance

Increasing internal & external pressures makes the ability to accurately analyze the organization’s data in a timely manner to make critical financial, clinical or operational decisions a requirement, not a “Nice to Have”

Regulatory Pressure: Pay for Performance Meaningful Use ICD-10

Cost Pressure: Reduced Funding/

Reimbursements Skill shortages Procurement management

Competitive Pressure: Consumer choice Specialist hospitals Attracting the Insured dollar

Healthcare Analytics Examples

Clinical Alerts

Core Measure Analysis

Longitudinal Records

Outcome Tracking

Patient Safety

Diabetes Management

Clinical Pathways Analysis

Personalized Medicine

Clinical Trial Effectiveness Analysis

Population Studies

Surgical Analytics

Material Usage Analysis vs. Outcomes

Cost Management

Service Line Profitability

Scheduling Analysis

Inventory Control Analysis

Claims Management

Service Line Profitability

Meaningful Use

Expanded Granularity using ICD-10

State Reporting

Public Health Reporting

Healthcare BI

Quality of Care Innovative Research

Financial Efficiencies

Operational Effectiveness

Regulatory Compliance

There are many options for business intelligence in Healthcare

Options for Healthcare Business Intelligence

“Top-Down Approach” More likely to have an

enterprise view and support from the beginning

Potentially longer time-line to deliver capabilities

“Bottom-Up Approach” More likely to have

departmental view at the beginning

Potentially shorter-time to deliver capabilities

Potentially requires significant rework to move to an enterprise platform

Can have either a departmental or enterprise view

Pre-built components offer potential for accelerated delivery

Often more of an accelerator based approach vs. shrink-wrap

Often provides only part of the solution and forces users to fit their problem into the package solution

Either a pre-packaged or accelerator –based approach

Typically tied to vendor’s transaction system(s)

Potentially limited ability to work outside their platform

Often not technology independent

EDW/DATA MARTS FEDERATED DATA MARTS

HEALTHCARE VENDOR/MAJOR

SOFTWARE COMPANY

SOLUTIONS

PACKAGE APPLICATIONS

What is the Targeted Analytics Approach?

Targeted analytics is a structured approach to building out an enterprise analytics platform through the implementation of a series of individual

applications focused on solving business critical issues

Structured Approach

• Leverages Governance, Technical & Implementation Frameworks

• Methodical identification & Use of Accelerators

Building an Enterprise

Analytics Platform

• Enterprise View of Data

• Quality, Consistent, Accurate Use of Data

• Enhanced Reporting & Analytical Capabilities

• Empowers Decision Making

Series of Individual

Applications

• Quicker Return on Investment

• Improved Time to Market

• Accelerated Realization of Benefits

• Flexibility to Address Changing Business Priorities

Solving Business Critical Issues

• Allows for short-term benefit of solving current business issues, while building for the long-term benefit of using enterprise data for competitive advantage

Accelerator-Based Implementation Framework

Perficient BI Enable™ Approach

Targeted Analytics Framework

Governance Framework

Enterprise View

Strategic Direction

Data Stewardship

Data Ownership

Data Guardianship

Enterprise Architecture FrameworkArchitectural

VisionTechnical Oversight Standards Technical

Direction

Accelerator/Reusable Component Library

VisualizationComponents

Integration Components

Metadata Components

Data Model Components

Other Components

Project Management Functional Expertise

Envision Execute Evolve

The governance framework ensures an enterprise view is maintained as the targeted analytics applications are implemented

The accelerator-based implementation framework:

Based on Perficient’s BI Enable Approach

Balances process, technology and organizational constructs

Heavily leverages the accelerator library

Provides project, functional and technical oversight

Heavily leverages prototyping as a design/development technique

The enterprise architecture framework provides the supporting technical vision for the required functional capabilities, as well as ensures the developed applications meets the appropriate standards

ENTERPRISE ARCHITECTURE

How Does Targeted Analytics Work?

1Develop Initial

Application (SCIP Core Measures)

2Populate

AcceleratorLibrary

3 Develop Additional Applications

Bu

sin

ess C

ap

ab

ilitiesPneumonia

Core Measures

Diabetes Cardiovascular

MeaningfulUse

ClinicalAlerting

GOVERNANCE

ACCELERATOR LIBRARY

VisualizationComponents

Integration Components

Metadata Components

Data Model Components

Other Components

Enterprise View

Strategic Direction

Data Stewardship

Data Ownership

Data Guardianship

Architectural Vision

Technical Oversight Standards

Technical Direction

Arc

hite

ctu

re V

isio

n

Imp

lem

en

tatio

n E

fficie

ncy

Enterprise View

Strategic Direction

Core Measures Example

Starting with SCIP Core Measures, you set the initial foundation of your analytics platform through the creation of enterprise level, re-usable components

SCIP VALUE

PROCEDURE

CORE MEASURE

TYPE

PHYSICIAN

DIAGNOSIS

PATIENT

CORE MEASURE

DESC

TIME

Data Source

1

Data Source

2

Data Integration


The development of the first analytical application provides a number of accelerators that can be reused in future analytical applications. The governance function provides

the enterprise view to ensure the re-usability in future analytical applications.

SCIP VALUE

PROCEDURE

CORE MEASURE

TYPE

PHYSICIAN

DIAGNOSIS

PATIENT

CORE MEASURE

DESC

TIME

Data Source

1

Data Source

2

Data Integration

DATA

GO

VERN

ANCE

ACCELERATOR COMPONENT LIBRARY

Metadata Enterprise

Definitions for Data Elements

Data Integration Mappings Transformations Data Quality Rules ETL Components

Data Model Dimensions:• Time• Patient• Diagnosis• Procedure• Physician• Core Measure Type• Core Measure

Description Metrics:• SCIP Value

Hierarchies Descriptive Attributes

Presentation/Analytic Capabilities

Dashboard Framework Dashboard Widgets

Data Visualization Report Templates

Other Security (ex. Roles) Automation

Constructs


Using the base created with the first application, the implementation of another core measure area is significantly accelerated. The architecture function function provides

structure and process for leveraging the accelerators for future application

PROCEDURE

CORE MEASURE

TYPE

PHYSICIAN

DIAGNOSIS

PATIENT

CORE MEASURE

DESC

TIME

Data Source

1

Data Integration

ENTE

RPRI

SE

ARCH

ITEC

TURE


Metadata Enterprise










Constructs


Using the accelerators previously created as a based, additional functionality can be delivered in a more time-sensitive manner

PROCEDURE

CORE MEASURE

TYPE

PHYSICIAN

DIAGNOSIS

PATIENT

CORE MEASURE

DESC

TIME

Data Source

1

Data Source

3

Data Integration

FACILITY

PNEUMONIAMETRICS

ENTE

RPRI

SE

ARCH

ITEC

TURE


Metadata Enterprise










Constructs


Once the second application is developed, the accelerator library is populated with the additional re-usable components

PROCEDURE

CORE MEASURE

TYPE

PHYSICIAN

DIAGNOSIS

PATIENT

CORE MEASURE

DESC

TIME

Data Source

1

Data Source

3

Data Integration

DATA

GO

VERN

ANCE


Metadata Enterprise










Constructs

FACILITY

PNEUMONIAMETRICS

Metadata Enterprise




Description• Facility

Metrics:• SCIP Value• Pneumonia Metrics






Constructs

ENTE

RPRI

SE

ARCH

ITEC

TURE

Extending Past Core Measures


PROCEDURE

PHYSICIAN

DIAGNOSIS

PATIENTTIME

Data Source

1

Data Source

3

Data Integration


Metadata Enterprise










Constructs

FACILITY

Metadata Enterprise











Constructs

ENTE

RPRI

SE

ARCH

ITEC

TURE



PROCEDURE

PHYSICIAN

DIAGNOSIS

PATIENT

DISCRETE MEASURE

TIME

Data Source

1

Data Source

3

Data Integration

FACILITY

Meaningful Use Metrics

ENTE

RPRI

SE

ARCH

ITEC

TURE

ENCOUNTER

ADMISSION DATE DISCHARGE DATE

NURSING UNIT

Data Source

4

Data Source

5

ENTERPRISE ANALYIC PLATFORM

Metadata Enterprise










Constructs

Metadata Enterprise











Constructs



DATA

GO

VERN

ANCE

ENTE

RPRI

SE

ARCH

ITEC

TURE

ENTERPRISE ANALYIC PLATFORM

Metadata Enterprise










Constructs

Metadata Enterprise



Data Model Dimensions:

Metrics:• SCIP Value• Pneumonia Metrics• Meaningful Use Metrics






Constructs

Time Encounter

Patient Admission Date

Diagnosis Discharge Date

Procedure Nursing Unit

Physician Discrete Measure

CM Type CM Description

Facility

PROCEDURE

PHYSICIAN

DIAGNOSIS

PATIENT

DISCRETE MEASURE

TIME

Data Source

1

Data Source

3

Data Integration

FACILITY

Meaningful Use Metrics

ENCOUNTER

ADMISSION DATE DISCHARGE DATE

NURSING UNIT

Data Source

4

Data Source

5

In Summary

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targeted analytics: using core measures to jump-start enterprise analytics

Technology

business processes

major technology vendors

new business opportunities

north america

repeat business rate

enterprise analytics

san francisco

san jose