Data Warehousing & Data Warehousing & Analytics in the VHAAnalytics in the VHA

Jack BatesJack BatesVHA Office of InformationVHA Office of Information

Corporate Data Warehouse GroupCorporate Data Warehouse Group

IHS Technology ConferenceIHS Technology ConferenceJune, 2005June, 2005

AgendaAgenda

What is Data Warehousing?What is Data Warehousing?Brief HistoryBrief HistoryPrinciplesPrinciplesCase StudiesCase StudiesOutlook for next 12 – 18 Outlook for next 12 – 18

monthsmonthsQ&AQ&A

““A structured repository of A structured repository of validated, integrated, and validated, integrated, and current data accessible to current data accessible to business people to provide the business people to provide the basis for both tactical and basis for both tactical and strategic business decisions.”strategic business decisions.”

What is a Data Warehouse?What is a Data Warehouse?What is a Data Warehouse?What is a Data Warehouse?

HRHR

Corporate Data Warehouse ConceptCorporate Data Warehouse Concept

Centralized extract and stagingCentralized extract and staging

Separate from operational Separate from operational systemsystem

Structured for analysisStructured for analysis

Current with sufficient historyCurrent with sufficient history

ADRADR

PATSPATS

HDRHDR

PFSSPFSS

FMSFMS

LogisticsLogistics

NPCDNPCD

CorporateCorporateData Data

WarehouseWarehouse

Operational SystemsOperational SystemsOperational SystemsOperational Systems

History of Data Warehousing in VHAHistory of Data Warehousing in VHA First instances were created at the regional First instances were created at the regional

levellevel First appeared in early FY98 First appeared in early FY98 Grass roots effortGrass roots effort Due to regional management (instead of Medical Due to regional management (instead of Medical

Center) centric management structureCenter) centric management structure No central data/information capabilityNo central data/information capability Spread slowly due to new technology issues Spread slowly due to new technology issues

(expertise was in M)(expertise was in M) Now technology is widespreadNow technology is widespread

Exists in every Region (more or less)Exists in every Region (more or less) VHA wide data marts now exist (PBM, Prosthetics)VHA wide data marts now exist (PBM, Prosthetics) VHA wide data warehouse strategy now existsVHA wide data warehouse strategy now exists VHA wide Corporate Data Warehouse in Phase II VHA wide Corporate Data Warehouse in Phase II

of construction phaseof construction phase

25 Years of VistA25 Years of VistA(July 25, 2005)(July 25, 2005)

Secrets of VistA’s SuccessSecrets of VistA’s Success Incremental EvolutionIncremental Evolution Built by the subject matter experts who Built by the subject matter experts who

were passionate about their productwere passionate about their product Best of Breed approachBest of Breed approach ModularModular Common infrastructureCommon infrastructure Consistent and evolving interfaceConsistent and evolving interface Provision for new ideasProvision for new ideas

Corporate Data Warehouse PrinciplesCorporate Data Warehouse Principles

Corporate Data WarehousingCorporate Data Warehousing is business-orientedis business-oriented will treat information as an will treat information as an

assetasset will be developed using will be developed using

standards-based and standards-based and architecturally-sound architecturally-sound principlesprinciples

will maximize leveraging, will maximize leveraging, collaboration, and reuse (and collaboration, and reuse (and Enterprise Agreements)Enterprise Agreements)

Rationale for Establishing aRationale for Establishing aCorporate Data Warehouse (CDW)Corporate Data Warehouse (CDW)

VHA needs a strategic corporate capability to:VHA needs a strategic corporate capability to: Manage cost, workload, utilization, quality, satisfaction, Manage cost, workload, utilization, quality, satisfaction,

and performanceand performance Perform effective budgeting and forecastingPerform effective budgeting and forecasting Enhance patient safetyEnhance patient safety Manage suppliersManage suppliers Facilitate disease managementFacilitate disease management Facilitate researchFacilitate research Facilitate business transformation from Facilitate business transformation from ”just in case” to ”just in case” to

“just in time”“just in time” Coordinate responses during national emergenciesCoordinate responses during national emergencies

Performance Measurement:Performance Measurement:Setting the U.S. Benchmark for 18 Setting the U.S. Benchmark for 18

Comparable IndicatorsComparable IndicatorsClinical Indicator VA 2002 VA 2003 Medicare 03 Best Not VA or Medicare

Advised Tobacco Cessation (VA x3, others x1) 69 75 62 68 (NCQA 2002)

Beta Blocker after MI 97 98 93 94 (NCQA 2002)

Breast Cancer Screening 80 84 75 75 (NCQA 2002)

Cervical Cancer Screening 89 90 62 81 (NCQA 2002)

Cholesterol Screening (all pts) 91 91 NA 73 (BRFSS 2001)

Cholesterol Screening (post MI) 92 94 78 79 (NCQA 2002)

LDL Cholesterol <130 post MI 74 78 62 61 (NCQA 2002)

Colorectal Cancer Screening 64 67 NA 49 (BRFSS 2002)

Diabetes Hgb A1c checked past year 94 94 85 83 (NCQA 2002)

Diabetes Hgb A1c > 9.5 (lower is better) 17 15 NA 34 (NCQA 2002)

Diabetes LDL Measured 94 95 88 85 (NCQA 2002)

Diabetes LDL < 130 70 77 63 55 (NCQA 2002)

Diabetes Eye Exam 72 75 68 52 (NCQA 2002)

Diabetes Kidney Function 78 70 57 52 (NCQA 2002)

Hypertension: BP < 140/90 55 68 57 58 (NCQA 2002)

Influenza Immunization 74 76 P 68 (BRFSS 2002)

Pneumocooccal Immunization 87 90 P 63 (BRFSS 2002)

Mental Health F/U 30 D post D/C 81 77 61 74 (NCQA 2002)

VHA Business Intelligence Road Map

VHA Business Intelligence Capability Maturity Model

A 5-7 year roadmap

Functional/Departmental QueriesPredefined QueriesKey Performance IndicatorsBalanced Score CardCorporate Alerts

Sophisticated OLAPAd hoc AnalysisPerformance DashboardsPortal Based ReportingStatistical AnalysisSpatial Analysis

Cross-Functional/Strategic AnalysisData VisualizationClick Stream AnalysisBehavior Profiling

Data MiningContent ManagementKnowledge ManagementText MiningClosed-loop Decision Processing

Pervasive and Personalized IntelligenceCollaborative and Real-time AnalysisWorkflow IntegrationBG and GG integrationCRM Contact Mgt. IntegrationMobile and Location Based Analysis

Level 1

Level 5

Level 4

Level 3

Level 2

Strategy, Program Planning,

Sponsorship, Governance, Communications,

Metadata, Data Standardization

WaitWaitTimesTimes

DataDataWarehouseWarehouseVHAVHAaa

VHAVHAcc

SourceSourceSystemsSystems

DiabetesDiabetes

AcquireAcquire Populate Populate Create Create Access Access Data Data WarehouseWarehouse MartsMarts Information Information

11 33 44

CommonCommonQuery, Reporting,Query, Reporting,

Analysis, and Analysis, and Data MiningData Mining

ToolsTools

OPOP

PBMPBM

22

OtherOther

VHA Corporate Data Warehouse Visual VHA Corporate Data Warehouse Visual ArchitectureArchitecture

VistAVistAHDRHDR

NPCDNPCDDSSDSSADRADR

VAVADoDDoDCMSCMS

ConformedConformedDimensionsDimensions

Prog OfficeProg OfficeData MartsData Marts

Ext

ract

, Tra

nsf

orm

, Lo

adE

xtra

ct, T

ran

sfo

rm, L

oad

VISNVISNWarehousesWarehouses

VHAVHAcc – VHA clinical data systems – VHA clinical data systemsVHAVHAaa – VHA administrative data systems – VHA administrative data systems

Program OfficesProgram Offices•Pharmacy BenefitsPharmacy Benefits•ProstheticsProsthetics•DentalDental

Closed Loop Information SystemClosed Loop Information System

(VISN Support Service Center)(VISN Support Service Center)(VHA Office of Information)(VHA Office of Information)

DataDataConsultantsConsultants

VSSCVSSCProfessionalProfessional

ServicesServices

ResearchResearchData MartsData Marts

VSSC ManagedVSSC ManagedVSSC ManagedVSSC Managed

Program Office ManagedProgram Office ManagedProgram Office ManagedProgram Office Managed

Value Added DataValue Added Data

Current Subject AreasCurrent Subject Areas OutpatientOutpatient

AppointmentsAppointments EncountersEncounters Primary Care PanelsPrimary Care Panels

InpatientInpatient MovementMovement DischargesDischarges

Lab (53 tests)Lab (53 tests) RadiologyRadiology PharmacyPharmacy ProstheticsProsthetics Non VA CareNon VA Care Human ResourcesHuman Resources Financial AccountingFinancial Accounting

•NursingNursing•DentalDental•PurchasingPurchasing•Outpatient EncountersOutpatient Encounters•Health Data RepositoryHealth Data Repository

•Vital signsVital signs•AllergiesAllergies•Lab testsLab tests•PharmacyPharmacy

Planned Additions:Planned Additions:

VHA Corporate Data WarehouseVHA Corporate Data WarehouseDimensional ArchitectureDimensional Architecture

Conformed Dimensions

Patien

t

Provid

er

Facilit

y

Stop

Code

Bed S

ectio

n

CPTIC

D9BOC

Time

Con

form

ed F

acts

Fact: Contains one/more measures or facts. E.g., Bed Days of Care per 1000 patients, Cost Per Veteran Per Month. These facts are numeric and additive. A fact table has a multi-part primary key made up of two or more foreign keys, and expresses a many to many relationship.

Dimension: Contains descriptive textual information. Dimension attributes form thesource for constraints for data warehouse/data mart queries. In essence, they providethe context/perspective for analysis. E.g., Drug, ICD9, DRG, Patient. Each dimensiontable has a single-part primary key that corresponds exactly to one of the componentsof the multi-part key in the fact table.

VHA > VISN > Facility > Division > Service > Clinic > Clinic Location

DimCPT

CPTID varchar(5)

CPTName varchar(30)CPTCategory varchar(75)CPTClass varchar(40)Inactive varchar(8)WorkRVU numeric(10,2)PrExpRVU numeric(10,2)MalPrRVU numeric(10,2)TotalRVU numeric(10,2)

DimDRG

DRGID smallint

DRGName varchar(70)DRGCategory varchar(70)DRGClass varchar(7)DRGType char(3)ValidYear int

DimICD9

ICD9ID int

ICD9Txt varchar(9)ICD9Prefix varchar(5)ICD9Name varchar(50)ICD9Category varchar(50)ICD9Class varchar(100)ICD9SubClass varchar(100)

Clinical

DimAge

AgeID smallint

AgeGrp2 varchar(15)AgeGrp4 varchar(15)AgeGrp10 varchar(15)AgeGrp14 varchar(15)AgeGrpARC varchar(15)

DimPatient

ScrNumID int

ScrSSN varchar(9)PtSSN varchar(9)ICN char(10)DoB smalldatetimeDoD smalldatetimeDoDSource varchar(10)Gender varchar(1)Race varchar(25)EnrZip intHmFIPS intPreferredVISN intPreferedSta3n intPreferredSta6a varchar(6)CFYVERAClass char(3)PFYVERAClass char(3)Eligibility char(3)EnrPriority varchar(3)EnrStatus varchar(50)PCProvider char(10)Diabetes char(1)Hypertensive char(1)

Demographic

DimARCTrtLoc

TrtLocID char(3)

TrtLocName varchar(100)TrtLocCategory varchar(100)

DimARCTrtType

TrtCodeID varchar(5)

TrtCodeName varchar(50)

DimALBAcct

AccountID smallint

AcctDesc varchar(50)

DimCostCtr

CostCtrID smallint

CCName varchar(100)CCCategory varchar(50)CCClass varchar(50)

DimALBProductionUnit

ProdUnitID char(2)

PUName varchar(125)PUCategory varchar(50)PUClass varchar(50)

DimARCDxClass

DXClassID smallint

DXClassName varchar(50)DXClassARC nvarchar(2)

DimARCEligibility

EligibilityID char(2)

EligibilityName varchar(100)EligibilityCategory varchar(100)

DimARCIncome

IncomeID smallint

IncomeGroup varchar(50)

Financial

DimBOC

BOCID smallint

BOCName varchar(50)BOCCategory varchar(50)BOCClass varchar(50)

Geographic

DimVISN

VISNID smallint

VISNTxt char(3)VISNName varchar(50)City varchar(75)State char(2)Zip intFIPS intFTE smallintBudget money

DimFacility3n

Sta3nID smallint

Sta3nName varchar(100)VISN smallintCity varchar(50)State varchar(2)Zip intFIPS intMCG smallintFTE smallint

DimFacility6a

Sta6aID varchar(6)

Sta6aName varchar(100)Sta6aType varchar(50)Sta3n smallintVISN smallintVASTID smallintSta6aCity varchar(100)Sta6aState char(2)Sta6aZip intSta6aFIPS intAdminParentCode intAdminParentCity varchar(100)AdminParentState char(2)AdminMCG smallint

DimFIPS

FIPSID int

State char(2)County varchar(30)VISN smallintVISNCARES smallintCARESMkt varchar(100)VetPop int

DimZip

ZipID int

State char(2)City varchar(100)

Hospital Location

DimStop

StopID smallint

StopName varchar(50)Category varchar(50)Class varchar(50)Type char(10)

DimBedsection

BedsectionID smallint

BedsectionName varchar(50)Category varchar(50)Class varchar(50)Type char(10)

Time

DimDate

DateID int

MDate smalldatetimeFYr char(4)FQtr char(6)CMth char(5)CDay varchar(30)FP smallintDoW char(3)DoM smallint

FCDM Dimensional Map

• Standardized•Type/Size conventions•Naming conventions

• Verified•“Gold” standard• Business rules

• Optimized•Primary keys•Indexed

• Refreshed

VHA Dimension MapVHA Dimension Map

VHA Corporate Data WarehouseVHA Corporate Data WarehouseDimensional ArchitectureDimensional Architecture

Conformed Dimensions

Patien

t

Provid

er

Facilit

y

Stop

Code

Bed S

ectio

n

CPTIC

D9BOC

Time

HDR.Vitals

ADR.Enroll

NPCD.Enc

PFSS.Bills

Pros.Actions

Sch.Appts

Con

form

ed F

acts

Business Process Transactions

12345, 34567, 598GA, 323, 5/1/05, BP, 140, 90

12345, 598GA, 5/1/05, 65, M, SC100, POW

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05, A123, $99

12345, 34567, 598GA, 323, 5/1/05, Wheelchair, $500

12345, 34567, 598GA, 323, 5/1/05, 6/1/05

VHA Corporate Data WarehouseVHA Corporate Data WarehouseDimensional ArchitectureDimensional Architecture

Conformed Dimensions

Patien

t

Provid

er

Facilit

y

Stop

Code

Bed S

ectio

n

CPTIC

D9BOC

Time

Business Process Transactions

HDR.Vitals 12345, 34567, 598GA, 323, 5/1/05, BP, 140, 90

ADR.Enroll

NPCD.Enc

12345, 598GA, 5/1/05, 65, M, SC100, POW

PFSS.Bills

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05

Pros.Actions

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05, A123, $99

12345, 34567, 598GA, 323, 5/1/05, Wheelchair, $500

Sch.Appts 12345, 34567, 598GA, 323, 5/1/05, 6/1/05

Con

form

ed F

acts

VHA Corporate Data WarehouseVHA Corporate Data WarehouseDimensional ArchitectureDimensional Architecture

Conformed Dimensions

Patien

t

Provid

er

Facilit

y

Stop

Code

Bed S

ectio

n

CPTIC

D9BOC

Time

Business Process Transactions

HDR.Vitals 12345, 34567, 598GA, 323, 5/1/05, BP, 140, 90

ADR.Enroll

NPCD.Enc

12345, 598GA, 5/1/05, 65, M, SC100, POW

PFSS.Bills

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05

Pros.Actions

12345, 34567, 598GA, 323, 73456, 250.01, 5/1/05, A123, $99

12345, 34567, 598GA, 323, 5/1/05, Wheelchair, $500

Sch.Appts 12345, 34567, 598GA, 323, 5/1/05, 6/1/05

Con

form

ed F

acts

Dia

bet

es D

MD

iab

etes

DM

Dia

bet

es D

MD

iab

etes

DM

SC

I D

MS

CI

DM

SC

I D

MS

CI

DM

PB

M D

MP

BM

DM

PB

M D

MP

BM

DM

Hig

h C

ost

DM

Hig

h C

ost

DM

Hig

h C

ost

DM

Hig

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ost

DM

DM – Data MartDM – Data MartDM – Data MartDM – Data Mart

Data Warehouse User ProfilesData Warehouse User Profiles

Information Information ConsumersConsumers

Information Information ExplorersExplorers

5-10% of users5-10% of users

15-25% of users15-25% of users

65-80% of users65-80% of users

AnalystsAnalysts

Robust analysis tool•Sophisticated reporting•Predictive analytics•Ranking, forecasting

Simple analysis tool•Data visualization•Simple filter/sort•Easy publishing

Simple analysis tool•Data visualization•Simple filter/sort•Easy publishing

Robust reporting tool•Access to reports•Report subscriptions •Browse/Search/View

Robust reporting tool•Access to reports•Report subscriptions •Browse/Search/View

Analytical & Reporting ToolsAnalytical & Reporting Tools

• Easy to learn and use• Latest technology• Variety• Complimentary• Standard access methods

Web Reporting

Spatial AnalysisStatistical Analysis

Systolic

Systolic

Fre

qu

en

cy

20000

10000

0

Std. Dev = 20.67

Mean = 137.4

N = 87199.00

Current Software SuiteCurrent Software Suite Operating SystemOperating System

MS Windows Server 2003 Enterprise Edition ServerMS Windows Server 2003 Enterprise Edition Server ETL EngineETL Engine

MS Data Transformation ServicesMS Data Transformation Services Database EngineDatabase Engine

MS SQL Server 2000MS SQL Server 2000 OLAP EngineOLAP Engine

MS Analysis ServicesMS Analysis Services Reporting EngineReporting Engine

MS Reporting ServicesMS Reporting Services Presentation ToolsPresentation Tools

ProClarity Analytics SuiteProClarity Analytics Suite Microsoft MapPointMicrosoft MapPoint SAS/SPSSSAS/SPSS

Portal EnginePortal Engine Microsoft SharePointMicrosoft SharePoint

Use cases…Use cases…

ProClarity ProfessionalProClarity Professional(Analyst, Information Explorer)(Analyst, Information Explorer)

Key Capabilities:•Effective ad-hoc analytic capabilities •Powerful calculation and query functionality •Advanced data visualization and navigation views

•Decomposition Tree •Perspective View •Performance Map

•Free form analytics

Key Capabilities:•Excel add-in to leverage Excel knowledge•Create high-quality, formatted business reports •Refresh information daily, weekly or whenever required •Eliminate the confusion and overhead in keeping spreadsheets current•Ties your Excel reports to a central data source

Business Reporter for ExcelBusiness Reporter for Excel(Information Explorer, Information Consumer)(Information Explorer, Information Consumer)

Web StandardWeb Standard(Information Consumer)(Information Consumer)

Key Capabilities:• Rapidly deploy analytics over the web• True zero-footprint client requiring no downloading or

installation on a user desktop • Users can consume pre-built analyses, or perform ad-hoc

analysis • Provides “Guided Analytics” to user community

DashboardDashboard(Information Consumer)(Information Consumer)

Key Capabilities:•Users can assemble KPIs and views that promote best practices for a given subject area•Groups can create personalized dashboards focusing directly on their specific KPIs and other information they need to monitor their specific area of interest•Users move quickly from monitoring KPIs into ad-hoc query mode. •Dashboards may be deployed alone or integrated within an enterprise portal solution such as Microsoft® SharePoint Portal Server•Add external content such as links to relational reports, web-based content or websites

DRG Root Cause Analysis: DRG 430 (Psychoses) is our highest volume discharge DRG. How do the medical centers in our Region compare to all other medical centers in volume and average cost/day of care for FY04?

CBOC Profile: We need to create a CBOC clinic profile that allows us to analyze cost and workload activity at each of the CBOC’s in our Region. We would also like the ability to look at cost and workload for specific disease entities.

National Program Office Issue: How many mammograms are we doing per month and what are the age ranges of the patients? Can I also look at CT and MRI procedures?

Non VA Care High Volume/High Cost Issues:What are the Regions high-cost/high volume DRGs? Where do the Non-VA Care patients live? Compare Avg. Cost/BDOC (Fee vs. VA) to assist in make-buy decisions.

Fee Inpatient Origin by County for DRGs 107 & 109Fee Inpatient Origin by County for DRGs 107 & 109

Prosthetic Issues:What percent of my prosthetics budget is spent on surgical implants as compared to the other Regions?

VHA Diabetic Patients by CountyVHA Diabetic Patients by County (One or more Inpatient or Outpatient ICD9 = 250.xx)(One or more Inpatient or Outpatient ICD9 = 250.xx)

Pts by County

10,000 to 99,999

1,000 to 9,999

100 to 999

10 to 99

1 to 9

Region 21 Diabetic Patient CostRegion 21 Diabetic Patient Cost(VA + Non VA)(VA + Non VA)

VISN 21 FY04 Diabetic Cost Statistics

23184 23184 23184

0 0 0

$3,224 $506 $3,731

$1,236 $0 $1,304

$0 $0 $28

$8,122 $5,117 $10,237

-$116 $0 -$62

$219,175 $474,498 $525,643

$599 $0 $625

$1,236 $0 $1,304

$2,697 $0 $2,923

Valid

Missing

N

Mean

Median

Mode

Std. Deviation

Minimum

Maximum

25

50

75

Percentiles

VACost FeeCost TotCost

CostPt by County

$3,724.00 to $48,109.00

$2,450.00 to $3,723.00

$1,650.00 to $2,449.00

$1,012.00 to $1,649.00

$620.00 to $1,011.00

$288.00 to $619.00

$108.00 to $287.00

$1.00 to $107.00

Human Resource Issues:What percentage of my nurses are eligible to retire? How does that compare with other Regions?

Quality Control:Quality Control:Data Completeness ReportData Completeness Report

Highlightmissing or

inconsistentsource data

Next steps…Next steps…

Longitudinal Data Mart Longitudinal Data Mart DevelopmentDevelopment

Inpatient Discharg

es

Outpatien

t Encoun

ters

Radiolog

y Pro

cedures

Account Level B

udgeting

Inpatient Tre

ating S

pecialty

Lab R

esults

Pha

rmacy F

ills

Non V

A C

are

830 R

eport

887 R

eport

Em

ployee Surveys

PA

ID

Natu

re of Action

Long T

erm C

are (R

AI/M

DS

)

Patient Demographics

Facility Demographics

Chart of Accounts

ICD9 Reference

Time

Workload Non VA Finance HR Other

Composite Inpatient/Outpatient Data Mart

Disease Specific Data Marts (Diabetes, Heart Disease, Mental Health)

Cohort Specific Data Marts (OEF/OIF)

Performance Measure Data Mart

Composite Inpatient and OutpatientComposite Inpatient and Outpatient

Diabetic Population AnalysisDiabetic Population Analysis

High Risk Patients

Details of the 20 Denver patients(1) Last A1C > 9

(2) Last Glucose => 140

Age Range

High Risk Diabetic AnalysisHigh Risk Diabetic Analysis

Personal Delivery of InformationPersonal Delivery of Information

•Performance Measures•Special Measures (MI)•Exception reporting•Clinical reminders/alerts•Event reporting•Designed to display on mobile devices (e.g.Blackberry)

Geographic Information SystemsGeographic Information Systems

Legend:

VA HospitalVA Clinic

Additional:• Puerto Rico• Hawaii• Alaska• Philippines

CustomizedBI

Portal

Ultimate Goal: Centralized BI Ultimate Goal: Centralized BI PortalPortal

ResourceResourceManagementManagementResourceResourceManagementManagement

ExceptionExceptionReportsReports

ExceptionExceptionReportsReports

VA/VHAVA/VHANewsNews

VA/VHAVA/VHANewsNews

PerformancePerformanceManagementManagement

ScorecardScorecardReportsReports

ScorecardScorecardReportsReports

Policies &Policies &ProceduresProceduresPolicies &Policies &

ProceduresProcedures

DiseaseDiseaseManagementManagementDiseaseDiseaseManagementManagement

Government & Government & Industry NewsIndustry NewsGovernment & Government & Industry NewsIndustry News

Current ChallengesCurrent Challenges

ScaleScale Subject area isolationSubject area isolation Tool availabilityTool availability Cube architectsCube architects Organizational culture (tipping point?)Organizational culture (tipping point?) Source data formatSource data format SSN level access and securitySSN level access and security Data qualityData quality Timeliness of dataTimeliness of data TrainingTraining

Next Six MonthsNext Six Months

Roll out ProClarity EARoll out ProClarity EA User Education and Training (w/ Analysis)User Education and Training (w/ Analysis) Continue Refining ProcessesContinue Refining Processes Continue Product Creation and Refinement Continue Product Creation and Refinement

(primarily cubes)(primarily cubes) Clinical Data Marts (Diabetes, Mental Health)Clinical Data Marts (Diabetes, Mental Health) Cultivate Existing Partnerships (DSS,ARC, Cultivate Existing Partnerships (DSS,ARC,

OQP, etc.)OQP, etc.) Establish Knowledge Sharing Framework (e.g. Establish Knowledge Sharing Framework (e.g.

SharePoint)SharePoint) Data Quality ControlData Quality Control

Next Eighteen MonthsNext Eighteen Months VISTA Reengineering ProjectsVISTA Reengineering Projects

Health Data RepositoryHealth Data Repository SchedulingScheduling BillingBilling

Common BI InterfaceCommon BI Interface SharePoint basedSharePoint based

ProClarity Web web partsProClarity Web web parts ProClarity Dashboard web partsProClarity Dashboard web parts Reporting Services web partsReporting Services web parts GIS web partsGIS web parts

Expanded Statistical AnalysisExpanded Statistical Analysis Predictive modelingPredictive modeling

Direct Query AccessDirect Query Access Power usersPower users Research communityResearch community

Questions?Questions?