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PADDI:A Business Intelligence and Data Quality platform

for Piedmont health

Giuliana BonelloBusiness Intelligence & Data Quality Practice Manager, CSI-Piemonte

Veronica BertiHealth expert, Health Division, CSI-Piemonte

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Polytechnic of Turin

University of Turin

Piedmont Region

Founded in 1977 by: 91 Associated Consortium

Members 176 Millions € annual

revenues 6 sites in Piedmont 1,200 employees

CSI-Piemonte is a leading ICT company (among the biggest 20 Italian companies in the ICT sector), providing with services

all segments of the public sector

Who We Are

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technologies and architectures

document management and related laws

policy making support systems

mission, organisation, business models of different PA bodies

Web sites and portals for thePublic Administration

Cross-Authority-Databases and Business Intelligence applications

Training for civil servants

more than more than 4 million4 million hits hits every dayevery day

more than more than 110 services110 services are availableare available

Expertise

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Since 2005 CSI is actively involved in promoting its international presence both through EU Initiatives and External Cooperation Policy Measures:

Relations and cooperation with our local Public Authorities and in cooperation with ICT partners of our territory (Think up project), promoting our best practices

International relations with donors (EC,WB,UN…). Relation with Italian Ministries (Foreign Affairs, Public

Administration, Environment, Health…) and for cooperation programme

Awarded projects: 45

International activities

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A SAS customer in Italy for more than 30 years

SAS top customer at European scale for variety of tools used

A pool of skilled staff on SAS technology

A SAS competency centre (since 2004)

One of the first companies signing the accreditation process to the EMEA Professional Services Partner Program

The owner of a SAS R&D laboratory set up with Piedmont Region

Relationship with SAS

CSI-Piemonte is the Winner of the Enterprise Intelligence Award for the PA at the SAS Forum 2007 in Stockholm.

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How Many Databases Today in Piedmont PA?

Data update September 2010Data update September 2010

TOTALPA CUSTOMER DECISION MAKING OPERATIONALPiedmont Region 108 854 962 Municipality of Turin 33 197 230 Province of Turin 6 123 129 Others 13 137 150 TOTAL 160 1.311 1.471

TYPE OF DB

PA CUSTOMER TABLES DBPiedmont Region 68.838 962 Municipality of Turin 25.065 230 Province of Turin 14.649 129 Others 25.392 150 TOTAL 133.944 1.471

Topics DB

Environment and territory 324

Institutional activities 212Education, culture and free time 62

Health-care systems 172Productive activities and work-related topics 362

Development and management of human resources

376

TOTAL 1.508

2005 2008 20090

200

400

600

800

1000

1200

Regione PiemonteCittà di TorinoProvincia di TorinoAltri

Data base growing

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Data Knowledge Decision

Knowledge

Territory and Environment (324)Institutional activities (212)

Educational, culture and free time (62)Health-care systems (172)

Producing activities and work-related topics (362)Human Resources (376)

DemographyLand

Register and TaxesAgricultureLabour

Internet and ICT

DA

TA

DA

TA

DA

TA

DA

TA

DA

TA

Information Decisions

DA

TA

Operational Data

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BICC Organizational History

19801990

2000

1st DW project(Piedmont region)

2005

2010

From BICC to PSI-CC:BI & DQ

Statistical center(mainframe)

Towards I-PSI-CC

BICC

DQ

First BICC phase:Centralisation for all customers

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BICC Business model

INFRASTRUCTURE

SOFTWARE

DATA

B I C C

PA Institution 3PA Institution 2

PA Institution 1

PA Institution 4

METADATA

APPLICATIONS

All inclusive project dev.Central server farm

Framework contract for all stakeholders

Common “Core” functionsSpecific applications

Single data and service catalogueBI Metadata are partitioned

between the large customers

Single coding tablesMaster Data for each customer

All inclusive service

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BI&DQ applications

2001 2003 2005 2006 2007 2008 20090

100

200

300

400

500

600

0

100

200

300

400

500

600

Città di TorinoRegione PiemonteTolali enti

BI applications growing

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Decisional Service Pyramid

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Health numbers in Piedmont

Administrative levelsHealth Ministry

Regional Government

Epidemiology research

13 Local Health Agency

8 Hospital Agency

4,5 million residents

4,000 doctors

19,000 beds in hospital

35 million prescriptions per year

66,5 million of professional medical services per year

800,000 hospitalizations

37.000 births per year

22 local health units

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The decisional pyramid for health: PADDI

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Information needs

Monitoring & Evaluation

Analysis of single health sector field

Management control/budgeting

Epidemiological studies

Clinical trials

Operational DB

1 2

Back-end Front-endEnterprise DWH

1) Extraction, Transformation and Loading (ETL)2) Data Warehouse (anonymous data)3) Front end (with authentication & profiling)

3

DW processes

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•The SSN set up in 1978 guaranteees health care for all citizens.•It is mainly financed through the general taxation but the regions are obliget to keep under control the health care expenses by ensuring effectiveness of treatments.

Very rich health information heritage Use of instruments of business intelligence

WH

YH

OW

Ensure the effectiveness of treatments by controlling the costHighlight critical areas

WH

AT

OUTCOME RESEARCH

Goals

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Health personnel

Assistiti

Territorial activities

Prevention activities

Hospitalactivities

Health agency

Health information heritage of the Piemont Region

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Type of Process

Visualize Explore Discover

Dashboard

Query / Reporting

Data Mining

Time

OLAPMultidimensional

analysis

From information to knowledgeUsers

Employees

Middle managers

Analyst

Managers

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Growth curve of knowledge

How to optimize the results?

What will happen?

Why it happened?

What it happened?

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Reporting

Monitoring

Analysis

StrategyStrategy FormulationFormulation Resource

Allocation

Data Quality

Action plan Data Quality Data Quality improvementimprovement

Mining

From strategy to data analysis

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OUR GOALS

Epoetine

Linee

Guida

Ipertens

DiabeticiFatt Coag

Aura

Biologici e

AR

Some example

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Data Anonymize engine

4.457.335 Residents 31/12/2010

Data Quality

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Planning/ Management Control

Doctors – District BudgetPatients

Structures

Dru

gs

Hos

pita

lizat

ion

Emer

genc

ies

Sala

ries

Hea

lth C

entr

es

Add

ictio

ns

Boo

king

Scre

enin

g

Trai

ning

Abs

ence

Pres

ence

Hom

e C

are

StructuresHealth Personal - Doctors

Patients

TransversalData mart

Sectorial Data mart

RegistryData mart

Query / Reporting

Data MiningOLAPMultidimensional

Analysis

Institution: •Region•Health agenciesType of user: •Analyst

Drugs and Chemistries Decisional SystemIndicator System

Directional Dashboard

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Goals:Implementare l`uso di epoetine biosimilari nei soggetti nefropatici naive per la dialisi.

DB :Medical visitDrug informationDrug administration

Biosimilar epoetinDashboard

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DB coinvolti:•Pathology`register•Medical visit•Hospitalization•Drug administration

Goals:Determinare se una migliore aderenza alla terapia farmacologica corrisponde una minore spesa per assistenza ospedaliera.

Dashboard Diabetics

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DB coinvolti:•Rares Diseases Register•Personal data of assisted•Drugs administration

Goals:Individuare soggetti che assumono fattori di coagulazione off label.

Dashboard Clotting factors

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Biological medicines are particularly expensive; their profiles of safety ad efficacy are not full Known.Ensuring effectiveness of treatments and keep under control the health care expenses

Pathologys` registerHospitalization, drugs` administration pathologys` register

WH

YH

OW

Ensure the effectiveness of treatments by controlling the costHighlight critical areas

WH

AT

Limited the prenscription only by Hospital doctors.

Biologic drugs for rheumatoid arthritis

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Data Mining

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Guide lines for the treatment of HypertensionThe iue of drugs` association only on risk` subject (comorbidity)

Drugs administration data

WH

YH

OW

Compliance with guide lines

WH

AT

Azione di richiamo dei medici prescrittori che non hanno rispettato le indicazioni delle linee guida.

Hypertension’s treatment

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Pazienti a rischio

Data Mining

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Thank you for your attention!

Giuliana Bonellogiuliana.bonello@csi.it

Veronica BertiVeronica.berti@csi.it

www.csipiemonte.it/eu

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