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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 [email protected]
Veronica [email protected]
www.csipiemonte.it/eu
© CSI-Piemonte – Tutti i diritti riservati
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