This presentation highlights CSI experience on the PADDI Program. The project is the integration of all data belonging to health management systems into a Enterprise Data Warehouse. This integration is the result of the implementation of data cleansing services and decisional systems and it enables regional health authorities to appropriately supervise health policies within their territories
PADDI - A business intelligence and data quality platform for Piedmont health
1. PADDI: A Business Intelligence and Data Quality platform for Piedmont health Giuliana Bonello Business Intelligence & Data Quality Practice Manager, CSI-Piemonte Veronica Berti Health expert, Health Division, CSI-Piemonte
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6. How Many Databases Today in Piedmont PA? Data update September 2010 Data base growing
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8. BICC Organizational History 1980 1990 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
9. BICC Business model INFRASTRUCTURE SOFTWARE DATA B I C C PA Institution 3 PA Institution 2 PA Institution 1 PA Institution 4 METADATA APPLICATIONS All inclusive project dev. Central server farm Framework contract for all stakeholders Common “Core” functions Specific applications Single data and service catalogue BI Metadata are partitioned between the large customers Single coding tables Master Data for each customer All inclusive service
12. Health numbers in Piedmont Administrative levels Health 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
16. Hospital activities Health information heritage of the Piemont Region Health personnel Assistiti Territorial activities Prevention activities Health agency
17. OLAP Multidimensional analysis From information to knowledge Users Employees Middle managers Analyst Managers Type of Process Visualize Explore Discover Dashboard Query / Reporting Data Mining Time
18. Growth curve of knowledge How to optimize the results? What will happen? Why it happened? What it happened?
19. Reporting Monitoring Analysis Strategy Formulation Resource Allocation Data Quality Action plan Data Quality improvement Mining From strategy to data analysis
20. OUR GOALS Epoetine Linee Guida Ipertens Diabetici Fatt Coag Aura Biologici e AR Some example
23. Goals: Implementare l`uso di epoetine biosimilari nei soggetti nefropatici naive per la dialisi. DB : Medical visit Drug information Drug administration Biosimilar epoetin Dashboard
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26. 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` register Hospitalization, drugs` administration pathologys` register WHY HOW Ensure the effectiveness of treatments by controlling the cost Highlight critical areas WHAT Limited the prenscription only by Hospital doctors. Biologic drugs for rheumatoid arthritis
28. Guide lines for the treatment of Hypertension The iue of drugs` association only on risk` subject (comorbidity) Drugs administration data WHY HOW Compliance with guide lines WHAT Azione di richiamo dei medici prescrittori che non hanno rispettato le indicazioni delle linee guida. Hypertension’s treatment
Good morning. My name’s Giuliana Bonello and I’m Product Manager of Business Intelligence & Data Quality Solutions in CSI-Piemonte. I’m very pleased to be here today. I share the speech with my colleague V.Berti, who is in charge of the Health division. She is a pharmaceutical and health care expert. The aim of our presentation is to give you an overview of PADDI, the business intelligence and data quality platform realized in Piedmont to support health systems.
CSI-Piemonte is a Public Consortium with a public right legal entity status, that operates in the Piedmont Region, located in Northern Italy. We are a leading ICT company, providing with services all segments of the local public sector – from health care to commerce & industry, from cultural heritage to administrative systems, from agriculture to territorial systems. Established in 1977 at the initiative of the Region of Piedmont, the University of Turin and the Polytechnic of Turin, we had a huge and steady growth along these decades. We are presently a consolidated company, with 91 partners that over the years have joined the consortium, including, besides the founding partners, the City of Turin, all the provinces of Piedmont, local councils and associations, health care offices, hospitals and government agencies
The role of the Consortium is being a key instrument for Piedmont public sector reform, through the interaction and the interchange of data between the public information systems on the Public Administration Network. Our mission is the setting up of the “Piedmont System” for the implementation of administrative decentralization using ICTs, based on a cloud idea. we act following a systemic approach, in order to promote: the cooperation among different local government; the knowledge sharing ; the internal process innovation and optimization ; the setting up of broadband infrastructure of the territory; the shared supply of on line services ; the promotion of and the cooperation with the business sector. Thanks to our expertise, public administrations can achieve economies of scale and rely on the top-class skills of professional consultants .
The value added by the consortium is also exported beyond regional borders through joint projects promoted in Italy and abroad, promoting the reuse and transfer of best practices to other regions and local administrations. At international level we have managed several research and development projects and also cooperation projects.
Our company has been working with SAS for 30 years. We received the Enterprse Intelligence Award for the Public Sector at the SAS Forum 2007. CSI-Piemonte was selected for its wide range of BI applications supporting the Piedmont local institutions, its innovative use of SAS technologies and solutions and the setting up of the Business Intelligence Competency Centre .
The catalogue of data and services provided for the members of the consortium makes it possible to draw a costantly upgraded picture of the existing data bases. We supports and maintains more than 1,400 databases for our members and 180 of those are datawarehouses
With so many databases, you can understand the importance of Business Intelligence (BI) solutions to support the business decision making processes of our customers. The Consortium manages the Piedmont Public Sector Data Governance Program, through the normalization of existing data banks, the promotion of the data sharing and the design and development of new integrated data banks, like population and enteprises registries, making them available and usable overall in the network, the reuse of BI solutions.
So we set up a Business Intelligence Competency Centre . This figure show the history of our BICC, from the eighties till now. The roots of the Competency Center date back to the 80’s, the first years in which the Consortium began its activity. During the ‘mainframe’ period we had, on one hand a support center on statistical aspects for the university researchers , and on the other hand, some experts that produced statistical reports for the members of the consortium in mainframe environment. The statistical experts were gradually grouped into a single unit from 1990 The first Datawarehouse project that crossed all areas was launched in 1996 for the Piedmont Region , to try and give a more homogenous approach to the different existing applications In 2000 we decided to converge to a single infrastructure both the hardware and the softwares of our 3 main customers, beginning the transfer of all applications from a client-server architecture to web architecture. The concept of BICC emerged from 2001 to 2005, with the extension of the overall DW project also to the Municipality of Turin. From 2006, the BICC was extended to the treatment of operational data and master data and was thus gradually transformed into a PSI-CC (Public Sector Information). From 2009, we launched an overall Data Governance initiative . Now we are experimenting some semantic aspects (like a semantic engine) and we are extracting knowledge from different typologies of data (texts, images, etc.) , so we are heading towards an I-PSI-CC (Intelligent PSI Competency Center)
The competency center works for all our associated institution. It is based on five layers a common hardware and network infrastructure A shared software layer for BI&DQ solutions. We have a Framework contract for all stakeholders. The layer of data: some basic information is shared between all the entities (eg coding tables). Each institution and sometimes all areas of Business has a blueprint for the construction of the overall Data Warehouse structured in different levels (the BI pyramids that we will see later), A Metadata layer: There is a single asset register for all customers, related to data and IT services, including business information and technical information. For data and decision-making applications , this catalog is partly fed by the BI metadata repository. The technical and business metadata in the BI are partitioned for large customers. BI & DQ applications : We Have carried out some transversal functions common to all customers and sometimes we share BI applications between different local governments
In the period 2005-2010 as you can see in this graph, the number of BI applications has grown significantly.
In this slide you can see a general blueprint for the construction of the overall Public Sector Data Warehouse, structured in different levels The basic layer, relating to the operational level, includes all the “operating” components of the sub-systems of the Information System of a certain Local government and the external data sources, that create as a whole, the original data sources. The decisional level is divided into two parts: The information layer for the middle management based on reporting and analytical function The information layer for the top management based on dashboard and gauge function
And now we go deep into the health world. In this slide we collected some significant numbers relating this topic in Piedmont so you can have a general overview.
After 10 years of different and specific BI application development for the Piedmont health government agencies, in 2009 the Piedmont Region adopted a comprehensive approach for Health regional Data Warehouse, gradually evolving to a complex integrated platform. After a feasibility study carried out in 2008, we began the setting up of the information – decisional layer (Data Warehouse) following this blueprint, named PADDI Program . The project is the integration of all data belonging to health management systems into a Enterprise Data Warehouse. This integration is the result of the implementation of data cleansing services and decisional systems and it enables regional health authorities to appropriately supervise health policies within their territory.
The goal is to answer to different information needs with this integrated platform. And now I introduce Veronica Berti, that will explain some detailed experience based on this platform.
I servizi decisionali devono quindi fornire diverse funzionalità di analisi a seconda del tipo di utente a cui sono indirizzati e della richiesta che devono soddisfare in base anche al tempo che si ha a disposizione
I’d like to thank you for your attention. I hope you found our presentation interesting. If you have any questions, we’d be happy to answer them. Please, use the mail addresses showed in this slide to send us your questions.