Business Intelligence and Data Sharing Bill Engle – Project Coordinator for Data Warehousing Illinois Department of Healthcare & Family Services 3/16/2018 Illinois Healthcare & Family Services 1
Introduction n n 3/16/2018 Project Coordinator sinception of IDPA MDW in 1999 Led a team in Developing the Proof of Concept Pilot Led the effort to bring in vendors for in-house demos of DW strategies Led the evaluation team in choosing System Integrator Illinois Healthcare & Family Services 2
What I Am Going to Show You Today n n n 3/16/2018 Overview of the HFS Medical Data Warehouse project Examples of queries reports The expansion to include Public Health and Human Services data Applied Business Intelligence tools Lessons Learned Illinois Healthcare & Family Services 3
analysis 3/16/2018 Illinois Healthcare & Family Services 4
Project Overview n n n 3/16/2018 Phase I u 3 years of claims loaded initially u Build to 5 years from FY ‘ 97 u Phase I reports replicated existing mainframe MARS reports (i. e. Balance, Expenditure reports etc. ) u Implemented in 9 Months Phase II u Expanded hardware platform u Continued loading claims u Developed EIS Current Expansion u Details Later Illinois Healthcare & Family Services 6
Data Warehouse Configuration Circa 1999 3/16/2018 Illinois Healthcare & Family Services 7
Data Warehouse Configuration Circa 2007 3/16/2018 Illinois Healthcare & Family Services 8
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EIS MERA
TDWI Best Practices Report 1 st Quarter 2007 Predictive Analytics: Extending the Value of Your Data Warehousing Investment By Wayne W. Eckerson 3/16/2018 Illinois Healthcare & Family Services 11
Query/Report Types n n n Ad Hoc Operational Strategic Analytical Predictive
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Current Expansion n n Including data from IDPH and IDHS Expanding analysis to include Quality of Care for u u u n n 3/16/2018 Maternal & Child Health Chronic Diseases Preventative Maintenance Moving from Retrospective to Prospective analysis Devising Proactive Strategies based on merged datasets Illinois Healthcare & Family Services 20
Benefits of Integrating Health Data n n n Match services to outcomes, e. g. , Compare maternal support services rendered to pregnant women to birth outcomes contained in vital records data Use vital records data to assist in identifying the potentially eligible population for WIC Link lead screen records to Medicaid beneficiaries to determine Medicaid status and aid in reporting both for Medicaid and lead screening What is the impact of chronic disease (diabetes, asthma, cardiovascular disease, cancer, etc. ) On the population of Illinois? Match children with positive metabolic screens to immunization data, particularly children who have been identified as having sickle cell anemia, to assure that they are receiving their immunizations since they are at an increased risk of infection 3/16/2018 Illinois Healthcare & Family Services 21
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Lessons Learned n n n 3/16/2018 Atomic level data is key This technology lets you investigate issues iteratively in a timely fashion Working from a position of knowledge allows you to issues and make informed decisions rather than educated guesses Marrying advanced analytics with a statewide health info repository has the potential to drive decision making statewide Result is a win both in terms of improved health outcomes and state cost Illinois savings Healthcare & Family 25 Services
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