Initiative Overview January 16, 2018
Contents Opening Remarks Introduction Program Overview Project Overview Interagency Coordination Project Expectations for Agencies Q&A 2
“Expand and enhance predictive models and profiling models to determine those at-risk for infant mortality in Ohio and design targeted interventions” - State of Ohio Infant Mortality RFP 3
Program Overview 4
Ohio Resident Live Births 5
Infant Mortality, Ohio & US, 2007 - 2016 9 8 7.9 7.4 7.7 7.7 7.7 7.7 7.57 7.4 rate per 1,000 live births 7.2 7 Ohio 6.8 6.8 6.6 6.4 6.2 6.1 6 6.0 6.0 5.9 5.8 United States 5 4 3 2 1 0 Data Sources: Office of Vital Statistics, Ohio Department of Health and the National Center for Health Statistics 6
Ohio Infant Mortality Rate by Race 2007-2016 7
Infant mortality, US, Ohio, OEI County, 2007-2016 OEI Counties 10 9.2 9.2 8.9 8.9 8.7 8.7 8.6 8.6 8.5 8.5 8.4 8.4 8.3 8.3 rate per 1,000 live births 8.2 8.2 8.2 8.2 8.1 8.1 Ohio 7.7 7.7 8 7.4 7.4 6.7 6.8 6.5 6.3 6.3 6.6 6 6.5 6.4 6.1 United States 5.4 Non-OEI Counties 4 2 Data Sources: Office of Vital Statistics, Ohio Department of Health and the National Center for Health Statistics Note: Categories are not mutually exclusive (e.g., United States includes Ohio) Overall infant mortality has significantly decreased from 2007 to 2016 in the US, Ohio as a whole, all OEI counties combined, or all OEI cities combined, but not all non-OEI counties combined. 0 8
Ohio Infant Mortality Numbers by Race 2016 9
Ohio Infant Deaths 2016, n=1024 • by OEI County Death Rate per 1,000 Number of Deaths 10 8.7 8.7 9.1 9.0 31 128 7.5 8 7.3 6.9 6.8 6.5 6 Non-OEI Counties 418 165 4 2 98 0 Butler Cuyahoga Franklin Hamilton Lucas Mahoning Montgomery Stark Summit Other Ohio 45 41 45 38 15 Butler Cuyahoga Franklin Hamilton Lucas Mahoning Montgomery Stark Summit 10
Causes of Infant Death in Ohio (2016) 11
Contact Information Sandra Oxley Chief, Maternal, Child and Family Health Ohio Department of Health (614) 728-6861 Sandra.Oxley@odh.ohio.gov 12
Initiative Core Components Taking Ohio to where it needs to be in the 21 st Century by em embracing tec echnology (H.B. #49 Sec. 125.32) Data Sharin Da ing & Data Analytics Da Clo Cloud Co Compute & Pre-Qualifie ied Vis isual l Analyti tics Analytic ics Support Servic ices Storage Analytic ics Fir irms Pla latf tform The State provides access The State provides access The State has a highly Visual analytics and The State supports the to cloud compute and to pre-qualified firms with secured hosted analytics interactive dashboards are tools and hybrid data storage for analytical expertise in data analytics platform inside the State provided out of an platform, supports data projects as part of a hybrid & machine learning across data center featuring enterprise service based on staging and curation, and cloud/on-prem strategy 14 functional domains industry leading tools for Tableau software provides scope and secure data sharing and procurement services analytical workloads 13
Analytics Model Descriptive Diagnostic Predictive Prescriptive Analytics Analytics Analytics Analytics • • • • Explains what Explains why Explains what will What should the business happened something happened happen do? • • • • Dashboards, reports, Data discovery and Forward- looking KPI’s Suggest best actions to data correlations and insights meet a desirable outcome • • • • Identify clusters based Understand causes Predict behavior of this Typical of streaming, on some variables set at a future point in machine-learning, & AI time 14
Project Overview 15
T eam Organization Accenture Advisory Team Engaged throughout. Analytics Lead Cri Critic ical l Su Success Fact actors State Clinical Domain SMA(s) • Help us access data and expertise SME(s) • Guide our analysis, share past learnings State Analytics Domain EXECUTIVE SMA(s) SME(s) • Help us focus on the right data and STEERING COMMITTEE context • Review outputs and contribute DELIVERY TEAM State State insights Policy Data Staff Experts Accenture Data Scientists Heavy onboarding w/ SQL, existing reporting, data, context Heavy lifter as findings emerge. Analytics Analytics Public Health, Social Services, Pod A Pod C regional, data sets Analytics Pod B State of Accenture Accenture Ohio Data Science Advisory 16
Scope of Work KEY QUESTIONS KEY MODELS Evaluating Efficacy of State Intervention Which mothers and infants are Programs most at risk of infant death? Identifying Mothers at High Risk of Infant Which families are most likely to Mortality and Constructing Their Profiles benefit from targeted interventions? Predicting the Characteristics of Mothers Most Likely To Benefit From An Intervention Program Which families are most likely to participate in targeted interventions? Predicting Which Intervention Program(s) At- Risk Mothers Should be Enrolled In Which intervention programs yield Identifying Mothers Most At-Risk of Having a the best return on investment? Baby that will Require a NICU Admission 17
Approach DATA DISCOVERY AND VALIDATION Fusin Fusing Da Data Se Sets ts to o Build Build No Novel l Vi Views • Data sets and understanding are validated in 2-way conversation with State SMEs Targeted CREATION OF THE • I ntervention Data are joined into an analytics MODELING ANALYTICS RECORD record with normalized data, for Roadmap modeling purposes • Segmentation and Profiling to compare apples to apples • Models are built per segment, in priority order SEGMENTATION AND PROFILING 18
Timeline MILESTONES MIL S AN AND CH CHECK-INS Data documentation All data accessed, validated, Milestone Checkpoint Milestone Checkpoint Coll ollaboratio ion wi with th Final readout to obtained, weekly bi-weekly touchpoints with with Executive with Executive executive leadership State Exp Experts to to bui build ld touchpoints with SMEs Policy Staff and Data Experts Steering Committee Steering Committee da data unde understandin ing 1/16 2/28 3/15 4/15 6/15 Analysis & Report: Analysis & Report: Analysis & Report: Kickoff Analysis & Causes & Profiles and Efficacy Analytical Models Report: Comparative Characteristics ACTI TIVITIES MOBILIZATION DATA DISCOVERY ANALYTICS RECORD SEGMENTATION AND PROFILING MODELING TARGETED INTERVENTION ROADMAP DEC 2017 JAN 2018 FEB MAR APR MAY JUN 19
Keys T o Success MOVING BEYOND THE EXPLORATORY AND THE ACADEMIC INDUCTIVE REASONING AND EVIDENCE-BASED INTERVENTIONS STATE PLANNING DRIVING LOCAL IMPACT 20
Interagency Coordination 21
Executive Steering Committee • Monthly Meetings • Receive updates on project • Remove roadblocks • Assess policy implications • Each participating agency will have a representative 22
Ohio Department of Health Lead agency • Coordinate with Accenture and participating agencies • Provide overall direction for project in conjunction with the Executive Steering Committee • Ensure project scope is complete • Ensure project goals are met • Deliverables are completely timely • Procurement and vendor payment • Communicate project status to stakeholders • Participating agencies • Governor’s Office 23
Department of Administrative Services Supporting agency • Stand up and maintain data lake platform • Work with agencies to receive and ingest data into the data lake • Ensure platform security • Provide data lake access when authorized • Technical support for participating agencies and Accenture • Guidance to all involved parties 24
ODJFS, ODM & OhioMHAS Participating agencies • Legal review of relevant data to determine what can be contributed • Submit data to OIT for inclusion in data lake • Provide subject matter experts for included datasets to share knowledge on: • Provide a point person to Accenture, ODH, and DAS to guide requests to the right individuals • Be engaged and part of the team throughout the project • Feedback on project direction • Timely responses 25
Legal Aspects: Memorandums Of Understanding • Types of Agreements: Business Associate Agreement, Data Use Agreement, or similar agreement • Structure: • Business Associate Agreement between DAS and the respective agency • DAS’ role: Hosting and managing all of the agencies’ information • Multi-party Business Associate Agreement or Data Use Agreement between ODH, Accenture (vendor) and respective agency • ODH’s role: Managing agency of the vendor, Accenture • Accenture’s role: Vendor accessing the information to perform the work under this project • Purpose: Establish each party’s role and obligations with respect to this project • Agency’s information shall be used and disclosed only for the purposes of this project • Include applicable federal, state and local requirements to safeguard the confidentiality and security of the agency’s protected information 26
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