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Accessing and using statistical information from Ohio’s VS system OPHA Vital Statistics Conference October 12, 2011 Jo

Accessing and using statistical information from Ohio’s VS system OPHA Vital Statistics Conference October 12, 2011 John Paulson Center for Public Health Statistics & Informatics Ohio Department of Health. Ohio Vital Statistics. Rich source of information on vital events.

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Accessing and using statistical information from Ohio’s VS system OPHA Vital Statistics Conference October 12, 2011 Jo

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  1. Accessing and using statistical information from Ohio’s VS system OPHA Vital Statistics Conference October 12, 2011 John Paulson Center for Public Health Statistics & Informatics Ohio Department of Health

  2. Ohio Vital Statistics Rich source of information on vital events. Provides important statistical measures used in public health.

  3. Ohio Vital Statistics: Births Newborn medical and demographic information Mom’s demographics Prenatal care, delivery, and after delivery information Pregnancy Risk factors Selected characteristics of the Father

  4. Ohio Vital Statistics: Selected Birth Data Birth date Birth location Prenatal care info Type of birth Race, ethnicity Education Abnormal conditions of the newborn Hospital Reg. Number Place of birth • Medical Risk factors • Method of delivery • Mom’s age, race, ethnicity • Gestation • Gender • Birth weight • Father’s age, race, ethnicity • Mom’s marital status 4

  5. 415,000 vital events per year Births

  6. 2011 Ohio occurrence births and deaths available for analysis as of 10/08/2011 Data are getting to us rapidly Deaths lag a bit behind births

  7. 2008-11 Ohio occurrence births by month of birth (2008-9 final, 2010-11 as of 10/08/2011) Annual birthing cycle Decline in Ohio births

  8. 2010 and 2011 Ohio occurrence births Approximately 2,000 fewer births Jan-Aug in 2011

  9. Births per 1,000 women, by ageOhio, 1990-2009 Putting birth events in a population perspective Nearly 50% decline! <15

  10. Diabetes association with NICU admission and heavy birth weight, Ohio, 2009 Cross-tabulation of one variable against another Percent Singleton births

  11. Ohio births occurring in weeks 36-38, and same without indication for induced delivery All 36-38 week deliveries Data provided to Ohio Perinatal Quality Collaborative

  12. Prenatal care timing component data:Missing data in first prenatal visit and menses, 2010 and 2011 Effort to minimize missing data values

  13. House Bill 197 Hospital Compare website • Three indicators are calculated from birth certificate file • Antenatal steroids • CS among low risk women • Appropriate level of care of very low birth weight babies • Presented on the public Hospital Compare website. • Started data collection from hospitals in October, 2009 for the items that are not BC derived • First display of data went public Jan 1, 2010

  14. IPHIS Hospital ID: B090 Hospital: Sample hospital Hospital Volume Statistics Number of births in IPHIS to date: 4409 Percent of Ohio births in IPHIS: 3.2 Hospital's rank among hospitals: 5 Missing Value Statistics Indicator No. missing Percent missing OH-wide missing % Rank 1st Pren. visit dt 1760 39.9 6.3% 1.0 Number visits 1483 33.6 11.3% 4.0 Mom height/weight 461 10.5 8.2% 20.0 WIC status 49 1.1 1.1% 15.5 Prev. pregnancies 113 2.6 1.0% 7.0 Summary statistics Total missing values in this hospital: 5566 Total missing percentage in this hospital: 14.00 Missing values per birth in this hospital: 1.26 Rank: 1=most missing 122=least missing: 5

  15. Ohio Vital Statistics: Deaths Decedent demographic information Decedent medical information Decedent birth location information Decedent armed forces information Decedent burial information

  16. Ohio Vital Statistics: Selected Death Data Death date Birth date Injury type and date Race, Hispanic ethnicity Age, gender Place of death Marital status Education Place of residence Place of occurrence Cause of death Place of birth Branch of service Disposition type Certifier, type Injury place Hospital of death Filing date

  17. Sleep related deaths by location of infant at time of death Child Fatality Review annual report, Ohio Department of Health

  18. Place of residence for African American infant deaths (dots)drawn over census tract poverty levelHamilton County, Ohio, 2003-2006

  19. Data warehouse overview

  20. Problem Statement: Data are not accessible Data are not timely Business Intelligence is not available to support public health policy decisions Key performance indicators (KPI’s) are not available to drive operational efficiencies Data and analytic tools are not transparent and do not support a self service model

  21. The Present Landscape: Average Age of Data available: ● Public: 5 1/2 years old ● Secure: 7 years old • Represents less than 5% of ODH data • Too labor intensive to update data even annually • Scalability concerns • End-of-life technology

  22. Vision of the OPHIW: • Maximize timeliness, efficiency, scalability, functionality and user friendliness • Provide a “one-stop shop” where ODH data is accessible in a consistent manner • Both Secure and Public views • Near real time access to preliminary data using a federated model. • More timely data for better decision support • Include shared analytic and GIS tools

  23. Business Case: • Consumable data = transparency and innovation ODH Perspective • Manual data processing reduced • Enterprise scalability • Elimination of duplication of effort • Health transformation/ State agency partnerships • HIE readiness LHD Perspective • Data accessibility • Data timeliness • Prepopulate grant forms, AFR’s, SART review, etc. • “Mashups” of ODH, LHD, and other data and content • Integrated community profiling • Shared statistical & GIS analytic platform

  24. What kinds of data can we liberate? Surveillance & Registry • Vital Statistics Examples: • Birth events • Death certificate data • Infant mortality • Mass casualty planning Preparedness Provider Quality & Performance ODH Data Being Liberated? Screening & health services Inspection & Enforcement Vital Statistics

  25. Are we on the right track? • Open Health Data Initiative core activities: liberate data and catalyze innovation • Publish brand new HHS data for public access – while rigorously protecting privacy and confidentiality • Make existing HHS data much more accessible -- “machine-readable,” accessible via application programming interfaces (APIs), free, much easier to find • Energetically publicize our data to innovators -- who can use it as raw material to develop applications and services that help improve health and health care

  26. The goal: a self-propelled, open “ecosystem of innovation” using data to improve health A Rapidly Growing Array of Innovative Products and Services That: • Help consumers take control of their health and health care • Help employers promote health and wellness • Help care providers deliver better care • Help journalists promote health information • Help local leaders make better-informed decisions • Support all of the above through “data intermediary” services • And much more Health-Related Data from FUELS

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