Analyzing Child Health Data Sets: How UCSF's CELDAC Initiative Helps to Move Your Research Forward
 

Analyzing Child Health Data Sets: How UCSF's CELDAC Initiative Helps to Move Your Research Forward

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Overview of UCSF-CTSI Comparative Effectiveness Large Dataset Analysis Core and large, public datasets for studying the health of children and the health care they receive.

Overview of UCSF-CTSI Comparative Effectiveness Large Dataset Analysis Core and large, public datasets for studying the health of children and the health care they receive.

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Analyzing Child Health Data Sets: How UCSF's CELDAC Initiative Helps to Move Your Research Forward Analyzing Child Health Data Sets: How UCSF's CELDAC Initiative Helps to Move Your Research Forward Presentation Transcript

  • UCSF’s Comparative Effectiveness Large Dataset Analytic Core:Focus on Child Health Data Sets Janet Coffman, PhD Philip R. Lee Institute for Health Policy Studies University of California, San Francisco November 30, 2011
  • Outline• Overview of CELDAC• Examples of major data sets for studying child health• Online tools for simple data analyses• Discussion 2
  • Overview of CELDAC 3
  • CELDAC PartnersCELDAC is a partnership at UCSF among the – Philip R Lee Institute for Health Policy Studies – Academic Research Systems – Department of Orthopedic Surgery – Clinical and Translational Science InstituteFunding – Administrative supplement to the NCRR grant for UCSF’s Clinical & Translational Science Institute –California HealthCare Foundation 4
  • CELDAC PersonnelFaculty IHPS Staff• Janet Coffman • Leon Traister• Jim G. Kahn • Claire Will• Claire Brindis ARS Staff• Steve Takemoto • Rob Wynden• Adams Dudley • Ketty Mobed• Kirsten Johansen • Hari Rekapalli • Prakash Lakshminarayanan 5
  • CELDAC MissionThe mission of CELDAC is to enhanceUCSFs capacity for analysis of large local,state, and national health datasets toconduct comparative effectivenessresearch and other types of healthservices and health policy research. 6
  • CELDAC Goals• Accelerate access to and use of local, state, and national health datasets, as a model for other CTSAs and health research organizations.• Enhance UCSF researchers’ ability to compete for funding to use large data sets to conduct CER.• Develop procedures and infrastructure by conducting pilot studies.• Support additional studies on the comparative effectiveness of clinical interventions.• Provide consultation to researchers currently working with or interested in working with large data sets 7
  • Find Large Datasets http://ctsi.ucsf.edu/research/celdacA guided search tool to find the best datasets for a project. Builds on previousefforts by Andy Bindman, Nancy Adler, Claire Brindis, Charlie Irwin and others. 8
  • Search Results –Search for administrative data on infants’ use of health care services http://ctsi.ucsf.edu/research/celdac 9
  • Analyze Large Data Sets• CELDAC has created a repository of select large, public data sets that are available to UCSF faculty at no cost.• These data sets include – HCUP Kids Inpatient Databases – HCUP National Emergency Department Sample – HCUP National Inpatient Sample – HCUP State Emergency Department and Inpatient Databases (select states) – American Hospital Association Annual Survey – Area Resource File 10
  • Provide Consultation• Study design/conceptualization• Identification of relevant datasets• Assistance with data set acquisition• Cohort selection• Data cleaning• Linking data sets• Strategies to deal with common methodological issues in analysis of observational data• Programming support for preliminary analyses 11
  • Test New Methods for Working with Large Data Sets• Conventional methods for managing large data sets have important limitations, especially for studies that draw data from multiple data sets – Requires programmers with expertise in managing and querying large data sets – Source data tables continue as individual entities – Manipulations and linkages between tables require awareness of each table’s architecture and customized “One-Off” programming 12
  • Test New Methods for Working with Large Data Sets• Pilot Projects – Integrated repository of data on spine surgery procedures and outcomes from five data sources – Graphical user interface for browsing California Office of Statewide Health Planning and Development data on hospital discharges 13
  • Examples of MajorChild Health Data Sets 14
  • Major Types of Large DatasetsUsed in Health Services ResearchType of Data Set Description ExamplesSurvey Collects information from • National Survey of individuals, families, or Children’s Health organizations • National Survey of Children with Special Health Care NeedsAdministrative Information from records • HCUP Kid’s Inpatientclaims of health professionals and Databases health care facilities, • HCUP State Inpatient usually from billing records DatabasesRegistries Information from datasets • California Cancer Registry that incorporate all • San Francisco persons with a particular Mammography Registry condition(s) 15
  • Major Types of Designs for SurveysType of Survey Description ExamplesCross-sectional Data collected from a • National Health and Nutrition single sample at a Examination Survey single point in time • National School-based Youth Behavior Survey • National Survey of Children’s HealthPanel Data collected from a • Medical Expenditure Panel Survey single sample at • National Longitudinal Study of multiple points in time Adolescent Health • National Longitudinal Survey of Youth 16
  • Major Types of Units of ObservationUnit of Observation ExamplesIndividual • National Health and Nutrition Examination Survey • National Survey of Children’s HealthHousehold • Medical Expenditure Panel Survey • National Health Interview SurveyVisit or discharge • HCUP Kid’s Inpatient Databases • National Ambulatory Medical Care SurveyPhysician • American Medical Association Masterfile • HSC Health Tracking Physician SurveyFacility (e.g., hospital, clinic) •American Hospital Association Annual Survey •California OSHPD Hospital Annual Financial DataGeographic area (e.g., county, •US Censusstate) •Area Resource File 17
  • Major National Data Sets Focused on Child Health• National Survey of Children’s Health• National Survey of Children with Special Health Care Needs• National Immunization Survey• National School-based Youth Risk Behavior Survey• National Longitudinal Study of Adolescent Health• Kids’ Inpatient Database 18
  • National Survey of Children’s Health• Nationally representative sample (90,000+ children in 2007-2008• Cross-sectional design, independent samples• Administered by telephone to parent or guardian • Historically landlines only; adding cell phones• Questions about • Child’s physical and emotional health • Parents’ health • Family interactions • School and communityhttp://www.cdc.gov/nchs/slaits/nsch.htm 19
  • Other National DatasetsContaining Data on Child Health• National Ambulatory Medical Care Survey• National Hospital Ambulatory Medical Care Survey• National Health and Nutrition Examination Survey• Medical Expenditures Panel Survey• HCUP State Emergency Department and Inpatient Databases 20
  • Medical Expenditure Panel Survey• Nationally representative sample of 22,000 to 37,000 persons• Overlapping panel design• 2 years of data collected through 5 rounds of interviews• Three major components • Household survey • Data on cost and utilization from providers caring for household survey participants • Survey of employers regarding employer-sponsored health insurance benefitshttp://www.meps.ahrq.gov/mepsweb/ 21
  • Online Tools for Simple Data Analyses 22
  • Approaches to Obtaining Information from Large Data Sets• Analyze the data set or find a programmer to do the analysis for you• Use an interactive data analysis tool provided for the data set• Use a web site that aggregates data from multiple sources 23
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  • Questions for Discussion• What services relating to large data set analysis would be most useful to you?• What data sets are of greatest interest to you?• How could CELDAC partner effectively with researchers in your school/department/division? 30 30
  • Contact CELDAC• Jim G. Kahn: JimG.Kahn@ucsf.edu• Janet Coffman: Janet.Coffman@ucsf.edu/415-476-2435• Claire Will: Claire.Will@ucsf.edu/415-476- 6009• http://ctsi.ucsf.edu/research/large-datasets 31