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

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Overview of CELDAC

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CELDAC Partners

CELDAC 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 Institute

Funding– Administrative supplement to the NCRR grant for UCSF’s Clinical & Translational Science Institute–California HealthCare Foundation

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CELDAC Personnel

Faculty

• Janet Coffman• Jim G. Kahn• Claire Brindis• Steve Takemoto• Adams Dudley• Kirsten Johansen

IHPS Staff

• Leon Traister• Claire Will

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ARS Staff• Rob Wynden• Ketty Mobed• Hari Rekapalli• Prakash Lakshminarayanan

CELDAC Mission

The mission of CELDAC is to enhance UCSF's capacity for analysis of large local, state, and national health datasets to conduct comparative effectiveness research and other types of health services and health policy research.

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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

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Find Large Datasetshttp://ctsi.ucsf.edu/research/celdac

A guided search tool to find the best datasets for a project. Builds on previous efforts by Andy Bindman, Nancy Adler, Claire Brindis, Charlie Irwin and others.

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Search Results –Search for administrative data on infants’ use of health care services

http://ctsi.ucsf.edu/research/celdac

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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

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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

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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

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

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Examples of Major Child Health Data Sets

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Major Types of Large Datasets Used in Health Services ResearchType of Data Set Description ExamplesSurvey Collects information from

individuals, families, or organizations

• National Survey of Children’s Health

• National Survey of Children with Special Health Care Needs

Administrative claims

Information from records of health professionals and health care facilities, usually from billing records

• HCUP Kid’s Inpatient Databases

• HCUP State Inpatient Databases

Registries Information from datasets that incorporate all persons with a particular condition(s)

• California Cancer Registry• San Francisco

Mammography Registry

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Major Types of Designs for Surveys

Type of Survey Description Examples

Cross-sectional Data collected from a single sample at a single point in time

• National Health and Nutrition Examination Survey

• National School-based Youth Behavior Survey

• National Survey of Children’s HealthPanel Data collected from a

single sample at multiple points in time

• Medical Expenditure Panel Survey• National Longitudinal Study of

Adolescent Health• National Longitudinal Survey of

Youth

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Major Types of Units of Observation

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Unit of Observation Examples

Individual • National Health and Nutrition Examination Survey• National Survey of Children’s Health

Household • Medical Expenditure Panel Survey• National Health Interview Survey

Visit or discharge • HCUP Kid’s Inpatient Databases• National Ambulatory Medical Care Survey

Physician • American Medical Association Masterfile• HSC Health Tracking Physician Survey

Facility (e.g., hospital, clinic) •American Hospital Association Annual Survey•California OSHPD Hospital Annual Financial Data

Geographic area (e.g., county, state)

•US Census•Area Resource File

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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

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 community

19http://www.cdc.gov/nchs/slaits/nsch.htm

Other National Datasets Containing 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 Databases20

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 benefits

http://www.meps.ahrq.gov/mepsweb/21

Online Tools for Simple Data Analyses

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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

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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?

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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

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