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.

1. 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

2. Outline
• Overview of CELDAC
• Examples of major data sets for studying
child health
• Online tools for simple data analyses
• Discussion
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3. Overview of CELDAC
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4. 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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5. CELDAC Personnel
Faculty 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
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6. 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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7. 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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8. Find Large Datasets
http://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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9. Search Results –
Search for administrative data on infants’ use of health care services
http://ctsi.ucsf.edu/research/celdac
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10. 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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11. 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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12. 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
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13. 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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14. Examples of Major
Child Health Data Sets
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15. Major Types of Large Datasets
Used in Health Services Research
Type of Data Set Description Examples
Survey Collects information from • National Survey of
individuals, families, or Children’s Health
organizations • National Survey of Children
with Special Health Care
Needs
Administrative Information from records • HCUP Kid’s Inpatient
claims of health professionals and Databases
health care facilities, • HCUP State Inpatient
usually from billing records Databases
Registries Information from datasets • California Cancer Registry
that incorporate all • San Francisco
persons with a particular Mammography Registry
condition(s)
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16. Major Types of Designs for
Surveys
Type of Survey Description Examples
Cross-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 Health
Panel 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
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17. Major Types of Units of
Observation
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, •US Census
state) •Area Resource File
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18. 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

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

20. 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 Databases
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21. 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

22. Online Tools for Simple
Data Analyses
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23. 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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30. 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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31. 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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