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The Comparative Effectiveness Large Dataset Analysis Core: A Resource for Accelerating Research with Large, Public Datasets Janet Coffman, PhD Associate.

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Presentation on theme: "The Comparative Effectiveness Large Dataset Analysis Core: A Resource for Accelerating Research with Large, Public Datasets Janet Coffman, PhD Associate."— Presentation transcript:

1 The Comparative Effectiveness Large Dataset Analysis Core: A Resource for Accelerating Research with Large, Public Datasets Janet Coffman, PhD Associate Adjunct Professor Philip R. Lee Institute for Health Policy Studies University of California, San Francisco October 5, 2012

2 Outline Examples of major types of large, public datasets Overview of Comparative Effectiveness Large Dataset Analysis Core (CELDAC) CELDAC datasets CELDAC accomplishments K Scholar success story Discussion 2

3 Major Types of Large Datasets Used in Health Services Research 3

4 Major Sources of Data Type of Data SetDescriptionExamples Survey Collects information from individuals, families, or organizations Medical Expenditure Panel Survey National Health and Nutrition Examination Survey Administrative claims Information from records of health professionals and health care facilities, usually from billing records HCUP National Inpatient Sample Medicare Research Identifiable Files Registries Information from datasets that incorporate all persons with a particular condition(s) California Cancer Registry San Francisco Mammography Registry 4

5 Major Units of Observation 5 Unit of ObservationExamples Individual National Health and Nutrition Examination Survey National Survey of Childrens Health Household Medical Expenditure Panel Survey National Health Interview Survey Visit or discharge HCUP Kids 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

6 Major Types of Survey Designs Type of Survey DescriptionExamples Cross- sectional Data collected from a single sample at a single point in time National Health Interview Survey National Survey of Childrens Health California Health Interview Survey Panel Data collected from a single sample at multiple points in time Medical Expenditure Panel Survey Health and Retirement Survey National Longitudinal Study of Adolescent Health 6

7 National Health and Nutrition Examination Survey Nationally representative sample of 5,000 persons per year Data collected in 15 counties per year Two major components –Interviews: demographic characteristics, socioeconomic status, diet, health behaviors –Physical examinations: medical, dental, physiological, lab tests 7

8 Examples of UCSF Faculty Publications Using NHANES Seligman H.K. Food insecurity is associated with diabetes mellitus: results from the National Health Examination and Nutrition Examination Survey (NHANES) Journal of General Internal Medicine Jul;22(7): Woodruff T, Zota A, Schwartz J. Environmental chemicals in pregnant women in the United States: NHANES Environmental Health Perspectives Jun;119(6): Jul;22(7):

9 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 9

10 Examples of UCSF Faculty Publications Using MEPS Newacheck P, Kim S. A national profile of health care utilization and expenditures for children with special health care need. Archives of Pediatric and Adolescent Medicine Jan;159(1):10-7. Yelin E., et al. Medical care expenditures and earnings losses among persons with arthritis and other rheumatic conditions in 2003, and comparisons with Arthritis and Rheumatism May;56(5):

11 Overview of CELDAC 11

12 CELDAC Partners CELDAC is a partnership at UCSF among the –Philip R Lee Institute for Health Policy Studies –Clinical and Translational Science Institute –Academic Research Systems Funding –Administrative supplement to the NCRR grant for UCSFs Clinical & Translational Science Institute – California HealthCare Foundation 12

13 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. 13

14 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 research. Develop procedures and infrastructure by conducting pilot studies. Support additional studies using large, public datasets. Provide consultation to researchers currently working with or interested in working with large datasets. 14

15 CELDACS Main Components, 2013 Online, searchable inventory of datasets Consultation Repository of select datasets available through MyResearch 15

16 Find Large Datasets A guided search tool to find the best datasets for a project. Builds on previous efforts by Nancy Adler, Andy Bindman, Claire Brindis, Charlie Irwin and others. 16

17 Search Results – Search for administrative data on infants use of health care services 17

18 Dataset Description and Links 18

19 Provide Consultation Study design/conceptualization Identification of relevant datasets Assistance with dataset acquisition Cohort selection Data cleaning Linking datasets Strategies to deal with common methodological issues in analysis of observational data Programming support for preliminary analyses 19

20 Provide Consultation CELDAC provides some services on its own Links researchers with other CTSI Consultation Service units as needed –Data management –Biostatistics –Other 20

21 CELDAC Datasets 21

22 Analyze Large Datasets CELDAC has created a repository of select large, public datasets that are available to UCSF faculty at no cost. These data sets include –American Hospital Association Annual Survey –Area Resource File –HCUP Kids Inpatient Database –HCUP National Emergency Department Sample –HCUP National Inpatient Sample –HCUP State Emergency Department and Inpatient Databases (select states) 22

23 National Inpatient Sample Largest publicly available all-payer inpatient database 20% stratified sample of admissions to community hospitals 8 million discharges Data available from 1988 to 2010 Number of participating states has increased over time from 8 to 45 23

24 Kids Inpatient Sample Only all-payer inpatient care database on children 3 million discharges of children and adolescents 20 years old Data available for 1997, 2000, 2003, 2006, and 2009 Number of participating states has increased over time from 22 to 44 24

25 State Inpatient Databases Universe of inpatient discharge abstracts from community hospitals 46 states currently participate: > 90% of community hospital discharges Some states provide variables for tracking readmissions Data available from 1990 onward UCSF has data from 2006 to 2010 for states with readmissions variables 25

26 National Emergency Department Sample 20% stratified sample of visits to community hospital EDs 25 to 30 million unweighted records Data available from 2006 to states currently participate Includes ED visits that resulted in –Treat-and-release –Transfer to another hospital –Admission to the same hospital 26

27 27 State Emergency Department Databases Universe of ED visits that did not result in a hospital admission from community hospitals in participating states 27 states currently participate Some states provide variables for tracking revisits Data available from 1999 onward UCSF has data from 2006 to 2010 for states with revisits variables

28 CELDAC Accomplishments 28

29 CELDAC Clients CELDAC has assisted over 70 faculty, staff, and trainees at UCSF –22 using datasets in CELDACs repository –18 consultations –11 linkages with other UCSF resources –9 presentations to faculty, staff, and trainees 29

30 CELDAC Clients CELDAC serves a wide range of departments 30 School of Medicine Anesthesia Dermatology Emergency Medicine Family & Community Medicine Medicine Neurological Surgery Neurology Obstetrics & Gynecology Orthopedic Surgery Psychiatry Pediatrics Radiology Surgery Urology School of Nursing Community Health Systems Nursing Family Health Care Nursing School of Dentistry Preventive and Restorative Dentistry School of Pharmacy Clinical Pharmacy

31 CELDAC Extensions UCSF Library –Cross reference available datasets UCSF CTSI –Assist Community Engagement with consultations that concern data analysis –Collaborate with Data Management consultation unit on project to identify UCSF staff with data management expertise 31

32 CELDAC Extensions California HealthCare Foundation –Assessment of state policymakers needs for health care data 32

33 K Scholar Success Story 33

34 Naomi Bardach, MD, MAS Assistant Professor of Pediatrics Former KL2 Scholar Current K23 Scholar (NICHD) 34

35 Initial Study 35 Objective –To describe variation in hospital-level pediatric asthma readmission rates in community hospitals and hospital and patient characteristics associated with readmissions

36 Initial Study Design/Methods –HCUP State Inpatient Databases for states with revisit linkages (AZ, CA, FL, NC, UT) –Readmissions of patients age 2-21 years to non- federal hospitals within 30-days of asthma related admission –Outliers = hospitals with readmission rates that did not overlap with estimate of group mean –Random effects logistic model to assess hospital and patient characteristics associated with readmissions 36

37 Initial Study Results –1.9% of admissions were readmissions within 30 days (391 of 20,323) –Readmissions ranged from 0% to 7.3% –Only 2 hospitals had readmission higher rates the group mean and none had lower rates –Patient age, race, payor, and immunological complex chronic condition associated with odds of readmission 37

38 Subsequent Studies Used HCUP State Inpatient and Emergency Department databases to assess readmission and revisit rates across diseases and conditions Used the HCUP Kids Inpatient Database and a database from freestanding childrens hospitals to analyze pediatric ED visits and hospitalizations for mental health conditions 38

39 How CELDAC Helped Initial K23 proposal not funded in part due to concerns about data sources Revised proposal to incorporate analysis of HCUP state databases Revised proposal funded Platform presentation at Pediatric Academic Societies Annual Meeting Manuscript revised and resubmitted to Pediatrics 39

40 40 Questions for Discussion How could CELDAC better serve K Scholars? What are the biggest barriers to research with large, public datasets at UCSF? What services relating to analysis of large, public datasets would be most helpful?

41 Contact CELDAC Janet Coffman, PhD, Principal Investigator: Claire Will, PhD, Project Coordinator: 41


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