1. Using Large Databases for Research
Melissa Schiff, MD, MPH
UNM Hospitalists’ Research Club
July 16, 2019

2. How many people have used a large database for a research project?

3. Outline Reasons for using large databases
How to evaluate if a database will work for your research
Nuts and bolts of using large databases
Useful databases for internal med / hospitalist research projects

4. “Epidemiologists are data scavengers”
Secondary database – administrative data collected by an organization, surveillance data
Use of secondary data revolutionized by tech advances and information technology
“Big Data” used in health and many other fields outside of medicine

5. Reasons to use Large Databases
Primary data collection – expensive in terms of money and time
Secondary database advantages –
Data available on the web, from data collection organization or third party
Ex: Medicare data available from CMS
Data collected on large number of people – large sample size, ascertain rare diseases or exposures
Ex: Cerner Health Facts 600 hospitals, 85+ million patients

6. Population-based data - calculate incidence rates, avoid referral bias
Ex: Birth certificates, death certificates, NM HIDD
Data less biased – collected for another purpose
Ex: Self-report alcohol-related admissions vs hospitalization data

7. Linkage of secondary database to primary data – independent measure or validation
Ex: Occupational lung disease study linked to employment records
Use of natural language processing – search text for keywords
Ex: OMI data searched for oil and gas worker deaths

8. Evaluating Large Database for your Research
Research question definition, variables
Exposure(s)
Outcome(s)
Confounding factors
Identify the database of interest – publically available, documentation available
Population included in database
Demographics, geographic location
Inclusion/exclusion criteria

10. Database – SEER linked to Medicare, 2001-2011
Research question: Does use of preventive care differ by race among Medicare beneficiaries with early stage endometrial cancer?
Database – SEER linked to Medicare,
Population –women 65+ years (Medicare), endometrial cancer (SEER) N=13,054
Exposure – race (Medicare)
Outcome – preventive care (Medicare outpatient visits)
Well visit
Flu vaccine
Mammogram
Diabetes screening

11. Time frame – months, years
Data dictionary – document listing the variables, definitions
Are your key variables included in the database?
How are they measured?
How much missing data for key variables?
How many cases available in database?
May need to download database to evaluate

12. Nuts and Bolts for using Large Databases
Accessing database –
Available online, from organization
May need to submit written request with research question
Cost of database
Finding help
Researchers at UNM with specific database experience
CTSC
State health department
Experts at federal agencies (e.g. CMS)

13. Statistical / data management needs
Statistical package capacity for large databases
Biostatistician with familiarity of database
Data collection at the individual level or encounter level – un-duplication
Subject identifiers
Longitudinal - analysis over time
IRB – typically considered “Exempt” status, check with UNM HRPO

14. Efficient use of one database
Main research question
Specific populations - age groups, disease severity
Trends over time
Evaluation of policy change
Financial data – health economics
Identify refined research question – future primary data collection
Become the local expert

15. Useful Databases Databases available at UNM
Health Facts – Cerner EMR data for UNM hospital, 600 hospitals
Truven – 240 million patients, pharmaceuticals
I2B2 – identify number of cases in UNM EMR
Vizient
New Mexico Tumor Registry (SEER) – all cancer cases in NM

16. New Mexico databases Office of Medical Investigator
New Mexico Death Certificates
SEER-Medicare linked data
Behavioral Risk Factor Surveillance System
New Mexico Prescription Monitoring Program
Indicator-based Information System (IBIS)

17. National databases Health Care Cost and Utilization Project (HCUP)
National Inpatient Sample (NIS) – 7 million hospital stays
National Health And Nutrition Examination Survey (NHANES) – 5000 people annually
National Ambulatory Medical Care Survey
Medicaid
Medicare
Veteran’s Administration

18. List of large databases - https://www.ehdp.com/vitalnet/datasets.htm

19. Summary Research question - consider using a large database
Investigating a large database – population, variables, missing data, cost
Accessing a large database – availability, time frame to get data, data management/analysis, people to help
Multiple uses – consider variety of research questions to answer

20. Questions?
Contact information