use of large databases for research n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Use of Large Databases for Research PowerPoint Presentation
Download Presentation
Use of Large Databases for Research

Loading in 2 Seconds...

play fullscreen
1 / 45

Use of Large Databases for Research - PowerPoint PPT Presentation


  • 193 Views
  • Uploaded on

Use of Large Databases for Research. Reaping the benefits of your tax dollars Jeff Coben, MD December 12, 2007. Learning Objectives. Understand the strengths and limitations of using existing large databases for research

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Use of Large Databases for Research' - jacob


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
use of large databases for research

Use of Large Databases for Research

Reaping the benefits of your tax dollars

Jeff Coben, MD

December 12, 2007

learning objectives
Learning Objectives
  • Understand the strengths and limitations of using existing large databases for research
  • Gain exposure to the Healthcare Cost and Utilization Project databases through a review of several examples of prior research
  • Understand the process of accessing, obtaining, and analyzing existing large databases
federal investment in research databases
Federal Investment in Research Databases
  • National or regional in scope
  • Rigorous and well-defined sampling and/or data collection methodologies
  • Often longitudinal, with ongoing data collection using standardized instruments
  • Public domain, with “wrap-around” services
  • Surveys, administrative data, census of providers
common examples
Behavioral Risk Factor Surveillance Survey

National Survey on Drug Use and Health

Healthcare Cost and Utilization Project

National Survey of Child and Adolescent Well-Being

National Health Interview Survey

National Hospital Discharge Survey

National Health and Nutrition Examination Surveys

National Vital Statistics System

Common Examples
federal investment
Federal Investment
  • Federal intramural research staff are devoted to maintaining these databases
  • Intramural staff also increasingly involved in database dissemination activities
reasons for using large federal databases for research
Reasons for Using Large Federal Databases for Research
  • National scope
  • Can study trends over time
  • Large sample sizes permit sub-analyses and multivariate analyses
  • Can obtain population-based estimates of disease
  • COST & EFFICIENCY
research process
Research Process

Choosing the research question

Developing the protocol

Pre-testing and revising the protocol

Carrying out the study

Analyzing the findings

Drawing and disseminating the conclusions

research question
Research Question
  • Do children with traumatic brain injury (TBI) benefit from “aggressive” intensive care management?
management of pediatric tbi
Management of Pediatric TBI
  • TBI is a leading cause of death among children
  • Variation in the management of critically ill TBI patients
  • Concerns over costs of aggressive management
slide10

Research Question - Do children with traumatic brain injury (TBI) benefit from “aggressive” intensive care management?

Develop the Protocol

  • Operationalize terms
  • Study Design
  • Subjects
  • Variables (Predictor/Outcome)
  • Statistical Issues
protocol development
Protocol Development
  • TBI case definition = severe brain injury requiring endotracheal intubation and mechanical ventilation
  • Aggressive management = insertion of intracranial pressure (ICP) monitor
  • Study Design = randomized trial
slide12

Study Design = RCT

Child meets inclusion criteria

ICU management

ICU management + ICP

  • Outcomes
  • Mortality
  • Morbidity
  • Costs
problems with rct design
Problems with RCT Design
  • Ethical?
  • Number of cases needed for prospective study (multi-site)
  • Time required to enroll sufficient sample
  • Cost of the study
using secondary analysis
Using Secondary Analysis
  • Secondary analysis is the reanalysis of data collected by another researcher or organization
  • The shortcut
research process1
Research Process

Choosing the research question

Pre-testing & revising the protocol

Carrying out the study

Drawing and disseminating the conclusions

Developing the protocol

Secondary data analysis

Analyzing the findings

slide16
Variation in therapy and outcome for pediatric head trauma patientsTilford JM, et al. Crit Care Med 2005
  • Study examined the incidence, use of procedures, and outcomes of critically ill children with TBI between 1988-1999 to describe the benefits of improved treatment
  • Hypothesis: more aggressive treatment (ICP monitoring) over time is associated with improved survival
methods
Methods
  • Used the Nationwide Inpatient Sample database to identify all children 0-21 with TBI requiring endotracheal intubation
  • Used ICD-9-CM codes to identify use of ICP monitoring, calculate injury severity scores, and describe consciousness level
changes in icp monitoring and outcome 1988 1999
Changes in ICP Monitoring and Outcome: 1988-1999

ICP Monitoring

Mortality

Injury Severity Score

1988-1989-1990-1991-1992-1993-1994-1995-1996-1997-1998-1999

secondary analysis
Secondary Analysis
  • Advantages: Speed and economy
  • Disadvantages:
    • No control over data variables
    • Compatibility between the available data and the research question
compatibility challenge
Compatibility Challenge
  • Since data already collected, can’t specify what you want
  • May require some modification of the original research question – or….
  • May need to work backwards
  • Compatible with the researcher?
slide21

Primary Data Collection

Research Question

  • Develop Protocol
  • Design
  • Subjects
  • Measures
  • Instruments

Secondary Data Analysis

  • Data Source
  • Design
  • Subjects
  • Measures
  • Instruments

Research Questions

What questions could these data answer?

finding research questions to fit an existing data base
Finding Research Questions to Fit an Existing Data Base
  • Become familiar with the data content
  • Identify pairs or groups of variables whose association may be of interest
  • Review the literature to determine if these research questions are novel and important
  • Formulate specific hypotheses and statistical methods
  • Analyze the data
slide23

HEALTHCARE COST AND UTILIZATION PROJECT

A Family of Databases, Tools and Products

understanding hospital discharge data
Understanding Hospital Discharge Data
  • Hospitals create “discharge abstracts” on every patient seen
  • Original purpose was billing/reimbursement
  • Includes valuable information (>100 variables)
    • Patient demographics
    • Diagnoses, procedures, complications
    • Charges, length of stay, ICU days
hospital discharge data
Hospital Discharge Data
  • Individual discharge abstracts are computerized
  • State regulatory agencies require all hospitals to submit all discharge abstracts on a regular basis
  • Edit checks routinely performed, quality assurance, penalties for non-compliance
slide27

HEALTHCARE COST AND UTILIZATION PROJECT

HCUP Process

HCUP Uniform Data

slide28

HEALTHCARE COST AND UTILIZATION PROJECT

State Inpatient Databases (SID)

Uniform Comprehensive hospital discharge data

HCUP Uniform Data

state inpatient database sid
State Inpatient Database (SID)
  • Complete data from 37 states
  • 90% of all hospital discharges in U.S. (N>30 million)
  • Example of research using the SID
    • Characteristics of motorcycle-related hospitalizations: Comparing states with different helmet laws
      • Coben, Steiner, and Miller. Accident Analysis & Prevention, 2007
slide30

Abstract

This study compares U.S. motorcycle-related hospitalizations across states with differing helmet laws. Cross-sectional analyses of hospital discharge data from 33 states participating in the Healthcare Cost and Utilization Project in 2001 were conducted. Results revealed that motorcyclists hospitalized from states without universal helmet laws are more likely to die during the hospitalization, sustain severe traumatic brain injury, be discharged to long-term care facilities, and lack private health insurance. This study further illustrates and substantiates the increased burden of hospitalization and long-term care seen in states that lack universal motorcycle helmet use laws.

slide31

HEALTHCARE COST AND UTILIZATION PROJECT

State Inpatient Databases (SID)

Nationwide Inpatient Sample (NIS)

  • Sample of community hospitals from SID
  • Approximates 20% sample of community hospitals in the U.S.

Uniform Comprehensive hospital discharge data

HCUP Uniform Data

nationwide inpatient sample nis
Nationwide Inpatient Sample (NIS)
  • Stratified sample of 994 hospitals from the 37 states contributing data to HCUP (N>7 million)
  • Designed for national and regional estimates
  • Example of research using the NIS
    • Rural-urban Differences in Injury Hospitalizations
      • Coben, Tiesman, Bossarte, and Furbee (in progress)
slide34

HEALTHCARE COST AND UTILIZATION PROJECT

State Inpatient Databases (SID)

Kids’ Inpatient Data Base (KID)

  • Sample of pediatric discharges from community hospitals in the SID

Uniform Comprehensive hospital discharge data

HCUP Uniform Data

Nationwide Inpatient Sample (NIS)

  • Sample of community hospitals from SID
  • Approximates 20% sample of community hospitals in the U.S.
kids inpatient database kid
Kids’ Inpatient Database (KID)
  • Stratified sample of pediatric discharges from the SID (N=3 million)
  • Allows national and regional studies of inpatient hospital utilization and charges for children and adolescents
  • Example of research using the KID
    • National estimates of ATV injury hospitalizations in Children
      • Killingsworth JB, et al. Pediatrics, 2005
slide36

HEALTHCARE COST AND UTILIZATION PROJECT

Kids’ Inpatient Data Base (KID)

  • Sample of pediatric discharges from community hospitals in the SID

State Outpatient Databases (SOD)

  • State Ambulatory Surgery Data (SASD)
  • State Emergency Department Data (SEDD)

HCUP Uniform Data

State Inpatient Databases (SID)

Nationwide Inpatient Sample (NIS)

  • Sample of community hospitals from SID
  • Approximates 20% sample of community hospitals in the U.S.

Comprehensive hospital discharge data from states

state ambulatory surgery databases sasd
State Ambulatory Surgery Databases (SASD)
  • Ambulatory surgery data provided by 19 states
  • Example of research using SASD
    • The Impact of Endometrial Ablation on Hysterectomy Rates in Women with Benign Uterine Conditions in the United States
      • Farquhar CM, et al. 2002
state emergency department databases sedd
State Emergency Department Databases (SEDD)
  • Statewide ED data from 17 states
  • Example of research using SEDD
    • Hospital and Demographic Influences on the Disposition of Transient Ischemic Attack
      • Coben, Owens, Steiner, and Crocco. Academic Emergency Medicine, in press.
slide39

Objective: Determine factors responsible for the variation in Emergency Department disposition of TIA cases.

Methods: All ED-treated TIA cases from hospitals in eleven states were identified from the Healthcare Cost and Utilization Project. Descriptive analyses compared admitted and discharged cases. Based on the results of the bivariate analyses, logistic regression models of the likelihood of hospital admission were derived, using a stepwise selection process. Adjusted risk ratios and 95% confidence intervals were calculated from the logistic regression models.

Results: A total of 34,843 cases were identified in the 11 states, with 53% of cases admitted to the hospital. In logistic regression models differences in admission status were found to be strongly associated with clinical characteristics such as age and co-morbidities. After controlling for co-morbidities, differences in admission status were also found to be associated hospital type and with socio-demographic characteristics, including county of residence and insurance status.

Conclusions: While clinical factors predictably and appropriately impact the ED disposition of patients diagnosed with TIA, several non-clinical factors are also associated with differences in disposition.

slide40

HEALTHCARE COST AND UTILIZATION PROJECT

State Inpatient Databases (SID)

State Ambulatory Surgery Data (SASD)

AHRQ

Central Distributor

Data Use Agreement

Public Researchers

KID

CD-SASD

NIS

CD-SID

slide41

HEALTHCARE COST AND UTILIZATION PROJECT

HCUP Tools

HCUP Research Products

HCUPnet: An interactive, on-line query tool for HCUP data

Clinical Classification Software (CCS): Clinical grouper of ICD-9-CM and ICD-10 codes

AHRQ Quality Indicators: Measures of health care quality based on hospital inpatient data

Comorbidity Software: Identifies comorbidities in hospital discharge records using ICD-9-CM codes and DRGs

Products include:

Research Studies

Statistics and

Fact Books on

HCUP Data

secondary analysis of large research databases can
Secondary Analysis of Large Research Databases Can…
  • Be used to test specific hypotheses
    • Improved outcomes with ICP monitoring
  • Be used for descriptive, epidemiological studies
    • Large (faculty): Firearm-related hospitalizations
    • Small (students): Rotavirus admissions
  • Generate pilot data for future investigations
    • ED prospective study on TIA disposition
steps in the process
Steps in the Process
  • Determine interest area
  • Search for existing databases
  • Learn the database
    • Data documentation manuals, CDs, web
  • Derive research question(s)
  • Conduct analyses
    • Statistical consultation, programming
additional tips
Additional Tips
  • Contact intramural staff for advice
  • Be thorough with literature searches
  • Understand the limitations of the database
  • Find other publications using the database