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Studying Injuries Using the National Hospital Discharge Survey. Marni Hall, Ph.D. Hospital Care Statistics Branch, Division of Health Care Statistics. Outline of this presentation. Present general information about the design of the National Hospital Discharge Survey (NHDS)

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studying injuries using the national hospital discharge survey

Studying Injuries Using the National Hospital Discharge Survey

Marni Hall, Ph.D.

Hospital Care Statistics Branch,

Division of Health Care Statistics

outline of this presentation
Outline of this presentation
  • Present general information about the design of the National Hospital Discharge Survey (NHDS)
  • Discuss decisions that have to be made when designing injury research using NHDS
  • Highlight issues particularly related to trend analyses in
slide3

Upcoming Chartbook

Trends in Injury Hospitalization,

United States, 1979-2001

by Melissa Heinen, Marni Hall,

Manon Boudreault, and Lois Fingerhut

slide4

NHDS a national probability sample of short-stay non-federal hospitals - conducted every year since 1965provides data on discharges or hospitalizations – not individuals2002 data - now available2003 data - available in the winter

nhds design
NHDS Design

Three stage design Geographic Units Hospitals Discharges

data collection
Data Collection

Automated – 40%

Manual – 60%

patient data
Patient Data
  • Sex
  • Race
  • Age
  • Expected source of payment
  • Discharge status – including deaths
facility characteristics
Facility Characteristics
  • Geographic region
  • Bed size
  • Ownership
slide9
Medical DataCoded according to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM)
  • Diagnoses
  • Surgical and nonsurgical procedures
additional variables
Additional Variables
  • Days of care
  • Month of admission/discharge
  • Weight
  • DRG – diagnosis-related group
  • Available since 2001 NHDS
    • Source of Admission
    • Type of Admission
slide11
2002 NHDS445 hospitals and 327,000 discharges were sampled Weighted number of discharges was 33.7 million
weights
Weights
  • Must use weighted data to obtain national estimates
  • Each record has a weight
  • Must calculate the sum the weights of the records – one line of programming
slide13

Estimates have standard errorsA standard error is the sampling variability that occurs by chance because only a sample rather than the entire universe is surveyed

for more design information
For more design information

Plan and Operation of the

National Hospital Discharge Survey: 1988 Redesign

Vital and Health Statistics, 1(39). 2000

http://www.cdc.gov/nchs/data/series/sr_01/sr01_039.pdf

designing injury research project
Designing Injury Research Project
  • Determine what injury definition will be used – all injuries or selected injuries – what ICD-9-CM codes
  • Decide how you will count injury patients
  • Select the data you will report
  • Evaluate whether and how external cause codes will be used
injury definitions
Injury definitions
  • Definition developed by injury experts, e.g. the State and Territorial Injury Prevention Directors Association (STIPDA) reported in Consensus recommendations for using hospital discharge data for injury surveillance, 2003
  • Use existing categorization of codes – e.g. the Barell Matrix which defines injuries by type and body region in Injury Prevention, 8, 2002
  • Injury and Poisoning Chapter of the ICD-9-CM – codes 800 to 999 – includes “true injuries” and “medical injuries”
slide17

Diagnoses selected for study should

  • Have a specific ICD-9-CM code(s)
  • Be relatively common in hospitalized patients or you will have to combine data over multiple years in order to get reliable estimates
reliability
Reliability
  • To be reliable, estimates must be based on at least 30 records, and have a relative standard error of less than 30 percent - these usually produce weighted estimates of less than 5,000
  • Estimates based on 30-59 records may be unreliable and should be used with caution – these usually produce weighted estimates from 5,000-9,000
slide19

Counting injury patientsIf you want the number of patientshospitalized because of an injury – count the first-listed diagnosesIf you want the number of hospitalized patients who have one or more injuries – count any-listed diagnoses

slide20
Counting injuriesIf you want the number of injuries and notthe number of patients – count all-listed diagnoses
hospital discharges with fractures 2002
Hospital discharges with fractures, 2002

1,609,000

1,387,000

995,000

Principal or first listed

All listed

Any listed

injury chartbook includes the following data
Injury chartbook includes the following data
  • Injury discharges by age and sex
  • Type and body region of injuries
  • Average number of diagnoses
  • Days of care/average length of stay
  • Expected source of payment
  • Discharge disposition
  • Percent with, and types of, external cause codes
choices involving external cause codes
Choices involving external cause codes
  • Evaluate the percent of injury patients with external cause codes – how complete is it?
  • If you decide you will use external cause codes, will you use just the first code or all codes?
  • Consider using a previously developed categorization, e.g. - the External Cause of Injury Matrix
challenges in studying trend data
Challenges in studying trend data
  • Coding changes over time
  • Size and availability of data files
  • Presenting the data
  • Interpreting the data
different versions of the international classification of diseases
Different versions of the International Classification of Diseases
  • 8th revision used 1970-78
  • 9th revision used 1979-2004 – with addenda since 1986
size and availability of nhds data
Size and availability of NHDS data
  • Single year files can be downloaded from the NHDS website and unzipped using free software. These include DRG’s.
  • Multiple year files are on CD’s, rather than our website, due to their large size. They can be obtained by calling our office (301-458-4321). They do not include DRG’s.
slide27
Presenting the data

Age adjustment - Eliminates the differences in observed rates that result from age differences in population composition over time

slide28

Presenting the data Use of the log scale - allows the presentation of estimates with a very wide range on the same graphandfacilitates comparison of the percent change of estimates over time

slide29

Presenting the data Measures of changeAAPC – Average annual percent change from 1979-2001APC – Average percent change for 1979-2001

slide30
Interpreting the results

Health service system changes which contributed to the decrease in hospitalization overall and for injuries

  • Reform of Medicare hospital payment
  • Increased utilization review of hospital care
  • Growth in managed care
  • Expansion and coverage of ambulatory surgery
slide31
Interpreting the results

Injury prevention activities which contributed to the decrease in hospitalization for injuries

  • Encouragement of the use of safety belts and helmets
  • Safer automobiles (air bags)
  • Safer roads
  • Improvements in home and workplace safety
  • Poison control centers
slide32
For more information:
  • Check our website

www.cdc.gov/nchs/about/major/hdasd/nhds.htm

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