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1 Using National Hospital Ambulatory Medical Care Survey (NHAMCS) data for injury analysis Linda McCaig Ambulatory Care Statistics Branch Division of Health Care Statistics U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics
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2 Overview Background Survey methodology Data uses User considerations for injury analysis
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3 NHAMCS background National probability sample survey of visits to EDs and OPDs of non- federal, short-stay, and general hospitals Survey began in 1992 Annual data collection (Census)
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4 NHAMCS Methodology
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5 NHAMCS Sample design 112 geographic PSUs 500 hospitals 400 EDs and 250 OPDs 37,000 ED and 35,000 OPD visits – 4-week reporting period
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6 ED Items collected Patient characteristics – age, race, sex Visit characteristics – Mode of arrival, immediacy, reason for visit, injury-related, diagnosis, medication Hospital characteristics – ownership, teaching hospital
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7 Injury/poisoning/adverse effect items Intentionality – Unintentional – Intentional self-inflicted assault Work related External cause – Up to 3 causes – Narrative text since 1997
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8 Coding systems used A Reason for Visit Classification (NCHS) International Classification of Diseases-9- CM – diagnosis codes – external cause of injury codes Barell Injury Diagnosis Matrix: Classification of Region of Body and Nature of Injury Drug coding system (NCHS) National Drug Code Directory
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9 Injury definition Injury checkbox marked Reason for visit in injury module Diagnosis is in injury or poisoning chapter of ICD-9-CM Cause of injury recorded
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10 Data quality Data are coded and keyed by Constella Group Inc. (CG) 10 percent of records are independently coded and keyed Coding error rate for cause of injury is 0.8 percent Item nonresponse for cause of injury 4- 23%
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11 Other Ambulatory Care Surveys with Injury Data National Ambulatory Medical Care Survey (NAMCS) – National probability sample survey of visits to office-based physicians OPD component of the NHAMCS
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13 ED Data uses for injury Track visits Find health disparities Compare illness and injury Examine hospital level data
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14 Annual rate of injury-related ED visits for children by diagnosis Head wound Other wound Intracranial Poisoning
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15 Rate of injury-related ED visits by race and age
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16 ED visits by day of week according to illness or injury Illness Injury
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17 Average annual injury-related ED visit rates for persons 5-24 years of age by sport
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18 Most frequent annual injury visits at ambulatory care settings by body site
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19 Fall-related ED characteristics for persons 65 years of age and over CharacteristicNumber in 1,000s PercentAdjusted odds ratio Age in years 65-799499.5Referent 80 and over1,00216.12.0 Residence Community1,36911.1Referent Institution37919.22.0
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20 Poisoning Pyramid Poison exposures 147 ED visits 59 Hospitalizations 13 Death 1
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22 Distribution of hospital EDs on the percent of visits for injuries
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23 Encounter vs. person data NHAMCS is a record-based survey Not population-based survey (NHIS) Can not calculate incidence or prevalence rates from NHAMCS estimates
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24 User considerations Sample data must be weighted to produce national estimates Estimates must be based on at least 30 raw cases Must use generalized variance curve or special software (e.g., SUDAAN) to calculate SEs for all estimates Only estimates with a relative standard error < 30% are reliable
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25 Ways to improve reliability of estimates Combine multiple years of ED data Combine NAMCS, ED and OPD data to produce ambulatory care visit estimates
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26 Microdata files Downloadable files NAMCS, 1973-2002 NHAMCS, 1992-2002 CD-ROMs NAMCS, 1990-2002 NHAMCS, 1992-2001 (2002 in Aug.) Tapes/cartridges (NTIS) NAMCS, 1973-1997 NHAMCS, 1992-1997
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27 Enhanced NHAMCS public-use files SAS (1995-2002), SPSS (2002), STATA (2002) - input statements, variable and value labels, and format assignments Masked sample design variables (1995- 2002) –Allows use of SUDAAN and STATA
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28 http://www.cdc.gov/nchs/about/major/ahcd/ahcd1.htm
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29 Thank You Linda McCaig – NHAMCS data lmccaig@cdc.gov
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