title: Implications of conducting trend analyses of emergency department visits using publicly released masked design variables.
abstract: OBJECTIVE
  We examine whether using public National Hospital Ambulatory Medical Care Survey (NHAMCS) data with masked design variables produces different estimates, standard errors, and confidence intervals (CIs) for the temporal trend of overall and injury-related emergency department (ED) visits compared with using unmasked data housed at the Centers for Disease Control and Prevention.
  
  
  METHODS
  We obtained counts of ED visits with their standard errors for unmasked data from published summaries from 1999 through 2006. Public files with masked design variables were used to estimate visit counts and rates with standard errors for each year, using the Taylor series linearization method. Weighted least squares linear regressions were used for trend analysis to estimate the annual change in visits.
  
  
  RESULTS
  Compared with using unmasked data, using masked data produced similar estimates of overall ED visit counts and rates for each year from 1999 through 2006 but overestimated standard errors by 27% on average (range 12% to 45%). According to unmasked data, overall ED visit counts increased by 1.973 million annually (standard error 0.747; 95% CI 0.505 to 3.440 million [corrected] ). With masked data, the estimated change was 1.977 million visits annually (standard error 0.894; 95% CI -0.221 to 3.733 million [corrected] ). As for injury-related ED visit counts, masked data overestimated the standard error by 16% for trend. Although neither unmasked nor masked data suggested a statistically significant annual increase of overall or injury-related ED visit rate, masked data overestimated the standard error by 16%.
  
  
  CONCLUSIONS
  Using masked public data overestimated standard errors for trend of counts and rates for overall and injury-related ED visits and resulted in wider CIs.
authors.affiliation: Department of Community Medicine and Injury Control Research Center, West Virginia University, Morgantown, WV, USA. mzhu@hsc.wvu.edu
authors.forename: Motao
authors.initials: M
authors.lastname: Zhu
authors.forename: Haitao
authors.initials: H
authors.lastname: Chu
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Rice
authors.forename: Mary W
authors.initials: MW
authors.lastname: Carter
mesh_terms: D002487:Centers for Disease Control and Prevention, U.S.; D003627:Data Interpretation, Statistical; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D019538:Health Care Surveys / Q000706:statistics & numerical data; D006801:Humans; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology*