title: An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity.
abstract: OBJECTIVE
  The accuracy of maternal morbidity estimates from hospital discharge data may be influenced by incomplete identification of deliveries. In maternal/infant health studies, obstetric deliveries are often identified only by the maternal outcome of delivery code (International Classification of Diseases code = V27). We developed an enhanced delivery identification method based on additional delivery-related codes and compared the performance of the enhanced method with the V27 method in identifying estimates of deliveries as well as estimates of maternal morbidity.
  
  
  METHODS
  The enhanced and standard V27 methods for identifying deliveries were applied to data from the 1998-2004 Healthcare Cost and Utilization Project Nationwide Inpatient Sample, an annual nationwide representative survey of U.S. hospitalizations. Odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression were used to examine predictors of deliveries not identified using the V27 method.
  
  
  RESULTS
  The enhanced method identified 958,868 (3.4%) more deliveries than the 27,128,539 identified using the V27 code alone. Severe complications including major puerperal infections (OR = 3.1, 95% CI 2.8-3.4), hysterectomy (OR = 6.0, 95% CI 5.3-6.8), sepsis (OR = 11.9, 95% CI 10.3-13.6) and respiratory distress syndrome (OR = 16.6, 95% CI 14.4-19.2) were strongly associated with deliveries not identified by the V27 method. Nationwide prevalence rates of severe maternal complications were underestimated with the V27 method compared to the enhanced method, ranging from 9% underestimation for major puerperal infections to 40% underestimation for respiratory distress syndrome.
  
  
  CONCLUSIONS
  Deliveries with severe obstetric complications may be more likely to be missed using the V27 code. Researchers should be aware that selecting deliveries from hospital stay records by V27 codes alone may affect the accuracy of their findings.
authors: Quantell Inc., Taneytown, MD, USA. ekuklina@cdc.gov
authors: Elena V
authors: EV
authors: Kuklina
authors: Maura K
authors: MK
authors: Whiteman
authors: Susan D
authors: SD
authors: Hillis
authors: Denise J
authors: DJ
authors: Jamieson
authors: Susan F
authors: SF
authors: Meikle
authors: Samuel F
authors: SF
authors: Posner
authors: Polly A
authors: PA
authors: Marchbanks
mesh_terms: D036861:Delivery, Obstetric / Q000145:classification* / Q000706:statistics & numerical data*; D005260:Female; D019538:Health Care Surveys / Q000379:methods*; D006801:Humans; D038801:International Classification of Diseases / Q000706:statistics & numerical data*; D007744:Obstetric Labor Complications / Q000145:classification / Q000453:epidemiology*; D011247:Pregnancy; D014481:United States / Q000453:epidemiology
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