An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity.
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.
Kuklina
Elena V
EV
Quantell Inc., Taneytown, MD, USA. ekuklina@cdc.gov
Whiteman
Maura K
MK
Hillis
Susan D
SD
Jamieson
Denise J
DJ
Meikle
Susan F
SF
Posner
Samuel F
SF
Marchbanks
Polly A
PA
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
Obstet Gynecol. 2005 Oct;106(4):684-92
16199622
Am J Obstet Gynecol. 2005 Jan;192(1):191-8
15672024
Eff Clin Pract. 2002 May-Jun;5(3):143-51
12088294
Obstet Gynecol. 2007 Mar;109(3):669-77
17329519
Obstet Gynecol. 2005 Oct;106(4):678-9
16199619
Health Serv Res. 2005 Oct;40(5 Pt 2):1620-39
16178999
MMWR Morb Mortal Wkly Rep. 2000 Mar 31;49(12):245-8
10774544
Vital Health Stat 13. 2005 Mar;(158):1-199
15853196
Am J Public Health. 2003 Apr;93(4):631-4
12660209
Obstet Gynecol. 2005 Oct;106(4):717-25
16199627
Obstet Gynecol. 2005 Sep;106(3):509-16
16135580
Am J Obstet Gynecol. 2004 Jun;190(6):1629-33; discussion 1633-4
15284758
Paediatr Perinat Epidemiol. 2004 Mar;18(2):112-9
14996250
J Clin Epidemiol. 2004 Sep;57(9):985-8
15504642
Paediatr Perinat Epidemiol. 2005 Nov;19(6):460-71
16269074
Int J Epidemiol. 1999 Feb;28(1):64-9
10195666
Paediatr Perinat Epidemiol. 2005 May;19(3):206-14
15860079
Am J Public Health. 2005 Mar;95(3):478-82
15727980