The Reporting of Pre-Existing Maternal Medical Conditions and Complications of Pregnancy on Birth Certificates and in Hospital Discharge Data
Department of Family and Child Nursing, University of Washington Seattle, Seattle, Washington, United States American Journal of Obstetrics and Gynecology
(Impact Factor: 4.7).
08/2005; 193(1):125-34. DOI: 10.1016/j.ajog.2005.02.096
The purpose of this study was to determine the accuracy of live-birth certificates and hospital discharge data that reported of pre-existing maternal medical conditions and complications of pregnancy.
We conducted a population-based validation study in 19 non-federal short-stay hospitals in Washington state with a stratified random sample of 4541 women who had live births between January 1, 2000, and December 31, 2000. True- and false-positive fractions were calculated.
Birth certificate and hospital discharge data combined had substantially higher true-positive fractions than did birth certificate data alone for cardiac disease (54% vs 29%), acute or chronic lung disease (24% vs 10%), gestational diabetes mellitus (93% vs 64%), established diabetes mellitus (97% vs 52%), active genital herpes (77% vs 38%), chronic hypertension (70% vs 47%), pregnancy-induced hypertension (74% vs 49%), renal disease (13% vs 2%), and placenta previa (70% vs 33%). For the 2 medical risk factors that are available only on birth certificates, true-positive fractions were 37% for established genital herpes and 68% for being seropositive for hepatitis B surface antigen.
In Washington, most medical conditions and complications of pregnancy that affect mothers are substantially underreported on birth certificates, but hospital discharge data are accurate in the reporting of gestational and established diabetes mellitus and placenta previa. Together, birth certificate and hospital discharge data are much superior to birth certificates alone in the reporting of gestational diabetes mellitus, active genital herpes, and chronic hypertension.
Available from: Onyebuchi Arah
- "We could find no validation studies of the use of administrative data to determine GBS colonization or infection status. However, validation of hospital discharge data for other pregnancy conditions has generally shown very high specificity, but sometimes low sensitivity . "
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We sought to characterize the relationship between individual group B streptococcus (GBS) colonization and pre-discharge postpartum methicillin resistant Staphylococcus aureus (MRSA) infection in United States women delivering at term. We also sought to examine the association between hospital GBS colonization prevalence and MRSA infection.
Materials and methods:
Data was from the Nationwide Inpatient Sample, a representative sample of United States community hospitals. Hierarchical regression models were used to estimate odds ratios adjusted for patient age, race, expected payer, and prepregnancy diabetes and hospital teaching status, urbanicity, ownership, size, and geographic region. We used multiple imputation for missing covariate data.
There were 3,136,595 deliveries and 462 cases of MRSA infection included in this study. The odds ratio for individual GBS colonization was 1.2 (95% confidence interval: 0.9 to 1.5). For a five-percent increase in the hospital prevalence of GBS colonization, the odds ratio was 0.9 (95% CI: 0.1 to 5.6).
The odds ratio estimate for the association of hospital GBS prevalence with MRSA infection is too imprecise to make conclusions about its magnitude and direction. Barring major bias in our estimates, individual GBS carriage does not appear to be strongly associated with predischarge postpartum MRSA infection.
Available from: Caitlyn Ellerbe
- "In 2004 the South Carolina birth certificate was revised: check boxes were added to differentiate between gestational and established diabetes; and information on maternal height, pre-pregnancy weight and weight at delivery was added. Moreover, a validation study conducted on a population-based sample of 4,541 women in Washington State (which uses a comparable birth certificate) compared information combined across birth certificate and hospital discharge data to medical record review, reporting a true positive fraction of 93.3 (95% CI, 86.9, 99.7) and a false positive fraction of 0.9 (95% CI: 0.5, 1.4)  for GDM. Previous studies have validated the reliability of maternal BMI from birth certificates –, with high correlation between self-report and clinically measured pre-pregnancy BMI that do not seem to differ by race/ethnicity, gestational age, or weight itself . "
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ABSTRACT: Background: Quantile regression, a robust semi-parametric approach, was used to examine the impact of gestational diabetes mellitus (GDM) across birthweight quantiles with a focus on maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG).
Methods: Using linked birth certificate, inpatient hospital and prenatal claims data we examined live singleton births to non-Hispanic white (NHW, 135,119) and non-Hispanic black (NHB, 76,675) women in South Carolina who delivered 28–44 weeks gestation in 2004–2008.
Results: At a maternal BMI of 30 kg/m2 at the 90th quantile of birthweight, exposure to GDM was associated with birthweights 84 grams (95% CI 57, 112) higher in NHW and 132 grams (95% CI: 104, 161) higher in NHB. Results at the 50th quantile were 34 grams (95% CI: 17, 51) and 78 grams (95% CI: 56, 100), respectively. At a maternal GWG of 13.5 kg at the 90th quantile of birthweight, exposure to GDM was associated with birthweights 83 grams (95% CI: 57, 109) higher in NHW and 135 grams (95% CI: 103, 167) higher in NHB. Results at the 50th quantile were 55 grams (95% CI: 40, 71) and 69 grams (95% CI: 46, 92), respectively.
Summary: Our findings indicate that GDM, maternal prepregnancy BMI and GWG increase birthweight more in NHW and NHB infants who are already at the greatest risk of macrosomia or being large for gestational age (LGA), that is those at the 90th rather than the median of the birthweight distribution.
Available from: Hannah E Knight
- "Approaches to validate the use of administrative health data for maternity statistics commonly fall into two categories. They either check the consistency of the administrative health data against medical records
[17-20,28] or against another source of maternity data such as national birth registers
[29-31]. Such external validation studies can be time consuming, costly and technically challenging, as well as raising ethical and information governance issues related to access and data linkage. "
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Information on maternity services is increasingly derived from national administrative health data. We evaluated how statistics on maternity care in England were affected by the completeness and consistency of data on “method of delivery” in a national dataset.
Singleton deliveries occurring between April 2009 and March 2010 in English NHS trusts were extracted from the Hospital Episode Statistics (HES) database. In HES, method of delivery can be entered twice: 1) as a procedure code in core fields, and 2) in supplementary maternity fields. We examined overall consistency of these data sources at a national level and among individual trusts. The impact of different analysis rules for handling inconsistent data was then examined using three maternity statistics: emergency caesarean section (CS) rate; third/fourth degree tear rate amongst instrumental deliveries, and elective CS rate for breech presentation.
We identified 629,049 singleton deliveries. Method of delivery was not entered as a procedure or in the supplementary fields in 0.8% and 12.5% of records, respectively. In 545,594 records containing both data items, method of delivery was coded consistently in 96.3% (kappa = 0.93; p < 0.001). Eleven of 136 NHS trusts had comparatively poor consistency (<92%) suggesting systematic data entry errors. The different analysis rules had a small effect on the statistics at a national level but the effect could be substantial for individual NHS trusts. The elective CS rate for breech was most sensitive to the chosen analysis rule.
Organisational maternity statistics are sensitive to inconsistencies in data on method of delivery, and publications of quality indicators should describe how such data were handled. Overall, method of delivery is coded consistently in English administrative health data.
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