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Lenore Gensburg - One of the best experts on this subject based on the ideXlab platform.
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problems in using Birth Certificate files in the capture recapture model to estimate the completeness of case ascertainment in a population based Birth defects registry in new york state
Birth Defects Research Part A-clinical and Molecular Teratology, 2006Co-Authors: Ying Wang, Charlotte M Druschel, Philip K Cross, Synian Hwang, Lenore GensburgAbstract:BACKGROUND: The limitations and underlying assumptions of the capture-recapture methods have hindered their application in epidemiological settings, especially in evaluating the completeness of Birth defects registries. This study explored the possibility of using Birth Certificates as the secondary data source in a simple two-source capture-recapture model to estimate the completeness of case ascertainment of the Congenital Malformations Registry (CMR) for selected major Birth defects. METHODS: The CMR and the Birth Certificates were used as the primary and secondary sources, respectively. Children who were born in 1996–2001 and had selected major Birth defects were identified from the two sources. The accuracy of the diagnoses was examined by comparing the individual Birth defect categories of the children from the two sources. RESULTS: Discrepancies in Birth defect categories in the two data sources and false positives in the Birth Certificates were the major problems encountered in estimating the completeness of the CMR using the simple two-source capture-recapture method. The estimated completeness for selected major Birth defects was only about 71%. Stratified analyses resulted in relatively high estimated completeness for oral clefts (90%) and Down syndrome (88%). CONCLUSIONS: Although the Birth Certificate data was not a good source for estimating the completeness of case ascertainment of the CMR using capture-recapture methods, the analyses provided reasonable estimates for some conditions that were relatively easy to identify and diagnose at Birth, such as oral clefts and Down syndrome. Birth Defects Research (Part A) 76:772–777, 2006. 2006 Wiley-Liss, Inc.
Charlotte M Druschel - One of the best experts on this subject based on the ideXlab platform.
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residential mobility during pregnancy and the potential for ambient air pollution exposure misclassification
Environmental Research, 2010Co-Authors: Charlotte M Druschel, Lei Chen, Erin M Bell, Alissa R CatonAbstract:Abstract Studies of environmental exposures and adverse Birth outcomes often rely on maternal address at Birth obtained from the Birth Certificate to classify exposure. Although the gestational age of interest is often early pregnancy, maternal addresses are not available for women who move during pregnancy when using maternal addresses abstracted from Birth Certificates. The aim of this study was to explore the extent of ambient air pollutant exposure misclassification due to maternal residential mobility during pregnancy among the subgroup of a New York Birth cohort. The authors obtained the maternal addresses at Birth from the New York Birth Certificate, and the maternal addresses by gestational age from the National Birth Defect Prevention Study for New York participants for the study period 1997–2002. Among the 1324 mothers, 172 (13.0%) moved once during pregnancy and 46 (3.5%) moved at least twice. When accounting for multiple addresses among some individuals, of the 218 mothers who moved, 38 (2.9%) moved in the 3rd to 8th weeks after conception (critical period, not exclusive from the 1st trimester), 80 (6.0%) moved in the 1st trimester, 112 (8.5%) in the 2nd trimester, and 51 (3.9%) in the 3rd trimester. Air monitoring data from the New York Department of Environmental Conservation were used as surrogates to compute the ambient ozone and PM10 exposures for mothers with complete residential data. This study estimates exposure using maternal address at Birth obtained from Birth Certificates, compared to exposure estimates when using maternal addresses by gestational age obtained from maternal interview, the gold standard. Average exposures during pregnancy were similar when using interview based versus Birth Certificate addresses (0.035 vs. 0.035 ppm for ozone, and 20.11 vs. 20.09 μg/m3 for PM10, respectively). Kappa statistics and percent agreement were calculated to measure the degree of agreement for dichotomous exposure measurements ( =median) and weighted kappa for quartile exposure measurements by gestational age. All the statistics indicated a high agreement between the two measurements. For mothers who moved, the majority maintained their address in the same exposure region. Given the low mobility during pregnancy and the short distance moved, the exposure assignment did not change substantially when using the more accurate interview based addresses in this study. However, the level of observed agreement may decrease for studies that require smaller geographic zones for exposure assignments or with more mobile study populations.
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problems in using Birth Certificate files in the capture recapture model to estimate the completeness of case ascertainment in a population based Birth defects registry in new york state
Birth Defects Research Part A-clinical and Molecular Teratology, 2006Co-Authors: Ying Wang, Charlotte M Druschel, Philip K Cross, Synian Hwang, Lenore GensburgAbstract:BACKGROUND: The limitations and underlying assumptions of the capture-recapture methods have hindered their application in epidemiological settings, especially in evaluating the completeness of Birth defects registries. This study explored the possibility of using Birth Certificates as the secondary data source in a simple two-source capture-recapture model to estimate the completeness of case ascertainment of the Congenital Malformations Registry (CMR) for selected major Birth defects. METHODS: The CMR and the Birth Certificates were used as the primary and secondary sources, respectively. Children who were born in 1996–2001 and had selected major Birth defects were identified from the two sources. The accuracy of the diagnoses was examined by comparing the individual Birth defect categories of the children from the two sources. RESULTS: Discrepancies in Birth defect categories in the two data sources and false positives in the Birth Certificates were the major problems encountered in estimating the completeness of the CMR using the simple two-source capture-recapture method. The estimated completeness for selected major Birth defects was only about 71%. Stratified analyses resulted in relatively high estimated completeness for oral clefts (90%) and Down syndrome (88%). CONCLUSIONS: Although the Birth Certificate data was not a good source for estimating the completeness of case ascertainment of the CMR using capture-recapture methods, the analyses provided reasonable estimates for some conditions that were relatively easy to identify and diagnose at Birth, such as oral clefts and Down syndrome. Birth Defects Research (Part A) 76:772–777, 2006. 2006 Wiley-Liss, Inc.
Sascha Dublin - One of the best experts on this subject based on the ideXlab platform.
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trends in elective labor induction for six united states health plans 2001 2007
Journal of Womens Health, 2014Co-Authors: Susan E Andrade, Robert L Davis, Sascha Dublin, Karin Johnson, Rod L Walker, Lyndsay A Avalos, Sarah J Beaton, Lisa J Herrinton, Pamala A PawloskiAbstract:Abstract Background: To describe trends in labor induction, including elective induction, from 2001 to 2007 for six U.S. health plans and to examine the validity of induction measures derived from Birth Certificate and health plan data. Methods: This retrospective cohort study included 339,123 deliveries at 35 weeks' gestation or greater. Linked health plan and Birth Certificate data provided information about induction, maternal medical conditions, and pregnancy complications. Induction was defined from diagnosis and procedure codes and Birth Certificate data and considered elective if no accepted indication was coded. We calculated induction prevalence across health plans and years. At four health plans, we reviewed medical records to validate induction measures. Results: Based on electronic data, induction prevalence rose from 28% in 2001 to 32% in 2005, then declined to 29% in 2007. The trend was driven by changes in the prevalence of apparent elective induction, which rose from 11% in 2001 to 14% in ...
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validation of an algorithm to estimate gestational age in electronic health plan databases
Pharmacoepidemiology and Drug Safety, 2013Co-Authors: Susan E Andrade, Pamela E Scott, Robert L Davis, Marsha A Raebel, Sascha Dublin, Pamala A Pawloski, Tarek A Hammad, William O Cooper, Simone P Pinheiro, David H SmithAbstract:Purpose To validate an algorithm that uses delivery date and diagnosis codes to define gestational age at Birth in electronic health plan databases. Methods Using data from 225 384 live born deliveries to women aged 15–45 years in 2001–2007 within eight of the 11 health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program, we compared (1) the algorithm-derived gestational age versus the “gold-standard” gestational age obtained from the infant Birth Certificate file and (2) the prenatal exposure status of two antidepressants (fluoxetine and sertraline) and two antibiotics (amoxicillin and azithromycin) as determined by the algorithm-derived versus the gold-standard gestational age. Results The mean algorithm-derived gestational age at Birth was lower than the mean obtained from the Birth Certificate file among singleton deliveries (267.9 vs 273.5 days) but not among multiple-gestation deliveries (253.9 vs 252.6 days). The algorithm-derived prenatal exposure to the antidepressants had a sensitivity and a positive predictive value of ≥95%, and a specificity and a negative predictive value of almost 100%. Sensitivity and positive predictive value were both ≥90%, and specificity and negative predictive value were both >99% for the antibiotics. Conclusions A gestational age algorithm based upon electronic health plan data correctly classified medication exposure status in most live born deliveries, but trimester-specific misclassification may be higher for drugs typically used for short durations. Copyright © 2013 John Wiley & Sons, Ltd.
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validity of health plan and Birth Certificate data for pregnancy research
Pharmacoepidemiology and Drug Safety, 2013Co-Authors: Susan E Andrade, Pamela E Scott, Robert L Davis, Darios Getahun, Craig T Cheetham, Marsha A Raebel, Sengwee Toh, Sascha Dublin, Pamala A Pawloski, Tarek A HammadAbstract:Purpose To evaluate the validity of health plan and Birth Certificate data for pregnancy research. Methods A retrospective study was conducted using administrative and claims data from 11 U.S. health plans and corresponding Birth Certificate data from state health departments. Diagnoses, drug dispensings, and procedure codes were used to identify infant outcomes (cardiac defects, anencephaly, preterm Birth, and neonatal intensive care unit [NICU] admission) and maternal diagnoses (asthma and systemic lupus erythematosus [SLE]) recorded in the health plan data for live born deliveries between January 2001 and December 2007. A random sample of medical charts (n = 802) was abstracted for infants and mothers identified with the specified outcomes. Information on newborn, maternal, and paternal characteristics (gestational age at Birth, Birth weight, previous pregnancies and live Births, race/ethnicity) was also abstracted and compared to Birth Certificate data. Positive predictive values (PPVs) were calculated with documentation in the medical chart serving as the gold standard. Results PPVs were 71% for cardiac defects, 37% for anencephaly, 87% for preterm Birth, and 92% for NICU admission. PPVs for algorithms to identify maternal diagnoses of asthma and SLE were ≥ 93%. Our findings indicated considerable agreement (PPVs > 90%) between Birth Certificate and medical record data for measures related to Birth weight, gestational age, prior obstetrical history, and race/ethnicity. Conclusions Health plan and Birth Certificate data can be useful to accurately identify some infant outcomes, maternal diagnoses, and newborn, maternal, and paternal characteristics. Other outcomes and variables may require medical record review for validation. Copyright © 2012 John Wiley & Sons, Ltd.
Andrea J Sharma - One of the best experts on this subject based on the ideXlab platform.
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gestational weight loss comparison between the Birth Certificate and the medical record florida 2012
Maternal and Child Health Journal, 2019Co-Authors: Shin Y Kim, Marie A Bailey, Jaylan Richardson, Cheryl A S Mcfarland, William M Sappenfield, Sabrina Luke, Andrea J SharmaAbstract:Objective Examine agreement with the medical record (MR) when gestational weight loss (GWL) on the Florida Birth Certificate (BC) is ≥ 0 pounds (lbs). Methods In 2012, 3923 Florida-resident women had a live, singleton Birth where BC indicated GWL ≥ 0 lbs. Of these, we selected a stratified random sample of 2141 and abstracted from the MR prepregnancy and delivery weight data used to compute four estimates of GWL (delivery minus prepregnancy weight) from different sources found within the MR (first prenatal visit record, nursing admission record, labor/delivery records, BC worksheet). We assessed agreement between the BC and MR estimates for GWL categorized as 0, 1–10, 11–19, and ≥ 20 lbs. Results Prepregnancy or delivery weight was missing or source not in the MR for 23–81% of records. Overall agreement on GWL between the BC and the four MR estimates ranged from 39.1 to 57.2%. Agreement by GWL category ranged from 10.6 to 38.0% for 0 lbs, 47.6 to 64.3% for 1–10 lbs, 49.5 to 60.0% for 11–19 lbs, and 47.8 to 67.7% for ≥ 20 lbs. Conclusions Prepregnancy and delivery weight were frequently missing from the MR or inconsistently documented across the different sources. When the BC indicated GWL ≥ 0 lbs, agreement with different sources of the MR was moderate to poor revealing the need to reduce missing data and better understand the quality of weight data in the MR.
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prevalence estimates of gestational diabetes mellitus in the united states pregnancy risk assessment monitoring system prams 2007 2010
Preventing Chronic Disease, 2014Co-Authors: Carla L Desisto, Shin Y Kim, Andrea J SharmaAbstract:Introduction The true prevalence of gestational diabetes mellitus (GDM) is unknown. The objective of this study was 1) to provide the most current GDM prevalence reported on the Birth Certificate and the Pregnancy Risk Assessment Monitoring System (PRAMS) questionnaire and 2) to compare GDM prevalence from PRAMS across 2007-2008 and 2009-2010. Methods We examined 2010 GDM prevalence reported on Birth Certificate or PRAMS questionnaire and concordance between the sources. We included 16 states that adopted the 2003 revised Birth Certificate. We also examined trends from 2007 through 2010 and included 21 states that participated in PRAMS for all 4 years. We combined GDM prevalence across 2-year intervals and conducted t tests to examine differences. Data were weighted to represent all women delivering live Births in each state. Results GDM prevalence in 2010 was 4.6% as reported on the Birth Certificate, 8.7% as reported on the PRAMS questionnaire, and 9.2% as reported on either the Birth Certificate or questionnaire. The agreement between sources was 94.1% (percent positive agreement = 3.7%, percent negative agreement = 90.4%). There was no significant difference in GDM prevalence between 2007-2008 (8.1%) and 2009-2010 (8.5%, P = .15). Conclusion Our results indicate that GDM prevalence is as high as 9.2% and is more likely to be reported on the PRAMS questionnaire than the Birth Certificate. We found no statistical difference in GDM prevalence between the 2 phases. Further studies are needed to understand discrepancies in reporting GDM by data source.
Pamala A Pawloski - One of the best experts on this subject based on the ideXlab platform.
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trends in elective labor induction for six united states health plans 2001 2007
Journal of Womens Health, 2014Co-Authors: Susan E Andrade, Robert L Davis, Sascha Dublin, Karin Johnson, Rod L Walker, Lyndsay A Avalos, Sarah J Beaton, Lisa J Herrinton, Pamala A PawloskiAbstract:Abstract Background: To describe trends in labor induction, including elective induction, from 2001 to 2007 for six U.S. health plans and to examine the validity of induction measures derived from Birth Certificate and health plan data. Methods: This retrospective cohort study included 339,123 deliveries at 35 weeks' gestation or greater. Linked health plan and Birth Certificate data provided information about induction, maternal medical conditions, and pregnancy complications. Induction was defined from diagnosis and procedure codes and Birth Certificate data and considered elective if no accepted indication was coded. We calculated induction prevalence across health plans and years. At four health plans, we reviewed medical records to validate induction measures. Results: Based on electronic data, induction prevalence rose from 28% in 2001 to 32% in 2005, then declined to 29% in 2007. The trend was driven by changes in the prevalence of apparent elective induction, which rose from 11% in 2001 to 14% in ...
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validation of an algorithm to estimate gestational age in electronic health plan databases
Pharmacoepidemiology and Drug Safety, 2013Co-Authors: Susan E Andrade, Pamela E Scott, Robert L Davis, Marsha A Raebel, Sascha Dublin, Pamala A Pawloski, Tarek A Hammad, William O Cooper, Simone P Pinheiro, David H SmithAbstract:Purpose To validate an algorithm that uses delivery date and diagnosis codes to define gestational age at Birth in electronic health plan databases. Methods Using data from 225 384 live born deliveries to women aged 15–45 years in 2001–2007 within eight of the 11 health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program, we compared (1) the algorithm-derived gestational age versus the “gold-standard” gestational age obtained from the infant Birth Certificate file and (2) the prenatal exposure status of two antidepressants (fluoxetine and sertraline) and two antibiotics (amoxicillin and azithromycin) as determined by the algorithm-derived versus the gold-standard gestational age. Results The mean algorithm-derived gestational age at Birth was lower than the mean obtained from the Birth Certificate file among singleton deliveries (267.9 vs 273.5 days) but not among multiple-gestation deliveries (253.9 vs 252.6 days). The algorithm-derived prenatal exposure to the antidepressants had a sensitivity and a positive predictive value of ≥95%, and a specificity and a negative predictive value of almost 100%. Sensitivity and positive predictive value were both ≥90%, and specificity and negative predictive value were both >99% for the antibiotics. Conclusions A gestational age algorithm based upon electronic health plan data correctly classified medication exposure status in most live born deliveries, but trimester-specific misclassification may be higher for drugs typically used for short durations. Copyright © 2013 John Wiley & Sons, Ltd.
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validity of health plan and Birth Certificate data for pregnancy research
Pharmacoepidemiology and Drug Safety, 2013Co-Authors: Susan E Andrade, Pamela E Scott, Robert L Davis, Darios Getahun, Craig T Cheetham, Marsha A Raebel, Sengwee Toh, Sascha Dublin, Pamala A Pawloski, Tarek A HammadAbstract:Purpose To evaluate the validity of health plan and Birth Certificate data for pregnancy research. Methods A retrospective study was conducted using administrative and claims data from 11 U.S. health plans and corresponding Birth Certificate data from state health departments. Diagnoses, drug dispensings, and procedure codes were used to identify infant outcomes (cardiac defects, anencephaly, preterm Birth, and neonatal intensive care unit [NICU] admission) and maternal diagnoses (asthma and systemic lupus erythematosus [SLE]) recorded in the health plan data for live born deliveries between January 2001 and December 2007. A random sample of medical charts (n = 802) was abstracted for infants and mothers identified with the specified outcomes. Information on newborn, maternal, and paternal characteristics (gestational age at Birth, Birth weight, previous pregnancies and live Births, race/ethnicity) was also abstracted and compared to Birth Certificate data. Positive predictive values (PPVs) were calculated with documentation in the medical chart serving as the gold standard. Results PPVs were 71% for cardiac defects, 37% for anencephaly, 87% for preterm Birth, and 92% for NICU admission. PPVs for algorithms to identify maternal diagnoses of asthma and SLE were ≥ 93%. Our findings indicated considerable agreement (PPVs > 90%) between Birth Certificate and medical record data for measures related to Birth weight, gestational age, prior obstetrical history, and race/ethnicity. Conclusions Health plan and Birth Certificate data can be useful to accurately identify some infant outcomes, maternal diagnoses, and newborn, maternal, and paternal characteristics. Other outcomes and variables may require medical record review for validation. Copyright © 2012 John Wiley & Sons, Ltd.