Validation of an algorithm to estimate gestational age in electronic health plan databases

Qian Li, Susan E. Andrade, William O. Cooper, Robert Davis, Sascha Dublin, Tarek A. Hammad, Pamala A. Pawloski, Simone P. Pinheiro, Marsha A. Raebel, Pamela E. Scott, David H. Smith, Inna Dashevsky, Katherine Haffenreffer, Karin E. Johnson, Sengwee Toh

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

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 225384 live born deliveries to women aged 15-45years 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 273.5days) but not among multiple-gestation deliveries (253.9 vs 252.6days). 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.

Original languageEnglish (US)
Pages (from-to)524-532
Number of pages9
JournalPharmacoepidemiology and Drug Safety
Volume22
Issue number5
DOIs
StatePublished - May 1 2013

Fingerprint

Gestational Age
Databases
Health
Birth Certificates
Gold
Antidepressive Agents
Parturition
Anti-Bacterial Agents
Sertraline
Pregnancy
Azithromycin
Fluoxetine
Amoxicillin
Program Evaluation
Pharmaceutical Preparations

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Pharmacology (medical)

Cite this

Validation of an algorithm to estimate gestational age in electronic health plan databases. / Li, Qian; Andrade, Susan E.; Cooper, William O.; Davis, Robert; Dublin, Sascha; Hammad, Tarek A.; Pawloski, Pamala A.; Pinheiro, Simone P.; Raebel, Marsha A.; Scott, Pamela E.; Smith, David H.; Dashevsky, Inna; Haffenreffer, Katherine; Johnson, Karin E.; Toh, Sengwee.

In: Pharmacoepidemiology and Drug Safety, Vol. 22, No. 5, 01.05.2013, p. 524-532.

Research output: Contribution to journalArticle

Li, Q, Andrade, SE, Cooper, WO, Davis, R, Dublin, S, Hammad, TA, Pawloski, PA, Pinheiro, SP, Raebel, MA, Scott, PE, Smith, DH, Dashevsky, I, Haffenreffer, K, Johnson, KE & Toh, S 2013, 'Validation of an algorithm to estimate gestational age in electronic health plan databases', Pharmacoepidemiology and Drug Safety, vol. 22, no. 5, pp. 524-532. https://doi.org/10.1002/pds.3407
Li, Qian ; Andrade, Susan E. ; Cooper, William O. ; Davis, Robert ; Dublin, Sascha ; Hammad, Tarek A. ; Pawloski, Pamala A. ; Pinheiro, Simone P. ; Raebel, Marsha A. ; Scott, Pamela E. ; Smith, David H. ; Dashevsky, Inna ; Haffenreffer, Katherine ; Johnson, Karin E. ; Toh, Sengwee. / Validation of an algorithm to estimate gestational age in electronic health plan databases. In: Pharmacoepidemiology and Drug Safety. 2013 ; Vol. 22, No. 5. pp. 524-532.
@article{e629e4b538584a56b324ca2b06d958af,
title = "Validation of an algorithm to estimate gestational age in electronic health plan databases",
abstract = "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 225384 live born deliveries to women aged 15-45years 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 273.5days) but not among multiple-gestation deliveries (253.9 vs 252.6days). 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.",
author = "Qian Li and Andrade, {Susan E.} and Cooper, {William O.} and Robert Davis and Sascha Dublin and Hammad, {Tarek A.} and Pawloski, {Pamala A.} and Pinheiro, {Simone P.} and Raebel, {Marsha A.} and Scott, {Pamela E.} and Smith, {David H.} and Inna Dashevsky and Katherine Haffenreffer and Johnson, {Karin E.} and Sengwee Toh",
year = "2013",
month = "5",
day = "1",
doi = "10.1002/pds.3407",
language = "English (US)",
volume = "22",
pages = "524--532",
journal = "Pharmacoepidemiology and Drug Safety",
issn = "1053-8569",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

TY - JOUR

T1 - Validation of an algorithm to estimate gestational age in electronic health plan databases

AU - Li, Qian

AU - Andrade, Susan E.

AU - Cooper, William O.

AU - Davis, Robert

AU - Dublin, Sascha

AU - Hammad, Tarek A.

AU - Pawloski, Pamala A.

AU - Pinheiro, Simone P.

AU - Raebel, Marsha A.

AU - Scott, Pamela E.

AU - Smith, David H.

AU - Dashevsky, Inna

AU - Haffenreffer, Katherine

AU - Johnson, Karin E.

AU - Toh, Sengwee

PY - 2013/5/1

Y1 - 2013/5/1

N2 - 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 225384 live born deliveries to women aged 15-45years 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 273.5days) but not among multiple-gestation deliveries (253.9 vs 252.6days). 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.

AB - 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 225384 live born deliveries to women aged 15-45years 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 273.5days) but not among multiple-gestation deliveries (253.9 vs 252.6days). 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.

UR - http://www.scopus.com/inward/record.url?scp=84877342928&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84877342928&partnerID=8YFLogxK

U2 - 10.1002/pds.3407

DO - 10.1002/pds.3407

M3 - Article

C2 - 23335117

AN - SCOPUS:84877342928

VL - 22

SP - 524

EP - 532

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

SN - 1053-8569

IS - 5

ER -