​Who we are

The Harvard Program on Perinatal and Pediatric Pharmacoepidemiology includes investigators from Brigham and Women’s Hospital, Harvard Medical School, the Harvard T.H. Chan School of Public Health, and Stanford University School of Medicine. Our multidisciplinary team consists of epidemiologists, physicians, statisticians, and pharmacists.  LEARN MORE.

Interested in following us on social media? Check out our LinkedIn account! 

What we do

Our team generates evidence regarding the safety of medications used during pregnancy and in childhood. To accomplish this, we use advanced epidemiological and statistical methods applied primarily to large databases derived from health data collected in the context of routine medical care. LEARN MORE.

​We strive to produce studies of the highest scientific standard and rigor, and many of our studies have been published in high-impact journals. LEARN MORE.
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Our team members are also active teaching faculty at local institutions and lecture nationally and internationally on related topics. LEARN MORE.

Postdoc position available! 
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​Our collaborators at Stanford University are looking for a postdoctoral scholar with a background in epidemiology or a related field. They leverage real-world data and analytical methods to answer clinical questions about medications in pregnancy and postpartum. They have a collaborative and inclusive team and are highly committed to mentorship. Flexible start date, in-person/hybrid position. LEARN MORE. 

Have questions? Please contact [email protected]. 

Our most recent publications

Associations of maternal and paternal characteristics with cardiac malformations using real-world data and machine learning

• Author list: Jeremy P. Brown, Krista F. Huybrechts, Loreen Straub, Dominik Heider, Brian T. Bateman & Sonia Hernández-Díaz
• In this study, we used 2011-2021 MarketScan US insurance claims data to identify and characterize associations between maternal and paternal characteristics and non-chromosomal cardiac malformations.

Buprenorphine and Methadone Discontinuation During Pregnancy and the Postpartum Period: A Nationwide Cohort Study

• Author list: Chih-Wan Grace Lin, Brian T Bateman, Loreen Straub, Sonia Hernández-Díaz, Seanna M Vine, Hendrée E Jones, Hilary S Connery, Jonathan M Davis, Kathryn J Gray, Barry Lester, Elizabeth A Suarez, Ayesha C Sujan, Mishka Terplan, Krista F Huybrechts​
• In this nationwide study, pregnant patients with opioid use disorder had high risks of treatment discontinuation. Risks were higher for patients initiating buprenorphine compared to methadone. These findings underscore the urgent need to identify modifiable clinical and health-system factors to improve treatment retention.

​Antihypertensive Treatment Adherence during Pregnancy by Race and Ethnicity

• Author list: Elyse DiCesare, Krista F. Huybrechts, Brian T. Bateman, Joyce Lii, Loreen Straub
• This study shows adherence to antihypertensive treatment during pregnancy differs by race and ethnicity among individuals who initiate treatment to methyldopa, labetalol, or nifedipine early in pregnancy. Adherence during the second half of pregnancy is considerably lower among Black individuals as compared to White individuals. Given the importance of appropriate management of chronic hypertension to reduce the risk of severe adverse pregnancy outcomes, future research defining strategies to improve antihypertension adherence across racial and ethnic groups is an important priority.

Modern Evidence Generation on Medication Effectiveness and Safety During Pregnancy: Study Design Considerations

• Author list: Krista F Huybrechts, Brian T Bateman, Sonia Hernández-Díaz
• ​We discuss special considerations to keep in mind when emulating target trials of drug effects in pregnancy including the alignment of treatment initiation with the appropriate gestational age, conditioning on conception and fetal survival, and varying etiologically relevant time widows and outcome rates throughout gestation. The target trial framework can guide us through the specification of the causal questions, the study population and the treatment strategies to be compared and helps to identify biases and assumptions.​

Accounting for Twins and Other Multiple Births in Perinatal Studies of Live Births Conducted Using Healthcare Administration Data

• Jeremy P Brown, Jennifer J Yland, Paige L Williams, Krista F Huybrechts, Sonia Hernández-Díaz
• ​Twins and other multiple births complicate the analysis of perinatal studies. Common approaches to handling multiples in analyses of infant outcomes include restriction to singletons, counting outcomes at the pregnancy level (i.e., counting if at least one twin experienced a binary outcome), and infant-level analysis (i.e., including all infants and accounting for clustering of outcomes). Several healthcare administration databases only support restriction to singletons or pregnancy-level approaches; however, little attention has been given to the differences that can arise from these approaches. In their study published in Epidemiology, Jeremy P. Brown, Jennifer J. Yland, Paige L. Williams, Krista F. Huybrechts, and Sonia Hernández-Díaz demonstrate these differences using Monte Carlo simulations, algebraic formulas, and an applied example. Their analyses highlight the importance of understanding both the study question and the role of multiples in a study when choosing an analytical approach.

Maternal periconception hyperglycemia, preconception diabetes, and risk of major congenital malformations in offspring

• Ran S Rotem, Marc G Weisskopf, Brian Bateman, Krista Huybrechts, Sonia Hernández-Diáz
• ​The study examined the relationship between preconception maternal diabetes, associated periconceptional hyperglycemia, and the risk of congenital malformations in newborns. Findings revealed that maternal preconception diabetes was linked to multiple congenital heart defects, with risks that, although reduced, remained elevated even at periconceptional HbA1c levels below 5.6%. The results highlight a subgroup of pregnant women at higher risk for early neonatal complications and suggest potential pharmaceutical interventions to attenuate these risks. Furthermore, the study indicated that the connection between maternal preconception diabetes and congenital malformations may, in part, involve mechanisms that are independent of maternal serum glucose levels during early pregnancy.

Development and validation of claims-based algorithms for estimating gestational age of spontaneous abortion and termination​

• Yanmin Zhu, Sonia Hernandez-Diaz, Brian T Bateman, Kathryn J Gray, Ethan M Alt, Loreen Straub, Lockwood G Taylor, Rita Ouellet-Hellstrom, Yong Ma, Yandong Qiang, Seanna Vine, Helen Mogun, Wei Hua, Krista F Huybrechts
• ​We developed and validated algorithms to estimate gestational age (GA) for spontaneous abortion and termination cases in Medicaid data. Using linked medical records as the gold standard, we tested three approaches—median assignment, population-based sampling, and regression modeling. Approach 1 and 3 had similar performance, though Random forest models were slightly better. SABs and terminations can be studied in claims data with careful implementation of validated algorithms.​

Development and Validation of an Algorithm to Predict Stillbirth Gestational Age in Medicaid Billing Records

• Thuy N Thai, Nicole E Smolinski, Sabina Nduaguba, Steven Bird, Loreen Straub, Brian T Bateman, Sonia Hernandez-Diaz, Krista F Huybrechts, Sonja A Rasmussen, Almut G Winterstein
• ​After linking stillbirths identified in MAX 1999-2013 to Florida Fetal Death Records (FDRs) to obtain clinical estimates of gestational age (GA), we developed and validated an algorithm to predict GA for stillbirth, exhibiting good validity and consistent performance across different external validation samples. Our algorithm can facilitate research on stillbirths in the Medicaid population

Comparative Safety of In Utero Exposure to Buprenorphine Combined With Naloxone vs Buprenorphine Alone

• Loreen Straub, Brian T Bateman, Sonia Hernández-Díaz, Yanmin Zhu, Elizabeth A Suarez, Seanna M Vine, Hendrée E Jones, Hilary S Connery, Jonathan M Davis, Kathryn J Gray, Barry Lester, Mishka Terplan, Heidi Zakoul, Helen Mogun, Krista F Huybrechts
• ​This observational study noted similar and, in some instances, more favorable neonatal and maternal outcomes for pregnancies exposed to buprenorphine combined with naloxone compared to buprenorphine alone. The findings demonstrate comparative safety for the combination of buprenorphine with naloxone for the outcomes considered, supporting both formulations as reasonable options for treating opioid use disorder during pregnancy.