Development and evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic health records

Canelón, Silvia P.; Burris, Heather H.; Levine, Lisa D.; Boland, Mary Regina

doi:10.1016/j.ijmedinf.2020.104339

Cited by 16 publications

(13 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A total of 63 334 deliveries were identified using a previously developed algorithm that extracts delivery episode details and delivery dates from the EHR. 33 These delivery episode details allowed us to (1) identify complications present for each of a patient’s deliveries and (2) examine the association of SCT 24 with a patient’s likelihood of experiencing a stillbirth. We linked this information with encounter-level information on patient age and marital status at the time of the encounter, self-reported race and ethnicity, ABO blood type, and Rhesus factor ( Figure 1 ).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Stillbirth Among Pregnant People With Sickle Cell Trait

2021

Self Cite

View full text Add to dashboard Cite

Key Points Question Is sickle cell trait associated with an increased risk of stillbirth? Findings In this cohort study of 50 560 patients and 63 334 deliveries (including 2482 deliveries from patients with sickle cell trait and 215 deliveries from patients with sickle cell disease) both sickle cell trait and sickle cell disease were associated with increased risk of stillbirth after adjusting for known risk factors. Meaning This study found both sickle cell trait and disease to be associated with an increased risk of stillbirth, suggesting that sickle cell carriers would benefit from additional risk assessment during pregnancy.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Native Hawaiian or Pacific Islander (0.1%), White(33.7%), other or mixed (3.2%), and unknown (1.7%). The groupings of "other or mixed" reflected the structured data available in the EHR and not a custom grouping particular to this study.…”

mentioning

confidence: 99%

Evaluation of Stillbirth Among Pregnant People With Sickle Cell Trait

2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…We obtained EHR data from 1,060,100 female patients treated at Penn Medicine, with inpatient and outpatient visits between 2010 and 2017. A previously developed algorithm called MADDIE identified 50,560 patients who delivered a baby at Penn Medicine having 63,334 distinct deliveries [ 23 ]. Figure 1 illustrates the study selection process of the cohort.…”

Section: Resultsmentioning

confidence: 99%

“…We used EHR data obtained from 4 different hospitals within the Penn Medicine system: the Hospital of the University of Pennsylvania, the Pennsylvania Hospital, Penn Presbyterian Hospital, and Chester County Hospital. The deliveries were identified using a previously developed algorithm called Method to Acquire Delivery Date Information from Electronic Health Records (MADDIE) [ 23 ]. The MADDIE identified deliveries occurred between 2010 and 2017.…”

Section: Methodsmentioning

confidence: 99%

Medication-Wide Association Study Using Electronic Health Record Data of Prescription Medication Exposure and Multifetal Pregnancies: Retrospective Study

Davidson¹,

Canelón²,

Boland³

2022

JMIR Med Inform

Self Cite

View full text Add to dashboard Cite

Background Medication-wide association studies (MWAS) have been applied to assess the risk of individual prescription use and a wide range of health outcomes, including cancer, acute myocardial infarction, acute liver failure, acute renal failure, and upper gastrointestinal ulcers. Current literature on the use of preconception and periconception medication and its association with the risk of multiple gestation pregnancies (eg, monozygotic and dizygotic) is largely based on assisted reproductive technology (ART) cohorts. However, among non-ART pregnancies, it is unknown whether other medications increase the risk of multifetal pregnancies. Objective This study aimed to investigate the risk of multiple gestational births (eg, twins and triplets) following preconception and periconception exposure to prescription medications in patients who delivered at Penn Medicine. Methods We used electronic health record data between 2010 and 2017 on patients who delivered babies at Penn Medicine, a health care system in the Greater Philadelphia area. We explored 3 logistic regression models: model 1 (no adjustment); model 2 (adjustment for maternal age); and model 3—our final logistic regression model (adjustment for maternal age, ART use, and infertility diagnosis). In all models, multiple births (MBs) were our outcome of interest (binary outcome), and each medication was assessed separately as a binary variable. To assess our MWAS model performance, we defined ART medications as our gold standard, given that these medications are known to increase the risk of MB. Results Of the 63,334 distinct deliveries in our cohort, only 1877 pregnancies (2.96%) were prescribed any medication during the preconception and first trimester period. Of the 123 medications prescribed, we found 26 (21.1%) medications associated with MB (using nominal P values) and 10 (8.1%) medications associated with MB (using Bonferroni adjustment) in fully adjusted model 3. We found that our model 3 algorithm had an accuracy of 85% (using nominal P values) and 89% (using Bonferroni-adjusted P values). Conclusions Our work demonstrates the opportunities in applying the MWAS approach with electronic health record data to explore associations between preconception and periconception medication exposure and the risk of MB while identifying novel candidate medications for further study. Overall, we found 3 novel medications linked with MB that could be explored in further work; this demonstrates the potential of our method to be used for hypothesis generation.

show abstract

“…In order to conduct our analysis of stillbirth and preterm birth, we first obtained data on patients who had deliveries at Penn Medicine hospitals from 2010 to 2017. We used a previously developed and validated algorithm by Canelón et al [7] to identify deliveries from Penn Medicine EHRs. After removing 17,305 observations with either missing values in the patient address or with patients living outside of the City of Philadelphia, our dataset contained a total of 46,029 deliveries at hospitals within the University of Pennsylvania Health System between 2010 and 2017.…”

Section: Motivating Datamentioning

confidence: 99%

Uncovering Patterns for Adverse Pregnancy Outcomes with Spatial Analysis: Evidence from Philadelphia

Balocchi¹,

Bai²,

Liu³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Studying the determinants of adverse pregnancy outcomes like stillbirth and preterm birth is of considerable interest in epidemiology. Understanding the role of both individual and community risk factors for these outcomes is crucial for planning appropriate clinical and public health interventions. With this goal, we develop geospatial mixed effects logistic regression models for adverse pregnancy outcomes. Our models account for both spatial autocorrelation and heterogeneity between neighborhoods. To mitigate the low incidence of stillbirth and preterm births in our data, we explore using class rebalancing techniques to improve predictive power. To assess the informative value of the covariates in our models, we use posterior distributions of their coefficients to gauge how well they can be distinguished from zero. As a case study, we model stillbirth and preterm birth in the city of Philadelphia, incorporating both patient-level data from electronic health records (EHR) data and publicly available neighborhood data at the census tract level. We find that patient-level features like self-identified race and ethnicity were highly informative for both outcomes. Neighborhood-level factors were also informative, with poverty important for stillbirth and crime important for preterm birth. Finally, we identify the neighborhoods in Philadelphia at highest risk of stillbirth and preterm birth.

show abstract

Development and evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic health records

Cited by 16 publications

References 32 publications

Evaluation of Stillbirth Among Pregnant People With Sickle Cell Trait

Evaluation of Stillbirth Among Pregnant People With Sickle Cell Trait

Medication-Wide Association Study Using Electronic Health Record Data of Prescription Medication Exposure and Multifetal Pregnancies: Retrospective Study

Uncovering Patterns for Adverse Pregnancy Outcomes with Spatial Analysis: Evidence from Philadelphia

Contact Info

Product

Resources

About