- Reproductive Health and Contraception
- Ectopic Pregnancy Diagnosis and Management
- Reproductive Health and Technologies
- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
- Maternal and Perinatal Health Interventions
- Global Maternal and Child Health
- Pregnancy and preeclampsia studies
- Bayesian Methods and Mixture Models
- COVID-19 Impact on Reproduction
- Insurance, Mortality, Demography, Risk Management
- Advanced Causal Inference Techniques
- Birth, Development, and Health
- Child Nutrition and Water Access
- Statistical Methods in Clinical Trials
- COVID-19 Clinical Research Studies
- COVID-19 epidemiological studies
- Vaccine Coverage and Hesitancy
- HIV/AIDS Research and Interventions
- Healthcare Policy and Management
- Health disparities and outcomes
- Health, Environment, Cognitive Aging
- Statistical Methods in Epidemiology
- Surgical Sutures and Adhesives
- Organ and Tissue Transplantation Research
Mathematica Policy Research
2020-2024
The University of Texas at Austin
2018-2021
To compare outcomes before and after implementation of medical abortion (termination pregnancy) without ultrasound via telemedicine.Cohort analysis.The three main providers.Medical abortions at home ≤69 days' gestation in two cohorts: traditional model (in-person with ultrasound, n = 22 158) from January to March 2020 versus telemedicine-hybrid (either person or telemedicine 29 984, whom 18 435 had no-test telemedicine) between April June 2020. Sample (n 52 142) comprises 85% all provided...
This study assesses changes in online telemedicine requests to self-manage abortions with medications before vs after the Dobbs v Jackson Women’s Health Organization Supreme Court decision overturning Roe Wade .
In Brief Increased demand for self-managed medication abortion in states with in-clinic restrictions or high infection rates during the coronavirus disease 2019 (COVID-19) pandemic demonstrates need remote care models.
Objectives In most European countries, patients seeking medication abortion during the COVID-19 pandemic are still required to attend healthcare settings in person. We assessed whether demand for self-managed provided by online telemedicine increased following emergence of COVID-19. Methods examined 3915 requests service Women on Web (WoW) between 1 January 2019 and June 2020. used regression discontinuity compare request rates eight countries before after they implemented lockdown measures...
Many studies have reported associations between later-life cognition and socioeconomic position in childhood, young adulthood, mid-life. However, the vast majority of these are unable to quantify how vary over time with respect several demographic factors. Varying coefficient (VC) models, which treat covariate effects a linear model as nonparametric functions additional effect modifiers, offer an appealing way overcome limitations. Unfortunately, state-of-the-art VC modeling methods require...
To examine demand for abortion medications through an online telemedicine service in the United States.
<h3>Importance</h3> People in the US have been seeking self-managed abortions outside formal health care system using medications obtained through online telemedicine. However, little is known about this practice, including potential motivating factors. <h3>Objective</h3> To examine individual reasons for accessing medication abortion an telemedicine service as well associations between state- and county-level factors rate of requests. <h3>Design, Setting, Participants</h3> This...
Association of Texas' Abortion Ban With the Number Facility-Based Abortions in Texas and Surrounding States
This cross-sectional study examines trends in the demand and characteristics motivations of individuals who requested advance provision abortion medications.
Low birth-weight is a major risk factor for perinatal death in sub-Saharan Africa, but the relative contribution of determinants are difficult to disentangle low resource settings. We sought delineate relationship between and maternal pre-eclampsia across gestation low-resource obstetric setting. Prospective cohort study tertiary referral centre urban Uganda, including 971 cases 1461 control pregnancies 28 42 weeks gestation. Nonlinear modeling versus status Models were adjusted...
This article introduces BART with Targeted Smoothing, or tsBART, a new Bayesian tree-based model for nonparametric regression. The goal of tsBART is to introduce smoothness over single target covariate $t$ while not necessarily requiring other covariates $x$. based on the Additive Regression Trees (BART) model, an ensemble regression trees. extends by parameterizing each tree's terminal nodes smooth functions rather than independent scalars. Like BART, captures complex nonlinear...
Patients attending US abortion clinics may consider or try self-managing their before coming to the clinic, yet little is known about factors associated with self-management behavior.
A rapid increase in restrictive abortion legislation the United States has sparked renewed interest self-managed as a response to clinic access barriers. Yet little is known about knowledge of, in, and experiences of medication among patients who obtain care clinic.
OBJECTIVE: To evaluate outcomes with simultaneous administration of mifepristone and misoprostol for medical abortion at 63 days gestation or less in the year after its implementation a British clinic system. METHODS: We conducted retrospective cohort study using deidentified data from electronic booking complications databases records women who underwent Pregnancy Advisory Service. Our primary outcome was treatment success dosing compared regimen 24- to 48-hour interval between medications....
Objective: Investigate the role of Ryan White HIV/AIDS Program (RWHAP) – which funds services for vulnerable and historically disadvantaged populations with HIV in reducing health inequities among people over a 10-year horizon. Design: We use an agent-based microsimulation model to incorporate complexity program long-time Methods: composite measure (the Theil index) evaluate equity implications RWHAP each four subgroups (based on race ethnicity, age, gender, transmission category) two...
Objectives: In most European countries, patients seeking medication abortion during the COVID-19 pandemic are still expected to attend healthcare settings in person despite lockdown measures and infection risk. We assessed whether demand for self-managed provided by a fully remote online telemedicine service increased following emergence of COVID-19. Design: used regression discontinuity compare number requests Women on Web eight countries before after they implemented slow transmission....
Objective To compare the effectiveness, safety and acceptability of medical abortion before after introduction no-test telemedicine Design Cohort study Setting The three main providers in England Population All patients having an early (comprising 85% all abortions performed nationally) Methods Comparison hybrid model vs. traditional (blanket in-person provision including ultrasound), adjusted for baseline differences Main outcome measures Access: waiting time, gestation Effectiveness:...
We introduce Targeted Smooth Bayesian Causal Forests (tsBCF), a nonparametric approach for estimating heterogeneous treatment effects which vary smoothly over single covariate in the observational data setting. The tsBCF method induces smoothness by parameterizing terminal tree nodes with smooth functions, and allows separate regularization of versus prognostic effect control covariates. Smoothing parameters can be chosen to reflect prior knowledge or tuned data-dependent way. use analyze...
We introduce Targeted Smooth Bayesian Causal Forests (tsBCF), a nonparametric approach for estimating heterogeneous treatment effects which vary smoothly over single covariate in the observational data setting. The tsBCF method induces smoothness by parameterizing terminal tree nodes with smooth functions and allows separate regularization of vs. prognostic effect control covariates. Smoothing parameters can be chosen to reflect prior knowledge or tuned data-dependent way. use analyze new...
This paper introduces aggregate Bayesian Causal Forests (aBCF), a new model for causal inference using aggregated data. Aggregated data are common in policy evaluations where we observe individuals such as students, but participation an intervention is determined at higher level of aggregation, schools implementing curriculum. Interventions often have millions far fewer higher-level units, making aggregation computationally attractive. To analyze data, must account heteroskedasticity and...
The linear varying coefficient models posits a relationship between an outcome and covariates in which the covariate effects are modeled as functions of additional effect modifiers. Despite long history study use statistics econometrics, state-of-the-art modeling methods cannot accommodate multivariate modifiers without imposing restrictive functional form assumptions or involving computationally intensive hyperparameter tuning. In response, we introduce VCBART, flexibly estimates model...