Jiayi (Jessie) Tong

I am an assistant professor in the Department of Biostatistics at Johns Hopkins University. I completed my Ph.D. at the Department of Biostatistics, Epidemiology and Informatics at Perelman School of Medicine at the University of Pennsylvania, where I was fortunate to be advised by Dr. Yong Chen. Previously, I received a B.S. with High Honors in Applied Mathematics from the University of California, San Diego in 2017.

Email / CV / Google Scholar / Twitter / Github

2023 The Observational Health Data Sciences and Informatics (OHDSI) Titan Award for Methodological Research
2023 Health Policy Statistics Section of American Statistical Association (ASA) Student Paper Award
2023 Best Student Poster Award of the 2023 Annual DBEI & CCEB Research Day
2022 American Statistical Association (ASA) Philadelphia Chapter Exceptional Achievement Award for Graduate Students
2022 Graduate Group in Epidemiology and Biostatistics Student Teaching Award
2021 Award for Outstanding Data Science Communication and Innovation at OptumLabs UnitedHealth Group.
2017 Department Honors in Mathematics (Applied) with High Distinction at University of California, San Diego.
2017 Honor society Phi Beta Kappa at University of California, San Diego.
2015-2017 Provost’s Honors at University of California, San Diego.

RESEARCH

With an overall theme of clinical evidence generation and evidence synthesis with real-world data (RWD), my research interests span:

Clinical evidence generation using data from distributed research networks
Surrogate-assisted semi-supervised learning
Systematic reviews and meta-analyses

I am also passionate about collaborative research in various fields, including opioid use disorder (OUD), dementia and other aging conditions, acute myocardial infarction, pediatric conditions, mental health disorder, long-COVID, hematology, vaccine effectiveness, health disparity and fairness, and health policy.

Selected Publications

• Clinical Evidence Generation Using Real-world Data

	A new end-to-end data aggregation approach for comparing hospital performance without sharing patient-level data Jiayi Tong, Jenna M. Reps, Chongliang Luo, Martijn J. Schuemie, Chao Yan, Patrick B. Ryan, Haitao Chu, Jiang Bian, Elizabeth A Shenkman, Yiwen Lu, Juan Manuel Ramirez-Anguita, Milou T. Brand, Zhaoyi Cheng, Scott L. DuVall, Thomas Falconer, Alex Mayer Fuentes, Kevin Hen, Jing Li, Michael E. Matheny, Miguel A. Mayer, Bhavnisha Patel, Di Wang, Ross D. Williams, Katherine Simone, Sarah Seager, James Yang, Yujia Zhou, Jeffrey S. Morris, Fei Wang, Elizabeth A. Stuart, Harlan M. Krumholz, Hua Xu, Rachel M. Werner, Marc A. Suchard, Thomas Lumley, Bradley A. Malin, David A. Asch, Yong Chen. (2023 JSM Student Award) Github page
	Real-world Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents Qiong Wu, Jiayi Tong (co-first author)**, Bingyu Zhang, Dazheng Zhang, Jie Xu, Yishan Shen, Lu Li, L. Charles Bailey, Jiang Bian, Dimitri A. Christakis, Megan L. Fitzgerald, Kathryn Hirabayashi, Ravi Jhaveri, Alka Khaitan, Tianchen Lyu, Suchitra Rao, Hanieh Razzaghi, Hayden T. Schwenk, Fei Wang, Margot I. Witvliet, Eric J. Tchetgen Tchetgen, Jeffrey S. Morris, Christopher B. Forrest, Yong Chen. Accepted by The Annals of Internal Medicine MedRxiv
	On the proportional likelihood ratio model for sparse data Jiayi Tong, Annie Qu, Raymond J. Carroll, Yang Ning, Yong Chen. Invited revision at The Annals of Applied Statistics, 2023
	Evaluating Site-of-Care-Related Racial Disparities in Kidney Graft Failure Using a Novel Federated Learning Framework Jiayi Tong, Yishan Shen, Alice Xu, Xing He, Chongliang Luo, Mackenzie Edmondson, Dazheng Zhang, Yiwen Lu, Chao Yan, Ruowang Li, Lianne Siegel, Lichao Sun, Elizabeth A Shenkman, Sally C. Morton, Bradley A. Malin, Jiang Bian, David A. Asch, Yong Chen. Invited revision at Journal of the American Medical Informatics Association (JAMIA), 2023
	Advancing Interpretable Regression Analysis for Binary Data: A Novel Distributed Algorithm Approach Jiayi Tong, Lu Li, Jenna Marie Reps, Vitaly Lorman, Naimin Jing, Mackenzie Edmondson, Xiwei Lou, Ravi Jhaveri, Kelly J. Kelleher, Nathan M. Pajor, Christopher B. Forrest, Jiang Bian, Haitao Chu, Yong Chen. Invited revision at Statistics in Medicine, 2023
	DisC2o-HD: Distributed Causal inference with covariates shift for analyzing real-world high-dimensional data *Jiayi Tong (co-first author)*, Jie Hu, George Hripcsak, Yang Ning, Yong Chen. Under review at the Journal of Machine Learning Research, 2023
	Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites Jiayi Tong, Chongliang Luo, Md Nazmul Islam, Natalie E. Sheils, John Buresh, Mackenzie Edmondson, Peter A. Merkel, Ebbing Lautenbach, Rui Duan and Yong Chen npj Digital Medicine, 2022 Paper / Github page
	Robust-ODAL: Learning from heterogeneous health systems without sharing patient-level data *Jiayi Tong (co-first author)*, Rui Duan, Ruowang Li, Martijn J. Scheuemie, Jason H. Moore, Yong Chen Pacific Symposium on Biocomputing (PSB) , 2020 Paper / Github page

• Surrogate-assisted semi-supervised learning

	An augmented estimation procedure for EHR-based association studies accounting for differential misclassification Jiayi Tong, Jing Huang, Jessica Chubak, Xuan Wang, Jason H Moore, Rebecca A Hubbard, Yong Chen Journal of the American Medical Informatics Association (JAMIA) , 2019 Paper / Github page
	A cost-effective chart review sampling design to account for phenotyping error in electronic health records (EHR) data Ziayan Yin, Jiayi Tong, Yong Chen, Rebecca A Hubbard, Cheng-Yong Tang Journal of the American Medical Informatics Association (JAMIA) , 2021 Paper
	An Augmented Estimation Procedure for EHR-based Association Studies with Multiple Surrogate Outcomes Yiwen Lu, Jiayi Tong (co-first author)*, Rebecca A Hubbard, Yong Chen Under review at Journal of the American Medical Informatics Association (JAMIA)* , 2023 Github page

• Systematic reviews and Meta-analyses

	Confidence Score: A Data-Driven Measure for Inclusive Systematic Reviews Considering Unpublished Preprints Jiayi Tong, Chongliang Luo, Yifei Sun, Rui Duan, M. Elle Saine, Lifeng Lin, Yifan Peng, Yiwen Lu, Anchita Batra, Anni Pan, Olivia Wang, Ruowang Li, Arielle Anglin, Yuchen Yang, Xu Zuo, Yulun Liu, Jiang Bian, Stephen E. Kimmel, Keith Hamilton, Adam Cuker, Rebecca A. Hubbard, Hua Xu, Yong Chen. Invited revision at Journal of the American Medical Informatics Association (JAMIA)
	Advancing timely and reliable evidence synthesis in the era of COVID-19: A novel method for including preprints in systematic reviews Jiayi Tong, Yifei Sun, Rebecca A. Hubbard, M. Elle Saine, Hua Xu, Xu Zuo, Lifeng Lin, Chunhua Weng, Christopher Schmid, Stephen E. Kimmel, Craig A. Umscheid, Adam Cuker, Yong Chen Under review at JAMA network open
	Meta-analysis of Reference Ranges Wei Liang, Jiayi Tong (co-first author)*, Haitao Chu, Nicolas Rodondi, Christine Baumgartner, Anne R. Cappola, Raymond J. Carroll, Yong Chen Under review at Biometrics*

• Scientific papers

	Quantifying and correcting bias due to outcome dependent self-reported weights in longitudinal study of weight loss interventions Jiayi Tong, Rui Duan, Ruowang Li, Chongliang Luo, Jason H. Moore, Jingsan Zhu, Gary D. Foster, Kevin G. Volpp, William S. Yancy, Jr., Pamela A. Shaw, Yong Chen. Scientific Reports, 2023
	Identifying Clinical Risk Factors for Opioid Use Disorder using a Distributed Algorithm to Combine Real-World Data from a Large Clinical Data Research Network Jiayi Tong, Zhaoyi Chen, Rui Duan, Wei-Hsuan Lo-Ciganic, Tianchen Lyu, Cui Tao, Peter A. Merkel, Henry R. Kranzler, Jiang Bian, Yong Chen American Medical Informatics Association (AMIA) Annual Symposium Proceedings, 2019 Paper / Github page
	Practice Environmenn Scale of the Nursing Work Index: A Descriptive Statistics Meta-Analysis Eileen T. Lake, Bingyu Zhang, Jiayi Tong, Gloria Mpundu, Kelsey N. Gross, Bingyu Zhang, Priscilla Cho, Yong Chen Invited Revision at International Journal of Nursing Studies, 2023
	Food insecurity and binge eating: A systematic review and meta‐analysis Jessica A. Abene, Jiayi Tong, Jeffrey Minuk, Gretchen Lindenfeldar, Yong Chen, and Ariana M. Chao. International Journal of Eating Disorders, 2023 Paper
	Adding caplacizumab to standard of care in thrombotic thrombocytopenic purpura: a systematic review and meta-analysis Mia Djulbegovic, Jiayi Tong, Alice Xu, Joanna Yang, Yong Chen, Adam Cuker, and Allyson M. Pishko Blood Advances, 2023 Paper
	Inherited thrombophilia and the risk of arterial ischemic stroke: a systematic review and meta‐analysis Thita Chiasakul, Elizabeth De Jesus, Jiayi Tong, Yong Chen, Mark Crowther, David Garcia, Chatree Chai‐Adisaksopha, Steven R. Messé, and Adam Cuker Journal of the American Heart Association, 2019 Paper
	The Use of Likelihood Ratio Test to Identify Rare Adverse Events with Year-varying Reporting Rates for FLU4 Vaccine in VAERS Jiayi Tong, Jing Huang, Jingcheng Du, Yi Cai, Cui Tao, Yong Chen American Medical Informatics Association (AMIA) Annual Symposium Proceedings, 2018 Paper

SOFTWARE

	PDA: Privacy-preserving Distributed Algorithms
	PDA-OTA: Privacy-preserving Distributed Algorithms Over The Air
	Xmeta: A Comprehensive Toolbox for Meta-analysis

TEACHING & SERVICES

	Teaching Assistant, "Clinical Evidence Generation using EHR data", JSM 2023 Teaching Assistant, "Practical Solutions for Working with EHR Data", JSM 2022 Session Chair, "Distributed Regressions in Real-World Data", JSM 2021
	Session Chair, "Advanced Methods for Pharmacoepidemiology", ENAR 2021
	Teaching Assistant, BSTA 754: Advanced Survival Analysis, Fall 2022 Teaching Assistant, BSTA 656: Longitudinal Data Analysis, Fall 2022 Teaching Assistant, BSTA 660: Design of Observational Studies, Fall 2021 Teaching Assistant, BSTA 661: Design Of Interventional Studies, Fall 2021
	Teaching Assistant, "Regression Methods: Concepts and Applications", Summer Institute in Statistical Genetics (SISG) 2022