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Harry Reyes Nieva, MAS, MA

Visiting Research Fellow

Brigham and Women's Hospital
Harvard Medical School

Harry Reyes Nieva, MAS, MA

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  • Harry Reyes Nieva is a visiting postgraduate research fellow at Harvard Medical School and PhD student in the Department of Biomedical Informatics at Columbia University, advised by Noémie Elhadad. His research focuses on leveraging machine learning and natural language processing to improve the equity, quality, and safety of health care and support precision medicine. He is especially passionate about using and expanding the vast toolbox that statistical and computational learning offers to better understand, improve, and facilitate study of the health of underserved communities. His PhD is funded by the National Library of Medicine through a Biomedical Informatics and Data Science Research training grant (T15LM007079-28). He is also the recipient of a Computational and Data Science Fellowship from the Association for Computing Machinery (ACM) Special Interest Group in High Performance Computing (SIGHPC).

    Prior to pursuing a career in health services research, Mr. Reyes Nieva was a member of the Strategic Information division of the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) at Harvard University which aimed to rapidly expand antiretroviral therapy (ART) treatment and care programs for people living with HIV/AIDS in sub-Saharan Africa. As Data Quality Assurance Manager for the Nigeria country program, his focus was scale-up and transition of data quality improvement and assurance activities nationwide. In this capacity, he worked closely with in-country quality improvement, monitoring and evaluation, and clinical specialists while developing or modifying pediatric and adult quality improvement dashboards and monitoring and evaluation tools for more than 90,000 patients. His division also produced monitoring and evaluation reports for the U.S. Health Resources and Services Administration (HRSA), U.S. Centers for Disease Control and Prevention (CDC), and United Nations General Assembly Special Session (UNGASS) on HIV/AIDS.

    Harry Reyes Nieva graduated from Yale University with a Bachelor of Arts in Sociology and History, studied Population and International Health at the Harvard T.H. Chan School of Public Health, received a Master of Applied Science in Spatial Analysis from the Johns Hopkins Bloomberg School of Public Health, and a Master of Arts in Biomedical Informatics from Columbia University.

Selected Publications

  • What Works in Medication Reconciliation: An On-Treatment and Site Analysis of the MARQUIS2 Study
  • The Timeliness of Point of Care Viral Load Results Improves HIV Monitoring in Nigeria.
  • An Electronic Pillbox Intervention Designed to Improve Medication Safety During Care Transitions: Challenges and Lessons Learned regarding Implementation and Evaluation.
  • A Scoping Review of Ethics Considerations in Clinical Natural Language Processing
  • Characteristics of Disease-Specific and Generic Diagnostic Pitfalls: A Qualitative Study
  • Exploring tai chi exercise and mind-body breathing in patients with COPD in a randomized controlled feasibility trial.Kraemer KM, Litrownik D, Moy ML, Wayne PM, Beach D, Klings ES, Reyes Nieva H, Pinheiro A, Davis RB, Yeh GY.
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Latest News

  • ACM SIGHPC Computational and Data Science Fellowships 2021 Winners Announced
  • Machine Learning and Health Equity | ThinkResearch Podcast
  • On the Margins | Harvard Medicine Magazine
  • Zhou, Reyes Nieva Awarded Harvard Catalyst Health Disparities Research Program Grant
  • Braverman, Palm, Reyes Nieva Receive Inaugural LGBT Leadership Awards
  • Brigham and Women’s Hospital Has Started Collecting Gender and Sexuality Information from Patients
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Selected Presentations

  • Large-scale Characterization of Gender Differences in Age at Diagnosis and Time to Diagnosis in Longitudinal Observational Health Data
  • Analyzing shifts in healthcare-seeking behavior among All of Us enrollees in the era of COVID-19
  • Mining the Health Disparities and Minority Health Bibliome: A Computational Scoping Review.
  • Differential Presentation and Delays in Treatment for Acute Myocardial Infarction Associated with Sex and Race/Ethnicity.
  • Examining Gender Differences in Time to Diagnosis through Fairness and Time-Variant Evaluation of EHR Data
  • Exploring Gender Disparities in Time to Diagnosis
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