Meghan Reading Turchioe, PhD, MPH, RN

Assistant Professor of Nursing

Overview

Meghan Reading Turchioe’s program of research focuses on developing and implementing digital health technologies including mobile applications, wearable devices, telehealth, and artificial intelligence (AI). A major focus of her work involves leveraging methods from data visualization, human-computer interaction, and implementation science to return health data and support decision-making among patients, nurses, and other clinicians. With a focus on developing equitable solutions, her research is motivated by her experience as a cardiac nurse caring for a diverse patient population with multiple chronic conditions in New York City. Turchioe’s research is supported by multiple grants from NIH and industry.

Turchioe serves on several committees through the American Heart Association (AHA) and American Medical Informatics Association (AMIA), including the AHA National Atrial Fibrillation Systems of Care Advisory Group Commission and the Editorial Board of the Journal of the American Medical Informatics Association. Turchioe also serves on the National Quality Forum Artificial Intelligence in Quality Measures Technical Expert Panel.

Academic Appointments

Assistant Professor of Nursing

Gender

Female

Credentials & Experience

Education & Training

BSN, 2012 Boston College Connell School of Nursing, Chestnut Hill, MA
MPH, 2015 George Washington University Milken Institute of Public Health, Washington, DC
PhD, 2018 Columbia University School of Nursing, New York, NY
Fellowship: 2020 Weill Cornell Medicine, New York, NY

Honors & Awards

Finalist, American Heart Association (AHA) Martha N. Hill Early Career Investigator Award	11/2022
Early Career Alumni Award: Emerging Nurse Leader, Columbia University School of Nursing	05/2022
Alliance for Nursing Informatics (ANI) emerging leader*	01/2022 – 12/2024
Honorarium, Weill Cornell Medicine Primary Care Innovations Symposium (top abstract)	02/2020
Research Travel Grant, AHA Council on Cardiovascular and Stroke Nursing (CVSN) (top abstract)	11/2019
Dissertation Research Award, Columbia University School of Nursing	06/2019
Jonas Nurse Leader Scholar, Jonas Center for Nursing and Veterans Healthcare	09/2016 – 06/2018

Research

Grants

Title: “Generative Artificial Intelligence for Nurses” (GAIN) Source: 2023 Office of the Provost Teaching and Learning Grants *Role: Principal Investigator	07/01/2023 – 6/30/2024
Title: “Usability evaluation of a HeartLogic mobile application prototype” Source: Boston Scientific Corporation Research Grant *Role: Principal Investigator	07/01/2023 – 06/30/2024
Title: “Data-driven shared decision-making to reduce symptom burden in atrial fibrillation” (R00NR019124) Source: NIH/NINR *Role: Principal Investigator	08/01/2022 – 07/31/2025
Title: “Atrial fibrillation among Black and Latinx heart failure patients: understanding clinical presentation and factors to promote technology-based surveillance” Source: COMMUNITY (NIMHD P50MD017341) Investigator Development Core pilot grant/Health Equity Scholars Program *Role: Principal Investigator	09/01/2022 – 08/31/2024
Title: “Improve the Meaning of Patient Reported Outcomes to eValuate Effectiveness for Cardiac Care (IMPROVE-Cardiac Care)” (R01HL161458) Source: NIH/NHLBI Role: Co-investigator PI: Masterson Creber	7/01/2022 – 06/30/2027
Title: “Bioethical Considerations for Building, Evaluating, and Implementing Artificial Intelligence in Perinatal Mood and Anxiety Disorders,” (R41MH124581-02S1-Administrative Supplement) Source: NIH/NIMH Role: Co-investigator PI: Pathak	07/28/2022 – 06/30/2023
Title: “Risk modeling and shared decision making for postpartum depression” (R41MH124581) Source: NIH/NIMH Role: Co-investigator PI: Pathak/ Laskoff	07/21/2021 – 06/30/2023
Title: “Using Mobile Integrated Health and Telehealth to Support Transitions of Care among Heart Failure Patients” (IHS-2019C2-17373) Source: Patient Centered Outcomes Research Institute (PCORI) Role: Co-investigator PI: Masterson Creber	05/01/2020 – 12/31/2024

Selected Publications

*Denotes co-first authorship, **Denotes senior authorship.

Reading Turchioe M, Hermann A, Benda N. (2024). Recentering responsible and explainable artificial intelligence research on patients: implications in perinatal psychiatry. Frontiers in Psychiatry, 14. https://doi.org/10.3389/fpsyt.2023.1321265
Reading Turchioe M, Slotwiner D. (2023). Screening for Atrial Fibrillation using Digital Health: Moving from Promises to Reality. JACC: Advances, 2(8), 100621. https://doi.org/10.1016/j.jacadv.2023.100621
Desai PM, Harkins S, Rahman S, Kumar S, Hermann A, Joly R, Zhang Y, Pathak J, Kim J, D’Angelo D, Benda NC*, Reading Turchioe M**. (2023). Visualizing Machine Learning-Based Predictions of Postpartum Depression Risk for Lay Audiences. Journal of the American Medical Informatics Association. doi: 10.1093/jamia/ocad198. [Epub ahead of print] PubMed PMID: 37847667.
Reading Turchioe M, Harkins S, Desai P, Kumar S, Kim J, Hermann A, Joly R, Zhang Y, Pathak J, Benda NC. (2023). Women’s perspectives on the use of artificial intelligence (AI)-based technologies in mental healthcare. JAMIA Open. ooad048. doi: 10.1093/jamiaopen/ooad048. PMID: 37425486; PMCID: PMC10329494.
Hobensack M, Zhao Y, Scharp D, Volodarskiy A, Slotwiner D, Reading Turchioe M.** (2023). Characterising symptom clusters in patients with atrial fibrillation undergoing catheter ablation. Open Heart. e002385. doi: 10.1136/openhrt-2023-002385. PMID: 37541744; PMCID: PMC10407417.
Reading Turchioe M, Soliman EZ, Goyal P, Merkler A, Kamel H, Cushman M, Soroka O, Masterson Creber R, Safford M. (2022). Atrial fibrillation and stroke symptoms in the REasons for Geographic and Racial differences in Stroke (REGARDS) study. Journal of the American Heart Association (JAHA); 11(2):e022921. doi: 10.1161/JAHA.121.022921. PMID: 35023350
Reading Turchioe M, Volodarskiy A, Pathak J, Wright D, Tcheng J, Slotwiner D. (2021). State of the science of natural language processing in cardiology: A systematic review. Heart. doi: 10.1136/heartjnl-2021-319769. PMID: 34711662.
Reading Turchioe M, Grossman LV, Baik D, Lee CS, Maurer MS, Goyal P, Masterson Creber RM. (2020). Older adults can successfully monitor symptoms using an inclusively designed mobile application. Journal of the American Geriatrics Society. doi: 10.1111/jgs.16403. PMCID: PMC7323569.
Reading Turchioe M*, Grossman LV*, Myers A, Baik D, Goyal P, Creber RM. (2020). Visual Analogies, Not Graphs, Increase Patients' Comprehension of Changes in their Health Status. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocz217. PMCID: PMC7309237.
Reading M, Merrill J. (2018). Converging and Diverging Needs between Patients and Providers who are Collecting and Using Patient-Generated Health Data: An Integrative Review. Journal of the American Medical Informatics Association; 25(6): 759–771. https://doi.org/10.1093/jamia/ocy006. PMCID: PMC5978018.

BOOK CHAPTERS

Reading Turchioe M, Lai AM, Siek KA. (in press). “Designing and Deploying Mobile Health Interventions.” In V.L. Patel, T.G. Kannampallil (Eds.), Cognitive Informatics in Health and Biomedicine: Human-Computer Interaction in Healthcare – The Role of Cognition. Springer.
Ancker JS, Reading Turchioe M. (2023). “The Promise of Patient Decision Support.” In R. Greenes (Ed.), Clinical Decision Support and Beyond. Progress and Opportunities in Knowledge-Enhanced Health and Health Care. Elsevier.
Reading Turchioe M, Masterson Creber R. (2022). “User-centered development and evaluation of patient-facing visualizations of health information.” In P.S. Hsueh, T. Wetter, X. Zhu (Eds.), Personal Health Informatics: Patient Participation in Precision Health. Springer.
Masterson Creber R, Reading Turchioe M. (2021). “Patient-facing data: challenges & opportunities.” In S. Mittal, D.J. Slotwiner (Eds.), Cardiac Electrophysiology Clinicals. Elsevier. 555-567. doi: 10.1016/j.ccep.2021.05.002. PMCID: PMC8328196.

For a complete list of publications, please visit MyNCBI.