Paige Nong

Datos Biográficos

ID373005
NOMBREPaige Nong
NOMBRESPaige
APELLIDONong
FIRMANONG P
AFILIACIONESUniversity of Michigan
ORCID0000-0002-2849-9005
VERIFICADOSí
TOTAL DE OBRAS8
TOTAL DE CITAS1
TOTAL COMO AUTOR8
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2020
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H1

  • Unintended Consequences of Using Ambient Artificial Intelligence Scribes for Billing

    Open AccessPaige Nong, Hannah NeprashARTICLEJAMA Health Forum2026

    This Viewpoint describes potential risks of using generative AI–driven ambient scribes to automate more intensive billing

  • Demonstrating Trustworthiness to Patients in Data‐Driven Health Care

    Open AccessPaige NongARTICLEThe Hastings Center Report2023

    Patient data is used to drive an ecosystem of advanced digital tools in health care, like predictive models or artificial intelligence‐based decision support. Patients themselves, however, receive little information about these technologies or how they affect their care. This raises important questions about patient trust and continued engagement in a health care system that extracts their data but does not treat them as key stakeholders. This es…

  • An Ecosystem Approach to Earning and Sustaining Trust in Health Care—Too Big to Care

    Open AccessJ Platt, Paige NongARTICLEJAMA Health Forum2023

    This Viewpoint describes the decline in trust in medical institutions in the US and suggests approches to rebuilding and maintaining trust

  • Clinical algorithms, racism, and "fairness" in healthcare

    Open AccessSarah El-Azab, Paige NongARTICLEBig Data & Society2023Referencias: 95

    To date, attempts to address racially discriminatory clinical algorithms have largely focused on fairness and the development of models that "do no harm." While the push for fairness is rooted in a desire to avoid or ameliorate health disparities, it generally neglects the role of racism in shaping health outcomes and does little to repair harm to patients. These limitations necessitate reconceptualizing how clinical algorithms should be designed…

  • Discrimination, trust, and withholding information from providers

    Open AccessPaige Nong, Alicia Williamson et al.ARTICLESSM - Population Health2022

    Quality care requires collaborative communication, information exchange, and decision-making between patients and providers. Complete and accurate data about patients and from patients are especially important as high volumes of data are used to build clinical decision support tools and inform precision medicine initiatives. However, systematically missing data can bias these tools and threaten their effectiveness. Data completeness relies in man…

  • Learning about Covid-19

    Open AccessPhilip S Amara, J Platt et al.ARTICLEBMC Public Health2022

    Policy makers can enhance willingness to participate in public health efforts such as contact tracing during infectious disease outbreaks by helping the public appreciate the seriousness of the public health threat and communicating trustworthy information through accessible channels

  • Understanding racial differences in attitudes about public health efforts during Covid-19 using an explanatory mixed methods design

    Open AccessPaige Nong, Mrinalini Raj et al.ARTICLESocial Science & Medicine2021Citada por: 1Referencias: 34

  • Patient-Reported Experiences of Discrimination in the US Health Care System

    Open AccessPaige Nong, Mrinalini Raj et al.ARTICLEJAMA Network Open2020

    Importance: Although considerable evidence exists on the association between negative health outcomes and daily experiences of discrimination, less is known about such experiences in the health care system at the national level. It is critically necessary to measure and address discrimination in the health care system to mitigate harm to patients and as part of the larger ongoing project of responding to health inequities. Objectives: To (1) iden…