Demonstrating Trustworthiness to Patients in Data-Driven Health Care

被引:2
|
作者
Nong, Paige
机构
关键词
artificial intelligence; machine learning; health information technology; data; trust; bioethics; RACIAL BIAS; TRUST; RESPONSIBILITY; INFORMATION; SYSTEM;
D O I
10.1002/hast.1526
中图分类号
B82 [伦理学(道德学)];
学科分类号
摘要
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 essay explores these tensions and provides steps forward for health systems as they design advanced health information-technology (IT) policies and practices. It centers patients, their concerns, and the ways they perceive trustworthiness to reframe advanced health IT in service of patient interests.
引用
收藏
页码:S69 / S75
页数:7
相关论文
共 50 条
  • [21] Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record
    Dhingra, Lovedeep Singh
    Shen, Miles
    Mangla, Anjali
    Khera, Rohan
    AMERICAN JOURNAL OF CARDIOLOGY, 2023, 203 : 136 - 148
  • [22] A Data-Driven Paradigm for a Resilient and Sustainable Integrated Health Information Systems for Health Care Applications
    Epizitone, Ayogeboh
    Moyane, Smangele Pretty
    Agbehadji, Israel Edem
    JOURNAL OF MULTIDISCIPLINARY HEALTHCARE, 2023, 16 : 4015 - 4025
  • [23] Using data-driven approaches to improve delivery of animal health care interventions for public health
    Mazeri, Stella
    Bailey, Jordana L. Burdon
    Mayer, Dagmar
    Chikungwa, Patrick
    Chulu, Julius
    Grossman, Paul Orion
    Lohr, Frederic
    Gibson, Andrew D.
    Handel, Ian G.
    Bronsvoort, Barend M. deC
    Gamble, Luke
    Mellanby, Richard J.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2021, 118 (05)
  • [24] Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients
    Lauffenburger, Julie C.
    Mahesri, Mufaddal
    Choudhry, Niteesh K.
    JAMA NETWORK OPEN, 2020, 3 (10) : E2020291
  • [25] Patients' Perspectives on Trust and Trustworthiness of Health Care Organizations
    Greene, Jessica
    MILBANK QUARTERLY, 2022, 100 (02): : 365 - 369
  • [26] Data-driven change towards integrated care
    Bourgeois, Jolyce
    De Ridder, Lotje
    Van den Bogaert, Saskia
    Van der Brempt, Isabelle
    De Ridder, Ri
    INTERNATIONAL JOURNAL OF INTEGRATED CARE, 2018, 18
  • [27] Clinical Analytics for Data-Driven Models of Care
    Nickitas, Donna M.
    NURSING ECONOMICS, 2014, 32 (03): : 106 - +
  • [28] A data-driven method of health monitoring for spacecraft
    Kang, Xu
    Pi, Dechang
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2018, 90 (02): : 435 - 451
  • [29] Derivation of data-driven triggers for palliative care consultation in critically ill patients
    Hua, May S.
    Ma, Xiaoyue
    Li, Guohua
    Wunsch, Hannah
    JOURNAL OF CRITICAL CARE, 2018, 46 : 79 - 83
  • [30] A data-driven health index for neonatal morbidities
    De Francesco, Davide
    Blumenfeld, Yair J.
    Maric, Ivana
    Mayo, Jonathan A.
    Chang, Alan L.
    Fallahzadeh, Ramin
    Phongpreecha, Thanaphong
    Butwick, Alex J.
    Xenochristou, Maria
    Phibbs, Ciaran S.
    Bidoki, Neda H.
    Becker, Martin
    Culos, Anthony
    Espinosa, Camilo
    Liu, Qun
    Sylvester, Karl G.
    Gaudilliere, Brice
    Angst, Martin S.
    Stevenson, David K.
    Shaw, Gary M.
    Aghaeepour, Nima
    ISCIENCE, 2022, 25 (04)