• NIH Sep 2, 2020 | R21

    Creating an initial ethics framework for biomedical data modeling by mapping and exploring key decision points

    Principal Investigator(s): KORNGIEBEL, DIANE M;

    Institution: HASTINGS CENTER, INC.

    FOA Number: PA-19-053

    Abstract

    Project Narrative This study would be the first to develop an initial bioethics framework to meet a critical gap in biomedical data modeling activities, where the downstream consequences of developing data models without careful and comprehensive review of ethical issues can be severe?not least because poorly developed data models have the potential to impact adversely the health of individuals, groups, and communities. Currently, there is limited conversation around potential bioethics issues in data modeling, and as yet no implementable guidance on how biomedical data science modeling research activities should occur. The initial ethics framework developed by this study would provide a roadmap to ensure that data modeling decision points are documented and their ethical ramifications considered at the outset of model creation, thus supporting core scientific values of inclusivity, accountability, reproducibility, and transparency that, in turn, foster trust in biomedical data modeling output and potential applications, whether local, national, or global.

    FUNDING AGENCY:

    Funder:
    NIH

    Institute:
    NATIONAL HUMAN GENOME RESEARCH INSTITUTE

    Funding Type:
    R21

    Project Number:
    R21HG011277

    Start Date:
    Sep 2, 2020

    End Date:
    Aug 31, 2022

    PROJECT TERMS:

    Accountability, Address, Area, Artificial intelligence, base, Big Data, Bioethical Issues, Bioethics, Bioethics Consultants, biomedical data science, Caring, Clinical, clinical decision support, clinical decision-making, Communities, Data, data modeling, data quality, Data science, Data Scientist, Data Sources, data tools, Decision Making, Development, Electronic Health Record, Ensure, Ethical Issues, ethical legal social implication, ethical review, Ethics, Focus Groups, Fostering, General Population, genomic data, Health, Health Resources, Health system, high standard, improved, Individual, individual patient, informant, Informatics, interest, interoperability, Interview, Machine Learning, Maps, meetings, Methods, Mobile Health Application, model development, Modeling, National Health Policy, Natural Language Processing, Nature, Output, patient population, Patients, Persons, Play, population health, Predictive Analytics, Process, programs, public trust, Qualitative Research, Reproducibility, Research, Research Activity, Research Methodology, Research Personnel, Resource Allocation, Role, Services, Social Environment, Strategic Planning, Structure, System, Time, tool, trend, Trust, United States National Institutes of Health, usability, Walking

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