# Critical Care Informatics: Ethical considerations around the use and sharing of health-related data

> **NIH NIH R01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2020 · $97,102

## Abstract

Project Summary
Significance: Health care systems around the world are increasingly utilizing the large
amount of routinely collected digital health data for biomedical research. Critical care
medicine is a data-rich environment and has been at the forefront of these efforts to utilize
data science to improve health care. Although such activities are urgently needed,
opportunities in health care data science are often not realized and questions persist
about how it can be ethically implemented.
Innovation: High-income countries have so far dominated the discussion over data
science and AI. However, in an era of increasing global collaborative health research
efforts, this imbalance is problematic and there is a need to better understand the attitudes
and unique challenges LMICs have in relation to health care data science and AI. This
project will make an important contribution toward this in critical care medicine.
Furthermore, although there has been a rush to consider how AI applications can be
developed and implemented in an ethical manner, most of the existing ethical guidance
consists of a range of high-level ethical principles that are often not health care specific
and published mainly by organizations in high-income countries. To ensure the ethical
implementation of data science and AI in critical care, there is a need to understand the
value stakeholders’ place in data science and AI, their awareness and use of existing
ethical guidance for AI, the their needs around receiving practical ethical guidance.
Approach: Using the interdisciplinary approach of empirical bioethics, this project will seek
to examine how the ethical implementation of data science in critical care for biomedical
research can be best achieved. It will first conduct an online survey with critical care
centers and relevant professional societies from a sample of high-income countries and
from a sample of LMICs, to inform and contextualize the ethical analysis. Using the
analytic method of wide reflective equilibrium, it will then develop normative conclusions
regarding how the implementation of data science in critical care for biomedical research
can be improved. A road map for the ethical implementation of data science in critical
care for biomedical research will be developed, and then discussed and refined at a
workshop held at MIT.

## Key facts

- **NIH application ID:** 10130860
- **Project number:** 3R01EB017205-06S1
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Leo Anthony G Celi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $97,102
- **Award type:** 3
- **Project period:** 2014-08-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10130860

## Citation

> US National Institutes of Health, RePORTER application 10130860, Critical Care Informatics: Ethical considerations around the use and sharing of health-related data (3R01EB017205-06S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10130860. Licensed CC0.

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