# Hospitals Sharing Patient Data and Biospecimens with Commercial Entities: Evidence-Based Translation to Improved Practice

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $466,507

## Abstract

PROJECT SUMMARY ABSTRACT
Background: Widely sharing patient data and biospecimens can enable life-saving advances in
translational science. Hospitals and commercial entities focusing on precision medicine and
other genetic and artificial intelligence technologies have increasingly partnered to share these
data resources. To ensure equitable access to scientific advances, datasets must include
patients reflecting the demographic distribution of disease. However, our previous research
demonstrates that many patients are uncomfortable with hospitals sharing their data with
industry and that individuals who identify as Black or Hispanic are consistently more likely to
report discomfort. We need to measure diverse patient responses to actual hospital data-
sharing practices with the power to differentiate preferences across race, ethnicity, and other
relevant scales to identify promising areas for compromise with an equitable impact. Approach:
The goal of this proposal is to identify areas for compromise between patients and hospitals to
improve data-sharing practices with industry in ways that are respectful of individual patient
autonomy and equitable in impact across diverse communities. Research Aims: To achieve
this goal, our project has three specific aims: (1) Explore hospital data-sharing policies and
practices with commercial entities, and their industry and patient relationships, (2) Characterize
the kinds of hospitals that have been approached by, are interested in, and/or have shared
patient data with industry and measure the kinds of patient impact that might drive change to
specific data-sharing practices, and (3) Examine the acceptability of hospital data-sharing
practices, preferences amongst acceptable practices, and anticipated impact of unacceptable
practices generally as well as by race and ethnicity specifically. Impact: Patient discomfort with
hospital data sharing practices that patients find unacceptable – and its association with race
and ethnicity – is a significant problem for increasing the accessibility and generalizability of
translational science advances. Though our mixed methods ELSI approach to discovering areas
for compromise between hospitals and patients, while centering those historically excluded, this
proposal will have a major impact on improving data-sharing practices to facilitate diversity in
data used to support high-impact translational science.

## Key facts

- **NIH application ID:** 10501505
- **Project number:** 1R01TR004244-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Kayte Kelleher Spector-Bagdady
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $466,507
- **Award type:** 1
- **Project period:** 2022-08-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10501505

## Citation

> US National Institutes of Health, RePORTER application 10501505, Hospitals Sharing Patient Data and Biospecimens with Commercial Entities: Evidence-Based Translation to Improved Practice (1R01TR004244-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10501505. Licensed CC0.

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