# Mapping the sociotechnical ecosystem of precision medicine

> **NIH NIH R21** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $425,385

## Abstract

Large-scale investment in precision medicine incentivized by the 21st Century Cures Act, as well as other
rapidly growing data networks of networks such as ORIEN and APOLLO connect health systems, industry
partners, and researchers to the genomic, physiologic, diagnostic, treatment, research, and mobile health data
of millions of individuals. Precision medicine is a sociotechnical learning health system, defined by dynamic,
collaborative relationships between people, processes, policy and technology in complex environments. In
sociotechnical systems, both technology and social settings mutually co-construct one another, so while
technology is often a critical component of what constitutes a complex system in healthcare, just as important
are the social commitments to integrate standards and usage into practice. For example, academic medical
centers are adopting precision medicine methods and technologies and are making decisions based on
whether their goal is to increase capacity for quick and efficient clinical management, investigational trials, or
large-scale basic research. Local goals shape subsequent choices about what to sequence (whole genome,
targeted panels, or whole exome), how to sequence (library preparation methods, platform, manufacturer), and
logistics (speed, volume). These choices, in turn, have implications for people working in the field, the
cooperative processes they engage, the policies they follow, and downstream technological developments.
The cutting-edge science driving precision medicine requires infrastructure of learning health systems at
multiple scales (individual, clinic/lab, organization, and societal) to transform big data to knowledge (e.g.
BD2K), move new knowledge into practice and evaluate subsequent health outcomes.
Nearly 80% of precision medicine programs are focused on cancer, with 35% of precision medicine programs
being run at academic medical centers. The proposed research will capture this experience by examining the
sociotechnical ecosystem of learning in precision oncology programs at five academic medical centers at
public universities enabling a network of networks, cross-systems analysis to identify gaps that can be
addressed by policies or practices. The proposed project will map the sociotechnical of learning
ecosystem for precision oncology by identifying the actors (people, organizations), technologies, processes,
and policies that are operating across the learning cycle (data collection, analysis, knowledge generation,
outcome evaluation) and functioning at multiple scales (individual, group (clinic/lab), organizational, and
societal) in five precision health practice sites nationwide (Aim 1). We will then conduct an iterative design
process to develop a sociotechnical maturity model for precision oncology, adapting an informatics
approach to describing the progression and developmental milestones of systems to include the social aspects
that are often considered separate from the technical...

## Key facts

- **NIH application ID:** 9892643
- **Project number:** 1R21EB026290-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Jodyn Elizabeth Platt
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $425,385
- **Award type:** 1
- **Project period:** 2020-09-21 → 2023-09-20

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9892643

## Citation

> US National Institutes of Health, RePORTER application 9892643, Mapping the sociotechnical ecosystem of precision medicine (1R21EB026290-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9892643. Licensed CC0.

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