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Establishment of a Clinic-based Biorepository

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The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference

Tobias Ueli Blatter^1,2, Harald Witte¹, Jules Fasquelle-Lopez³

¹University Institute of Clinical Chemistry, University Hospital Bern, Bern, Switzerland.

Journal of Medical Internet Research

|October 18, 2023

Summary

This study introduces the BioRef infrastructure, enabling precise, patient-specific reference intervals (RIs) from routine lab data. This privacy-preserving framework enhances precision medicine and patient care.

Keywords:

confidential data data security differential privacy laboratory medicine personalized health precision medicine reference interval research infrastructure sensitive data

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Area of Science:

Clinical Laboratory Science
Bioinformatics
Precision Medicine

Background:

Reference intervals (RIs) are crucial for identifying pathological states in patient test results.
Inferring cohort-specific RIs is often hindered by high costs and complex efforts.
Sophisticated tools are needed to automatically derive local RIs from routine laboratory data.

Purpose of the Study:

To describe the BioRef infrastructure, a multicentric IT framework for estimating patient group-specific RIs.
To detail a decentralized data-sharing approach and a clinically oriented graphical user interface (GUI) for data analysis.
To enable the assessment of RIs directly from routine clinical laboratory data.

Main Methods:

Established common governance and interoperability standards for harmonizing multidimensional lab data into a unified resource.
Utilized international coding systems (ICD-10, GUDID, GMDN) and Resource Description Framework (RDF) for data alignment.
Implemented a decentralized data-sharing approach ('no copy, no move') for privacy-preserving, federated analysis using the TI4Health system.

Main Results:

The BioRef-TI4Health infrastructure enables privacy-preserving computation of RIs via a GUI without exposing raw data.
The GUI allows intuitive data stratification by patient factors (age, sex, medical history) and lab determinants (device, analyzer, test kit).
Generated individualized, covariate-adjusted RIs on the fly, facilitating detailed, patient group-specific queries.

Conclusions:

The BioRef-TI4Health infrastructure provides a framework for defining precise, privacy-preserving, and reproducible RIs.
This promotes precision medicine by streamlining compliance and avoiding raw patient data transfers.
The approach offers a crucial update on RIs, improving patient care for personalized medicine.