JMIR Publications

ABSTRACT

Background:

Reference intervals for patient test results are in standard use across many medical disciplines, allowing physicians to identify measurements indicating potentially pathological states with relative ease. The process of inferring cohort-specific reference intervals is, however, often ignored due to the high costs and cumbersome effort associated with it. Sophisticated analysis tools are needed to automatically infer relevant and locally specific RIs directly from laboratory routine data. This would effectively connect clinical laboratory databases to physicians and provide personalized target ranges for the respective cohort population.v

Objective:

We describe the BioRef infrastructure, a multicentric governance and IT framework for the estimation and assessment of patient group-specific reference intervals from clinical laboratory routine data by the use of an innovative decentralized data sharing approach and a sophisticated, clinically-oriented data analysis graphical user interface.

Methods:

A common governance agreement and interoperability standards have been established, allowing harmonization of multidimensional laboratory measurements from multiple clinical databases into a unified “Big Data” ressource. International coding systems such as the International Classification of Diseases (ICD-10), unique identifiers for medical devices from the Global Unique Device Identification Database (GUDID), type identifiers from the Global Medical Device Nomenclature (GMDN) and a universal transfer logic such as the Resource Description Framework (RDF) are used to align the routine laboratory data of each data provider for use within the BioRef framework. With a decentralized data sharing approach, the BioRef data can be evaluated by end-users from each cohort site following a strict “no copy, no move” principle, i.e., only data aggregates for the intercohort analysis of target ranges are exchanged.

Results:

The TI4Health distributed and secure analytics system is used to implement the proposed federated and privacy-preserving approach and comply with the limitations applying to sensitive patient data. Under the BioRef interoperability consensus, clinical partners enable the computation of reference intervals via the TI4Health query graphical user interface without exposing the underlying raw data. The interface is developed to be used for physicians and clinical laboratory specialists alike and allows intuitive and interactive data stratification by patient factors (age, administrative gender and personal medical history) as well as laboratory analysis determinants (device, analyzer and test kit identifier). The consolidated effort enables creating extremely detailed and patient group-specific queries, allowing the generation of individualized, covariate-adjusted reference intervals on-the-fly.

Conclusions:

With the BioRef – TI4Health infrastructure a framework for clinical physicians and researchers to define precise reference intervals immediately in a convenient, privacy-preserving, and reproducible manner has been implemented promoting a vital part of practicing precision medicine while streamlining compliance and avoiding transfers of raw patient data. This new approach can provide a crucial update on reference intervals and improve patient care for personalized medicine. Clinical Trial: None required