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Big data and reference intervals: rationale, current practices, harmonization and standardization prerequisites and
Luisa Martinez-Sanchez1,2,3, Fernando Marques-Garcia4, Yesim Ozarda5
1Clinical Biochemistry Department, Vall d'Hebron University Hospital, Barcelona, Spain.
Advances in Laboratory Medicine
|June 26, 2023
Summary
This review explores big data
Area of Science:
- Clinical Chemistry
- Biostatistics
- Health Informatics
Background:
- Reference intervals are crucial for clinical decision-making.
- Current methods for establishing reference intervals are evolving.
- The integration of big data presents new opportunities and challenges.
Purpose of the Study:
- To provide an overview of big data's role in determining reference intervals.
- To discuss current practices, statistical methods, and data quality prerequisites.
- To explore future perspectives for indirect determination using routine laboratory data.
Main Methods:
- Literature review of "big data" applications in reference interval determination.
- Analysis of statistical methods for indirect estimation.
- Discussion of data quality requirements, including harmonization and standardization.
Main Results:
- Big data offers potential for more robust and dynamic reference intervals.
- Data quality, harmonization, and standardization are critical for reliable results.
- Indirect determination using routine data is a promising future direction.
Conclusions:
- Big data approaches can enhance the utility of reference intervals.
- Addressing data quality is paramount for successful implementation.
- Future research should focus on validating indirect methods for broader application.
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