Intuitive web tools for reference interval estimation: goCrunch and ReferenceRangeR

Abstract Objectives Verification of reference intervals (RIs) is mandatory for clinical laboratories. In this context indirect methods of RI estimation may be of assistance, yet these are often limited to experts with programming or statistical skills due to the lack of standardized solutions in laboratory information systems. Methods This study evaluates two web-based platforms, goCrunch and ReferenceRangeR, developed to simplify RI estimation with indirect methods for laboratory professionals without requiring expertise in R or other statistical software. RIs estimated from real-world platelet and anion gap datasets were compared across the platforms. Results The platforms were assessed regarding data handling, statistical methods, visualization, and quality assurance. goCrunch supports both classical (Hoffmann, Bhattacharya) and modern methods (refineR, reflimR), with options for filtering, transformation, verification, and graphical outputs. ReferenceRangeR focuses on newer methods (refineR, TML, TMC, kosmic, reflimR) and includes additional features such as stratification by age and sex, age-drift detection, and RI comparison against external values. The comparison of a simple analyte (platelet count) and a complex one (anion gap) highlighted the strengths and limitations of each platform. Conclusions Both tools enable efficient RI generation and verification with minimal user intervention. While goCrunch is particularly suitable for routine applications and educational purposes, ReferenceRangeR provides enhanced analytical and comparative functionalities, thereby both tools support laboratories in meeting accreditation requirements.