Randox Launches Data Management ‘Advisor’ to Optimize Lab Quality Control

Global clinical diagnostics firm Randox Laboratories has launched a new ‘Advisor’ application to complement its interlaboratory data management software Acusera 24•7 Live Online.

Acusera Advisor is an optional tool designed to help laboratories select an optimum QC strategy for each individual test in use. It will recommend and automatically apply QC multi-rules per parameter, as well as advising how frequently a laboratory should run IQC.

By automatically recommending optimized QC multi-rules, this lowers the Probability for False Rejection (Pfr) whilst maintaining high Probability for Error Detection (Ped). It helps labs reduce time spent troubleshooting anomalies, helping avoid unnecessary and costly QC repeats without affecting error detection.

Based on the performance limits selected by the customer Acusera Advisor will calculate the laboratory’s allowable imprecision (%CV) and allowable inaccuracy (%bias). These figures are then plotted on an Operating Specifications Chat (OPSpecs Chart) against the line equations for each strategy and from this the optimal QC multi-rules and frequency are selected.

The QC multi-rules and frequency are recommended based on the level of quality that the laboratory wishes to achieve. Before any recommendations can be made for any particular method, users must enter a minimum of 20 results for at least two levels of controls and set user defined performance limits.

A web-based system, Acusera 24•7 offers an easy-to-use and intuitive interface, direct connectivity to the laboratory’s LIS and the ability to produce fully interactive charts and comprehensive reports to meet individual laboratory requirements. Peer group data is updated every 24 hours, giving laboratories access to the most up to date information available. Statistics for Acusera 24•7 are generated from a peer data group of over 28,000 laboratory participants, the largest available in the market. This ensures a large database of results and analytical methods, therefore increasing statistical validity.