Exploration of Integrated NATA – RCPAQAP Predictive Modelling to Improve Pathology Quality

This page provides information related to the project

Page last updated: 07 October 2020

This project identified relationships between distinct sets of performance data with the aim of developing a model (machine learning algorithm) to assist in the detection of poor performing pathology laboratories and generate decision-guiding rules to reduce inappropriate testing and to improve overall performance based on previous laboratory performance data.

Exploration of Integrated NATA – RCPAQAP Predictive Modelling to Improve Pathology Quality (PDF 1425 KB)
Exploration of Integrated NATA – RCPAQAP Predictive Modelling to Improve Pathology Quality (Word 32639 KB)