Development and pilot testing of measurement tool for diagnosis of lung cancer

Start Date Jan 2020

Code W3-Aff

Status Ongoing

Senior Lead
Prof Fiona Walter (Cambridge), Prof Richard Neal (Leeds), Liz Sarma (NCI), Dr Lesleigh Kowalski Frank, Larry Kessler, Kari Stephens, Meliha Yetisgen, Morhaf Al Achkar (all Washington)

Project summary

This project aims to develop and test a clinical quality measure for lung cancer diagnosis using electronic medical record (EMR) data from a large integrated health care system. The quality measure will incorporate three metrics to lung cancer diagnosis. 1) Time intervals within the diagnostic pathway, including patient interval (from first recognizing a bodily change to presenting), and the diagnostic interval (from first clinical assessment of symptoms and signs, via performing laboratory tests and imaging tests for presumptive diagnosis, to definitive histological diagnosis); 2) measurement of patient centered outcomes of testing, and 3) appropriateness of the testing process.

This work is funded by the Gordon and Betty Moore Foundation, and involves collaborations with several CanTest researchers including University of Cambridge, University of Leeds and the University of Washington.  


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