Clinical Decision Support for Calculating Patient Cancer Risk
Principal Investigator
Name
James Morrison
Degrees
MD
Institution
University of Maryland
Position Title
Radiology Fellow
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-60
Initial CDAS Request Approval
Jan 29, 2014
Title
Clinical Decision Support for Calculating Patient Cancer Risk
Summary
The PLCO dataset contains patient specific information matched to long-term morbidity and mortality outcomes. The size and scope of the study is well suited for patient risk factor data mining. We propose to develop a case-based clinical decision support tool which matches user defined patient demographics to sub-cohorts of the PLCO dataset. Statistical analysis of the sub-cohorts will then be used to determine personalized pre-test probability of disease and screening recommendations. Real-time data mining of high quality clinical research dataset such as the PLCO study has the potential to guide evidence-based clinical decision-making through appropriate screening patient selection.
Aims
1. Match patient demographic data with morbidity and mortality outcomes in the PLCO dataset.
2. Provide real-time clinical decision support for pre-test probability of disease and optimized screening patient selection.
3. Use our findings as a model for case-based clinical decision support applications using evolving research databases.
Collaborators
Jason Hostetter, MD University of Maryland
Ken Wang, MD Baltimore VA/University of Maryland
Eliot Siegel, MD Baltimore VA/University of Maryland
Arjun Sharma, MD University of Maryland
Related Publications
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Focused Decision Support: a Data Mining Tool to Query the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Dataset and Guide Screening Management for the Individual Patient.
Sharma A, Hostetter J, Morrison J, Wang K, Siegel E
J Digit Imaging. 2015 Sep; Volume : Pages PUBMED