Title |
Automated eligibility screening and monitoring for genotype-driven precision oncology trials
|
---|---|
Published in |
Journal of the American Medical Informatics Association, March 2016
|
DOI | 10.1093/jamia/ocw020 |
Pubmed ID | |
Authors |
Michael H Eubank, David M Hyman, Amritha D Kanakamedala, Stuart M Gardos, Jonathan M Wills, Peter D Stetson |
Abstract |
The Information Systems Department at Memorial Sloan Kettering Cancer Center developed the DARWIN Cohort Management System (DCMS). The DCMS identifies and tracks cohorts of patients based on genotypic and clinical data. It assists researchers and treating physicians in enrolling patients to genotype-matched IRB-approved clinical trials. The DCMS sends automated, actionable, and secure email notifications to users with information about eligible or enrolled patients before their upcoming appointments. The system also captures investigators input via annotations on patient eligibility and preferences on future status updates. As of August 2015, the DCMS is tracking 159,893 patients on both clinical operations and research cohorts. 134 research cohorts have been established and track 64,473 patients. 51,192 of these have had one or more genomic tests including MSK-IMPACT, comprising the pool eligible for genotype-matched studies. This paper describes the design and evolution of this Informatics solution. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 33% |
Philippines | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 36 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 28% |
Student > Ph. D. Student | 5 | 14% |
Professor > Associate Professor | 4 | 11% |
Student > Doctoral Student | 2 | 6% |
Student > Postgraduate | 2 | 6% |
Other | 5 | 14% |
Unknown | 8 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 10 | 28% |
Agricultural and Biological Sciences | 6 | 17% |
Biochemistry, Genetics and Molecular Biology | 3 | 8% |
Computer Science | 2 | 6% |
Business, Management and Accounting | 1 | 3% |
Other | 4 | 11% |
Unknown | 10 | 28% |