A predictive model to identify hospitalized cancer patients at risk for 30-day mortality based on admission criteria via the electronic medical record

Alternate title: 
J2 - Cancer
Secondary title: 
T2 - Cancer
Short title: 
A predictive model to identify hospitalized cancer patients at risk for 30-day mortality based on admission criteria via the electronic medical record
Authors: 
Ramchandran, Kavitha J.
Shega, Joseph W.
Von Roenn, Jamie
Schumacher, Mark
Szmuilowicz, Eytan
Rademaker, Alfred
Weitner, Bing Bing
Loftus, Pooja D.
Chu, Isabella M.
Weitzman, Sigmund
Volume: 
119
Start page: 
2074-80
Annotations: 
Type D, Prognosis
Date: 
Jun 1
Year: 
2013
Accession number: 
23504709
Database: 
EMBASE Cohort
Number: 
M1 - 11
Serial: 
1097-0142
Type of work: 
M3 - Observational Study
ID: 
12991
DOI: 
http://dx.doi.org/10.1002/cncr.27974
Notes: 
N1 - Ramchandran KJ Shega JW Von Roenn J Schumacher M Szmuilowicz E Rademaker A Weitner BB Loftus PD Chu IM Weitzman S
Key words: 
Aged
Cohort Studies
*Electronic Health Records/sn [Statistics & Numerical Data]
Female
Hospital Mortality
Humans
Logistic Models
Male
*Models, Statistical
*Neoplasms/mo [Mortality]
*Patient Admission/sn [Statistics & Numerical Data]
Prognosis
Risk Assessment/mt [Methods]
Risk Factors
Types of evidence: 
Type D
Other annotations: 
Prognosis