How I use clinical decision support to improve red blood cell utilization

Transfusion ◽  
2016 ◽  
Vol 56 (10) ◽  
pp. 2406-2411 ◽  
Author(s):  
Lawrence Tim Goodnough ◽  
Steven Andrew Baker ◽  
Neil Shah
Keyword(s):  
Decision Support ◽  
Blood Cell ◽  
Clinical Decision Support ◽  
Red Blood Cell ◽  
Clinical Decision

Improving red blood cell orders, utilization, and management with point-of-care clinical decision support

Transfusion ◽  
2015 ◽  
Vol 55 (9) ◽  
pp. 2086-2094 ◽  
Author(s):  
Zeke J. McKinney ◽  
Jessica M. Peters ◽  
Jed B. Gorlin ◽  
Elizabeth H. Perry
Keyword(s):  
Decision Support ◽  
Blood Cell ◽  
Clinical Decision Support ◽  
Red Blood Cell ◽  
Point Of Care ◽  
Clinical Decision

Clinical decision support

2013 ◽  
Vol 46 (2) ◽  
pp. 52
Author(s):  
CHRISTOPHER NOTTE ◽  
NEIL SKOLNIK
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision

Architectures for Architects

1993 ◽  
Vol 32 (01) ◽  
pp. 12-13 ◽  
Author(s):  
M. A. Musen
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Design And Development

Abstract:Response to Heathfield HA, Wyatt J. Philosophies for the design and development of clinical decision-support systems. Meth Inform Med 1993; 32: 1-8.

Characterizing Decision Support Telemedicine Systems

2006 ◽  
Vol 45 (05) ◽  
pp. 523-527 ◽  
Author(s):  
A. Abu-Hanna ◽  
B. Nannings
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Literature Search ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Problem Dimension ◽  
Process Dimension

Summary Objectives: Decision Support Telemedicine Systems (DSTS) are at the intersection of two disciplines: telemedicine and clinical decision support systems (CDSS). The objective of this paper is to provide a set of characterizing properties for DSTSs. This characterizing property set (CPS) can be used for typing, classifying and clustering DSTSs. Methods: We performed a systematic keyword-based literature search to identify candidate-characterizing properties. We selected a subset of candidates and refined them by assessing their potential in order to obtain the CPS. Results: The CPS consists of 14 properties, which can be used for the uniform description and typing of applications of DSTSs. The properties are grouped in three categories that we refer to as the problem dimension, process dimension, and system dimension. We provide CPS instantiations for three prototypical applications. Conclusions: The CPS includes important properties for typing DSTSs, focusing on aspects of communication for the telemedicine part and on aspects of decisionmaking for the CDSS part. The CPS provides users with tools for uniformly describing DSTSs.

Sign in / Sign up

Export Citation Format

Share Document