A Participatory Approach for Developing Decision Support Systems for Building Energy Plants

2020 ◽  
pp. 349-357
Author(s):  
Samuel Patterson ◽  
Talara Berry ◽  
Michael Campbell
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Building Energy ◽  
Participatory Approach ◽  
Energy Plants

Effect of a participatory approach on the successful development of agricultural decision support systems: The case of Pigs2win

2012 ◽  
Vol 54 (1) ◽  
pp. 164-172 ◽  
Author(s):  
Jef Van Meensel ◽  
Ludwig Lauwers ◽  
Ine Kempen ◽  
Joost Dessein ◽  
Guido Van Huylenbroeck
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Participatory Approach ◽  
Successful Development

A Participatory Approach to Designing Decision Support Systems in Emergency Management

2014 ◽  
Vol 6 (1) ◽  
pp. 60-80 ◽  
Author(s):  
Pietro Baroni ◽  
Daniela Fogli ◽  
Massimiliano Giacomin ◽  
Giovanni Guida ◽  
Loredana Parasiliti Provenza ◽  
...  
Keyword(s):  
Decision Support ◽  
Emergency Management ◽  
Decision Support Systems ◽  
Participatory Design ◽  
Support Systems ◽  
Participatory Approach ◽  
Work Environments ◽  
System Evaluation ◽  
Health Related ◽  
Pandemic Flu

This article presents a participatory design approach to Decision Support Systems, which is specifically built to face the socio-technical gap that often impedes DSS acceptability by end-users in real work environments. The approach has been experimented in two case studies in the field of health-related emergencies, namely earthquake and pandemic flu. The application of the approach and the results obtained are described with specific focus on the phases of requirement analysis and system evaluation.

Assigning Value to Clinical Information – A Major Limiting Factor in the Implementation of Decision-Support Systems

1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Clinical Information ◽  
Limiting Factor ◽  
Major Difficulty ◽  
Computer Aided ◽  
Computer Aided Decision

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.

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.

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