Advancement of Decision Support Systems, Complex Systems and Empirical Studies Based on the Fifteenth ICMSEM Proceedings

2021 ◽  
pp. 1-10
Author(s):  
Jiuping Xu
Keyword(s):  
Decision Support ◽  
Complex Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Empirical Studies

scholarly journals A review of measurement practice in studies of clinical decision support systems 1998–2017

2019 ◽  
Vol 26 (10) ◽  
pp. 1120-1128 ◽  
Author(s):  
Philip J Scott ◽  
Angela W Brown ◽  
Taiwo Adedeji ◽  
Jeremy C Wyatt ◽  
Andrew Georgiou ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Empirical Studies ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Impact Studies ◽  
Study Results ◽  
Measurement Methodology

Abstract Objective To assess measurement practice in clinical decision support evaluation studies. Materials and Methods We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention to measurement validity, reliability, or reuse. We used Friedman and Wyatt’s typology to categorize the studies. Results There were 391 studies that met the inclusion criteria. Study types in this cohort were primarily field user effect studies (n = 210) or problem impact studies (n = 150). Of those, 280 studies (72%) had no evidence of attention to measurement methodology, and 111 (28%) had some evidence with 33 (8%) offering validity evidence; 45 (12%) offering reliability evidence; and 61 (16%) reporting measurement artefact reuse. Discussion Only 5 studies offered validity assessment within the study. Valid measures were predominantly observed in problem impact studies with the majority of measures being clinical or patient reported outcomes with validity measured elsewhere. Conclusion Measurement methodology is frequently ignored in empirical studies of clinical decision support systems and particularly so in field user effect studies. Authors may in fact be attending to measurement considerations and not reporting this or employing methods of unknown validity and reliability in their studies. In the latter case, reported study results may be biased and effect sizes misleading. We argue that replication studies to strengthen the evidence base require greater attention to measurement practice in health informatics research.

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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