Identifying the data elements and functionalities of clinical decision-support systems to administer medications for neonates and pediatrics: A systematic literature review protocol v1

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.

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Characterizing Decision Support Telemedicine Systems

Methods of Information in Medicine ◽

10.1055/s-0038-1634113 ◽

2006 ◽

Vol 45 (05) ◽

pp. 523-527 ◽

Cited By ~ 3

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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The acceptance of clinical decision support systems among clinicians in the treatment of neck and/or back pain

European Journal of Public Health ◽

10.1093/eurpub/ckaa165.1234 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

S M Jansen-Kosterink ◽

M Cabrita ◽

I Flierman

Keyword(s):

Back Pain ◽

Decision Support ◽

Focus Groups ◽

Decision Support Systems ◽

Clinical Decision Support ◽

Support Systems ◽

Clinical Decision Support Systems ◽

Clinical Decision ◽

Case Based Reasoning ◽

Online Questionnaire

Abstract Background Clinical Decision Support Systems (CDSSs) are computerized systems using case-based reasoning to assist clinicians in making clinical decisions. Despite the proven added value to public health, the implementation of CDSS clinical practice is scarce. Particularly, little is known about the acceptance of CDSS among clinicians. Within the Back-UP project (Project Number: H2020-SC1-2017-CNECT-2-777090) a CDSS is developed with prognostic models to improve the management of Neck and/or Low Back Pain (NLBP). Therefore, the aim of this study is to present the factors involved in the acceptance of CDSSs among clinicians. Methods To assess the acceptance of CDSSs among clinicians we conducted a mixed method analysis of questionnaires and focus groups. An online questionnaire with a low-fidelity prototype of a CDSS (TRL3) was sent to Dutch clinicians aimed to identify the factors influencing the acceptance of CDSSs (intention to use, perceived threat to professional autonomy, trusting believes and perceived usefulness). Next to this, two focus groups were conducted with clinicians addressing the general attitudes towards CDSSs, the factors determining the level of acceptance, and the conditions to facilitate use of CDSSs. Results A pilot-study of the online questionnaire is completed and the results of the large evaluation are expected spring 2020. Eight clinicians participated in two focus groups. After being introduced to various types of CDSSs, participants were positive about the value of CDSS in the care of NLBP. The clinicians agreed that the human touch in NLBP care must be preserved and that CDSSs must remain a supporting tool, and not a replacement of their role as professionals. Conclusions By identifying the factors hindering the acceptance of CDSSs we can draw implications for implementation of CDSSs in the treatment of NLBP.

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