scholarly journals Clinical Decision Support Systems: An Effective Pathway to Reduce Medical Errors and Improve Patient Safety

10.5772/39469 ◽  
2010 ◽  
Author(s):  
Chiang S. ◽  
Daniel B.
Keyword(s):  
Patient Safety ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Medical Errors ◽  
Support Systems ◽  
Improve Patient Safety ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Improve Patient

Framework for Evaluating Appropriateness of Clinical Decision Support Systems Alert in Supporting Clinical Workflow (Preprint)

2019 ◽  
Author(s):  
Maryati Yusof ◽  
Olufisayo Olakotan ◽  
Sharifa Ezat Puteh
Keyword(s):  
Patient Safety ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Process Analysis ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structured Interview ◽  
Clinical Workflow

BACKGROUND Clinical decision support systems (CDSS) generate excessive alerts that lead to alert fatigue and override. Alert overrides have resulted in patient death and medical errors. CDSS with its alert function can also disrupt clinical workflow. Therefore, inefficient clinical processes that contribute to the misfit between CDSS alert and workflows must be evaluated. Evaluation findings can serve as input to the process redesign. Redesigning clinical processes can enhance CDSS alert appropriateness and subsequently improve patient safety. OBJECTIVE The paper presents a proposed framework for evaluating CDSS appropriateness in supporting clinical workflow. The paper also discusses the preliminary results of the framework validation. METHODS A subjectivist, qualitative case study evaluation was conducted at a 620-bed public teaching hospital using semi-structured interview, observation, and document analysis methods to investigate the features and functions of alert appropriateness and workflow related issues. The current state map for medication prescription process was also modelled to identify problems pertinent to alert appropriateness. RESULTS The main findings showed that CDSS is not well designed to fit into clinical workflow due to several influencing factors including technology (system design and implementation), human (information analysis and acquisition), organization (clinical tasks, organizational policies & procedures) and process (process analysis, redesign, implementation, monitoring and improvement) impeding the use of CDSS with its alert function. CONCLUSIONS CDSS alerts should be integrated into clinical workflows due to their potentials in enhancing patient safety. Process improvement methods such as Lean can be used to enhance the appropriateness of CDSS alerts by identifying inefficient clinical processes that impede the fit of CDSS alerts with clinical workflow. The validated framework can be used to address alert and workflow related problems in any healthcare setting.

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.

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

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.

Sign in / Sign up

Export Citation Format

Share Document