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Journal articles on the topic 'Decision support systems usability'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Danielsson, Mats, and Håkan Alm. "Usability and decision support systems in emergency management." Work 41 (2012): 3455–58. http://dx.doi.org/10.3233/wor-2012-0624-3455.

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Oras, Abdulkhudhur Hussein, and Hameed Mousa Ayad. "Toward measuring the usability of decision support applications in fog computing environment." Toward measuring the usability of decision support applications in fog computing environment 30, no. 3 (2023): 1689–98. https://doi.org/10.11591/ijeecs.v30.i3.pp1689-1698.

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Decision support systems are applications that provide meaningful information and help with decision support. To gain the benefits of these applications, they need to be used optimally. Thus, the optimal manner to utilize relies on several properties, such as usability. This research aims to investigate the decision support systems applications (DSS) in terms of usability evaluation and propose a usability instrument for DSS in a fog computing environment. Recently, complexity is a major problem with most software products. Hence, the way to ensure user satisfaction is by measuring its usabili

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Otieno Okal, Christopher, and Harriet Tsinale Loice. "USABILITY OF BIG DATA ANALYTICS WITHIN CLINICAL DECISION SUPPORT SYSTEMS." International Journal of Engineering Applied Sciences and Technology 04, no. 05 (2019): 64–73. http://dx.doi.org/10.33564/ijeast.2019.v04i05.010.

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Hardenbol, Alec Xander, Bram Knols, Mathijs Louws, Michiel Meulendijk, and Marjan Askari. "Usability aspects of medication-related decision support systems in the outpatient setting: A systematic literature review." Health Informatics Journal 26, no. 1 (2018): 72–87. http://dx.doi.org/10.1177/1460458218813732.

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In this study, we evaluated the usability aspects of medication-related clinical decision support systems in the outpatient setting. Articles published between 2000 and 2016 in Scopus, PubMed and EMBASE were searched and classified into three usability aspects: Effectiveness, Efficiency and Satisfaction. Using Van Welie et al.’s usability model, we categorized usability aspects in terms of usage indicators and means. Out of the 1999 articles, 24 articles met the selection criteria of which the main focus was on reducing inappropriate medication, prescription rate and prescription errors. Evide

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Hussein, Oras Abdulkhdhur, and Ayad Hameed Mousa. "Toward measuring the usability of decision support applications in fog computing environment." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1689. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1689-1698.

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Decision support systems are applications that provide meaningful information and help with decision support. To gain the benefits of these applications, they need to be used optimally. Thus, the optimal manner to utilize relies on several properties, such as usability. This research aims to investigate the decision support systems applications (DSS) in terms of usability evaluation and propose a usability instrument for DSS in a fog computing environment. Recently, complexity is a major problem with most software products. Hence, the way to ensure user satisfaction is by measuring its usabili

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Ghorayeb, Abir, Julie L. Darbyshire, Marta W. Wronikowska, and Peter J. Watkinson. "Design and validation of a new Healthcare Systems Usability Scale (HSUS) for clinical decision support systems: a mixed-methods approach." BMJ Open 13, no. 1 (2023): e065323. http://dx.doi.org/10.1136/bmjopen-2022-065323.

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ObjectiveTo develop and validate a questionnaire to assess the usability of clinical decision support systems (CDSS) and to assist in the early identification of usability issues that may impact patient safety and quality of care.DesignMixed research methods were used to develop and validate the questionnaire. The qualitative study involved scale item development, content and face validity. Pilot testing established construct validity using factor analysis and facilitated estimates for reliability and internal consistency using the Cronbach’s alpha coefficient.SettingTwo hospitals within a sin

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Knols, Bram, Mathijs Louws, Alec Hardenbol, Jamshid Dehmeshki, and Marjan Askari. "The usability aspects of medication-related decision support systems in the inpatient setting: A systematic review." Health Informatics Journal 26, no. 1 (2019): 613–27. http://dx.doi.org/10.1177/1460458219841167.

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Effort has been made to study the effect of medication-related clinical decision support systems in the inpatient setting; however, there is not much known about the usability of these systems. The goal of this study is to systematically review studies that focused on the usability aspects such as effectiveness, efficiency, and satisfaction of these systems. We systematically searched relevant articles in Scopus, Embase, and PubMed from 1 January 2000 to 1 January 2016, and found 22 articles. Based on Van Welie’s usability model, we categorized usability aspects in terms of usage indicators an

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Labinsky, Hannah, Dubravka Ukalovic, Fabian Hartmann, et al. "An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study." Diagnostics 13, no. 1 (2023): 148. http://dx.doi.org/10.3390/diagnostics13010148.

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Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support. The aim of this study was to investigate the accuracy, effectiveness, usability, and acceptance of such a CDSS—Rheuma Care Manager (RCM)—including an artificial intelligence (AI)-powered flare risk prediction tool to support the management of rheumatoid arthritis (RA). Longitudinal clinical routine data of RA patients were used to develop and test the R

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Suleymanova, Leila O., Zulai K. Tavbulatova, and Leila R. Magomaeva. "INNOVATIVE SYSTEMS FOR MANAGEMENT DECISION SUPPORT: ANALYSIS AND APPLICATION OF EXISTING SYSTEMS." Society, Economy, Management 8, no. 3 (2023): 68–74. http://dx.doi.org/10.47475/2618-9852-2023-8-3-68-74.

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In this scientific article, the analysis, development and application of innovative management decision support systems was carried out. Various systems were reviewed such as SAP Business Objects, IBM Cognos, Oracle Business Intelligence and ITSM 365. Each system was analyzed against a number of criteria such as data analytics capabilities, usability, performance and price. As a result, the advantages and disadvantages of each system were identified, which helped to determine their effectiveness and suitability for use in enterprises. It was found that the development and implementation of man

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Intedhar, Shakir Nasir, Hameed Mousa Ayad, M. Ali Alkhafaji Sakina, Shaker Abdul Hussein Wafia, Razzaq Jasim Zahraa, and Qasim Ali Saeed. "Virtual data integration for a clinical decision support systems." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5243–52. https://doi.org/10.11591/ijece.v13i5.pp5243-5252.

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Clinical decision support (CDS) supplies clinicians and their patients, and relevant staff with meaningful and timely information intelligently integrated or visualized to enhance health and the health sector. Data is the backbone of decision support systems, especially (clinical) ones. Data integration (either virtual or physical manner) is a powerful technique to manipulate a vast amount of heterogeneous data and prepare it as input for the decision-making process. The difficulties in manipulating data that have a physical data integration technique motivated the decision support developers

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Oztekin, Asil. "A decision support system for usability evaluation of web-based information systems." Expert Systems with Applications 38, no. 3 (2011): 2110–18. http://dx.doi.org/10.1016/j.eswa.2010.07.151.

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Nasir, Intedhar Shakir, Ayad Hameed Mousa, Sakina M. Ali Alkhafaji, Wafia Shaker Abdul Hussein, Zahraa Razzaq Jasim, and Saeed Qasim Ali. "Virtual data integration for a clinical decision support systems." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5243. http://dx.doi.org/10.11591/ijece.v13i5.pp5243-5252.

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<span lang="EN-US">Clinical decision support (CDS) supplies clinicians and their patients, and relevant staff with meaningful and timely information intelligently integrated or visualized to enhance health and the health sector. Data is the backbone of decision support systems, especially (clinical) ones. Data integration (either virtual or physical manner) is a powerful technique to manipulate a vast amount of heterogeneous data and prepare it as input for the decision-making process. The difficulties in manipulating data that have a physical data integration technique motivated the dec

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McGonagle, Erin A., Dean J. Karavite, Robert W. Grundmeier, et al. "Evaluation of an Antimicrobial Stewardship Decision Support for Pediatric Infections." Applied Clinical Informatics 14, no. 01 (2023): 108–18. http://dx.doi.org/10.1055/s-0042-1760082.

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Abstract Objectives Clinical decision support (CDS) has promise for the implementation of antimicrobial stewardship programs (ASPs) in the emergency department (ED). We sought to assess the usability of a newly developed automated CDS to improve guideline-adherent antibiotic prescribing for pediatric community-acquired pneumonia (CAP) and urinary tract infection (UTI). Methods We conducted comparative usability testing between an automated, prototype CDS-enhanced discharge order set and standard order set, for pediatric CAP and UTI antibiotic prescribing. After an extensive user-centered desig

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Kim, Min, Frederick Thum, Laura Rivera, et al. "Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment." Applied Clinical Informatics 07, no. 01 (2016): 128–42. http://dx.doi.org/10.4338/aci-2015-08-ra-0108.

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SummaryOlder adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed.To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions.Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in

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Sada, Imrana, Prof Obunadike G. N., and Mukhtar Abubakar. "Machine learning-based framework for predicting user satisfaction in e-Learning systems." Journal of Basics and Applied Sciences Research 3, no. 2 (2025): 78–85. https://doi.org/10.4314/jobasr.v3i2.9.

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The usability of eLearning systems is of paramount importance in determining the effectiveness and user satisfaction. This study introduces a machine learning-based framework to predict users satisfaction on eLearning System aiming to create user-centered platforms that cater to diverse learners satisfaction. The study employed machine learning models such as Support Vector Machines, Decision Trees and Neural Networks to predict user satisfaction towards usability of eLearning System. OC2 (Optimal Course Content & Online Collaboration Lab) dataset was subject into the three said models to

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Dhouib, Amira, Abdelawheb Trabelsi, Christophe Kolski, and Mahmoud Neji. "EvalCHOICE: A Decision Support Approach for the Usability Evaluation of Interactive Adaptive Systems." Procedia Computer Science 112 (2017): 864–73. http://dx.doi.org/10.1016/j.procs.2017.08.086.

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Kunath, Martin, and Herwig Winkler. "Usability of information systems to support decision making in the order management process." Procedia CIRP 81 (2019): 322–27. http://dx.doi.org/10.1016/j.procir.2019.03.056.

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Brauner, Philipp, Ralf Philipsen, André Calero Valdez, and Martina Ziefle. "What happens when decision support systems fail? — the importance of usability on performance in erroneous systems." Behaviour & Information Technology 38, no. 12 (2019): 1225–42. http://dx.doi.org/10.1080/0144929x.2019.1581258.

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Azadi, Ali, and Francisco José García-Peñalvo. "Optimizing Clinical Decision Support System Functionality by Leveraging Specific Human-Computer Interaction Elements: Insights From a Systematic Review." JMIR Human Factors 12 (May 6, 2025): e69333. https://doi.org/10.2196/69333.

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Background Clinical decision support systems (CDSSs) play a pivotal role in health care by enhancing clinical decision-making processes. These systems represent a significant advancement in medical information systems. However, optimizing their effectiveness requires accounting for various human-computer interaction (HCI) elements that influence their functionality and user acceptance. Objective This study aimed to identify and categorize key HCI elements that impact CDSS performance to enhance system usability, adaptability, and decision-making accuracy. Methods We conducted a systematic lite

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Haux, R. "Knowledge-Based Decision Support for Diagnosis and Therapy: On the Multiple Usability of Patient Data." Methods of Information in Medicine 28, no. 02 (1989): 69–77. http://dx.doi.org/10.1055/s-0038-1635551.

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Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechan

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Bouaud, J., and V. Koutkias. "Computerized Clinical Decision Support: Contributions from 2015." Yearbook of Medical Informatics 25, no. 01 (2016): 170–77. http://dx.doi.org/10.15265/iy-2016-055.

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Summary Objective: To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IM

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Souza, Enio Alves de, and Evaldo Cesar Cavalcante Rodrigues. "Usability of Cost systems in the Federal Public Sector." Revista Catarinense da Ciência Contábil 21 (August 19, 2022): e3224. http://dx.doi.org/10.16930/2237-7662202232242.

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The objective of this study was to identify the perception of the usability of the Federal Public sector cost systems by the managers and cost information users. To this end, a survey was carried out with sector and sectionals of costs of the Federal Government, using a questionnaire that was validated by brainstorming and by focal group. The research quantitative data were obtained from the application of the multicriteria analysis model for decision support - Constructivist “Multicriteria Decision Aid - Constructivist” (MCDA-C). The results, generated in the MyMCDA-C software, showed that ni

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Ltifi, Hela, Saber Amri, and Mounir Ben Ayed. "Fuzzy logic–based evaluation of visualizations generated by intelligent decision support systems." Information Visualization 17, no. 1 (2016): 3–21. http://dx.doi.org/10.1177/1473871616674046.

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The development of intelligent decision support systems requires much research effort to solve decision-making problems’ complexity. In fact, the combination of both intelligent components and visualization aspects in intelligent decision support system required a lot of efforts in order to develop advanced information visualization schemes for decision-making processes. For this, an efficient evaluation of these systems has become a major concern for applications in multiple fields. The reports of the existing usability evaluation studies are helpful to verify the potential and the limitation

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Cresswell, Kathrin, Margaret Callaghan, Hajar Mozaffar, and Aziz Sheikh. "NHS Scotland’s Decision Support Platform: a formative qualitative evaluation." BMJ Health & Care Informatics 26, no. 1 (2019): e100022. http://dx.doi.org/10.1136/bmjhci-2019-100022.

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ContextThe Scottish Government has identified computerised decision support as a strategic priority in order to improve knowledge management in health and social care settings. A national programme to build a pilot Decision Support Platform was funded in 2015.AimsWe undertook a formative evaluation of the Decision Support Platform to inform plans for its national roll-out in primary care.MethodsWe conducted a series of in-depth semistructured interviews and non-participant observations of workshops demonstrating decision support systems. Participants were policymakers and clinical opinion lead

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Blanes-Selva, Vicent, Sabina Asensio-Cuesta, Ascensión Doñate-Martínez, Felipe Pereira Mesquita, and Juan M. García-Gómez. "User-centred design of a clinical decision support system for palliative care: Insights from healthcare professionals." DIGITAL HEALTH 9 (January 2023): 205520762211507. http://dx.doi.org/10.1177/20552076221150735.

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Objective: Although clinical decision support systems (CDSS) have many benefits for clinical practice, they also have several barriers to their acceptance by professionals. Our objective in this study was to design and validate The Aleph palliative care (PC) CDSS through a user-centred method, considering the predictions of the artificial intelligence (AI) core, usability and user experience (UX). Methods: We performed two rounds of individual evaluation sessions with potential users. Each session included a model evaluation, a task test and a usability and UX assessment. Results: The machine

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Sacchi, L., G. Lanzola, N. Viani, and S. Quaglini. "Personalization and Patient Involvement in Decision Support Systems: Current Trends." Yearbook of Medical Informatics 24, no. 01 (2015): 106–18. http://dx.doi.org/10.15265/iy-2015-015.

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Summary Objectives: This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods: We considered papers published on scientific journals, by querying PubMed and Web of ScienceTM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since th

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Tsyganok, Vitaliy, Nikita Savchenko, and Roman Tsyhanok. "A universal transaction delegation method for decentralized decision support systems." Collection "Information Technology and Security" 12, no. 2 (2024): 184–98. https://doi.org/10.20535/2411-1031.2024.12.2.315737.

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This study examines methods for decentralizing computation and storage to enhance the security of end systems, focusing on decision support systems as a use case. Common limitations of system decentralization are identified, and a new, universal transaction delegation method is proposed to simplify decentralized system usage. An overview of available transaction delegation methods in self-protected decentralized data platforms is provided, based on well-known projects using the Ethereum platform. Four popular delegation methods in decentralized networks are distinguished, with their advantages

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Piira, Kalevi, Julia Kantorovitch, Lotta Kannari, Jouko Piippo, and Nam Vu Hoang. "Decision Support Tool to Enable Real-Time Data-Driven Building Energy Retrofitting Design." Energies 15, no. 15 (2022): 5408. http://dx.doi.org/10.3390/en15155408.

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The availability of near-real-time data on energy performance is opening new opportunities to optimize buildings’ energy efficiency and flexibility capabilities and to support the decision-making and planning process of building retrofitting infrastructure investment. Existing tools can support retrofitting design and energy performance contracting. However, there are well-recognized shortcomings of these tools related to their usability, complexity, and ability to perform calculations based on the real-time energy performance of buildings. To address this gap, the advanced retrofitting decisi

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Marcilly, Romaric, Wu Yi Zheng, Regis Beuscart, and Melissa T. Baysari. "Comparison of the validity, perceived usefulness and usability of I-MeDeSA and TEMAS, two tools to evaluate alert system usability: a study protocol." BMJ Open 11, no. 8 (2021): e050448. http://dx.doi.org/10.1136/bmjopen-2021-050448.

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IntroductionResearch has shown that improvements to the usability of medication alert systems are needed. For designers and decisions-makers to assess usability of their alert systems, two paper-based tools are currently available: the instrument for evaluating human-factors principles in medication-related decision support alerts (I-MeDeSA) and the tool for evaluating medication alerting systems (TEMAS). This study aims to compare the validity, usability and usefulness of both tools to identify their strengths and limitations and assist designers and decision-makers in making an informed deci

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shin, Juh Hyun, Chung Hyuk Park, Myungeun Lee, et al. "STANDARDIZED NURSING LANGUAGE—KNOWLEDGE-BASED CLINICAL DECISION SUPPORT SYSTEM MODULE FOR LONG TERM CARE NURSES." Innovation in Aging 8, Supplement_1 (2024): 1276–77. https://doi.org/10.1093/geroni/igae098.4081.

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Abstract Clinical decision support systems (CDSS) integrate patient health information with clinical expertise to guide referrals, reduce prescription medication errors, and ensure adherence to guidelines. Standardized nursing languages, such as NANDA-I (North American Nursing Diagnosis Association International), NIC (Nursing Interventions Classification), and NOC (Nursing Outcomes Classification), enhance evidence-based practice by providing essential diagnostic and outcome data. However, the adoption of CDSS in long term care settings, incorporating standardized nursing languages and cultur

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Moss, Richard H. "Assessing decision support systems and levels of confidence to narrow the climate information “usability gap”." Climatic Change 135, no. 1 (2015): 143–55. http://dx.doi.org/10.1007/s10584-015-1549-1.

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Abayomi, Abraham Ayodeji, Azubike Collins Mgbame, Oyinomomo-emi Emmanuel Akpe, Ejielo Ogbuefi, and Oluwatobi Opeyemi Adeyelu. "Automated decision support systems for resource-constrained businesses: A technical review." International Journal of Social Science Exceptional Research 1, no. 1 (2022): 246–62. https://doi.org/10.54660/ijsser.2022.1.1.246-262.

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In an era defined by digital transformation, resource-constrained businesses—particularly small and medium-sized enterprises (SMEs)—are under increasing pressure to make timely and accurate decisions despite limited access to skilled personnel, time, and capital. Automated Decision Support Systems (ADSS) represent a promising technological solution to this challenge, offering structured, data-driven guidance that enhances managerial decision-making while reducing operational overhead. This technical review explores the design, architecture, and deployment of ADSS tailored to the unique needs o

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King, Jayde, Yolanda Ortiz, Beth Blickensderfer, and Emalee Christy. "Challenges Contributing to the General Aviation Weather Problem & Decision Support Systems Technology Recommendations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 1771–75. http://dx.doi.org/10.1177/1541931218621401.

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General Aviation (GA) weather related accidents have steadily remained the most fatal accidents and incidents in the GA flight community. The majority of these accidents involve low-experienced Visual Flight Rule (VFR) pilots, inadvertently encountering Instrument Meteorological Conditions (IMC). Previous research indicates, poor inflight weather avoidance could stem from insufficient preflight weather planning. Further investigation reveals, pilots’ face many challenges during the preflight planning process, including: poor weather product interpretation/ usability, decision making biases and

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Schubel, Laura, Robin Littlejohn, Ronald Romero Barrientos, Ryan Arnold, Muge Capan, and Kristen Miller. "Everything but the Kitchen Sink: A Mixed Methods Approach to Health IT Usability Testing." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 718–22. http://dx.doi.org/10.1177/1071181319631290.

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Usability testing has become a necessary step to successfully implement health information technology, but despite the expanded variety of usability methods, systems still are not guaranteed to meet user needs in a hectic and dynamic healthcare environment. The present work discusses some of the metrics employed with the intent of usability testing clinical decision support alerts for the early identification of sepsis patients. By utilizing methods such as eye tracking, think aloud protocols, human computer interaction, and more, health information technology can be adequately developed to en

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Nugraha, Dwianto, and Chinwendu Onuegbu. "Healthcare Professionals’ Views on Decision Support Systems for Resource Management." Journal of Resource Management and Decision Engineering 3, no. 2 (2024): 4–12. http://dx.doi.org/10.61838/kman.jrmde.3.2.2.

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The objective of this study is to explore healthcare professionals' views on Decision Support Systems (DSS) for resource management. It aims to identify the benefits, challenges, and effective implementation strategies associated with DSS, providing insights that can inform the optimization of these systems in healthcare settings. This qualitative research employed semi-structured interviews to gather data from 12 healthcare professionals with direct experience in resource management and familiarity with DSS. Participants were purposively sampled from various departments within a large urban h

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Dunn Lopez, Karen, Sheila M. Gephart, Rebecca Raszewski, Vanessa Sousa, Lauren E. Shehorn, and Joanna Abraham. "Integrative review of clinical decision support for registered nurses in acute care settings." Journal of the American Medical Informatics Association 24, no. 2 (2016): 441–50. http://dx.doi.org/10.1093/jamia/ocw084.

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Objective: To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. Materials and Methods: We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts,

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Choi, Hyeonkyeong, Yourim Kim, and Wonseuk Jang. "Enhancing the Usability of Patient Monitoring Devices in Intensive Care Units: Usability Engineering Processes for Early Warning System (EWS) Evaluation and Design." Journal of Clinical Medicine 14, no. 9 (2025): 3218. https://doi.org/10.3390/jcm14093218.

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Background/Objectives: This study aimed to enhance the usability of patient monitoring systems by integrating the Early Warning Score (EWS) function and improving user interface elements. The EWS function is expected to enable the early detection of acute deterioration and prompt medical intervention, while the optimized design supports rapid decision-making by nursing staff. Methods: Two formative usability evaluations were conducted to identify user requirements and improve the device design. A simulated usability test involved five ICU medical staff members, followed by a user preference su

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Chien, Shuo-Chen, Ya-Lin Chen, Chia-Hui Chien, et al. "Alerts in Clinical Decision Support Systems (CDSS): A Bibliometric Review and Content Analysis." Healthcare 10, no. 4 (2022): 601. http://dx.doi.org/10.3390/healthcare10040601.

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A clinical decision support system (CDSS) informs or generates medical recommendations for healthcare practitioners. An alert is the most common way for a CDSS to interact with practitioners. Research about alerts in CDSS has proliferated over the past ten years. The research trend is ongoing with new emerging terms and focus. Bibliometric analysis is ideal for researchers to understand the research trend and future directions. Influential articles, institutes, countries, authors, and commonly used keywords were analyzed to grasp a comprehensive view on our topic, alerts in CDSS. Articles publ

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Basavaraj, Kaladagi, Krishna Prasad Bodapati Rama, and Guptal Rachit. "Context-Aware NLP in Healthcare: AI-Powered Medical Text Processing for Clinical Decision Support Systems." Global Journal of Engineering and Technology [GJET] 4, no. 2 (2025): 19–21. https://doi.org/10.5281/zenodo.14964402.

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<em>The rapid advancement of Natural Language Processing (NLP) and Artificial Intelligence (AI) has created substantial opportunities for improving healthcare delivery, particularly in the realm of clinical decision support systems (CDSS). Context-aware NLP techniques are increasingly being integrated into healthcare settings to extract valuable insights from unstructured medical texts. The role of <strong>Software Engineering</strong> in building scalable and efficient AI-driven healthcare solutions is paramount, especially in handling <strong>APIs</strong>, <strong>Distributed Systems</stron

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Romero-Riaño, Efrén, Claudia Galeano-Barrera, César D. Guerrero, Mauricio Martinez-Toro, and Dewar Rico-Bautista. "IoT applied to irrigation systems in agriculture: A usability analysis." Revista Colombiana de Computación 23, no. 1 (2022): 44–52. http://dx.doi.org/10.29375/25392115.4483.

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The Internet of Things favors using technological tools in rural environments thanks to the ability to connect to the Internet between devices that facilitate daily tasks. The research aims to evaluate the usability of the decision support system for irrigation in agriculture, AgroRIEGO, through the development of an IoT-based device. The sponsors of this project were the Ministry of Information and Communication Technologies and the Center of Excellence in the Internet of Things Appropriation (CEA-IoT) in Colombia. Among the methods used is the use of the heuristic evaluation technique, struc

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Ruponen, Pekka, Petri Pennanen, and Teemu Manderbacka. "On the alternative approaches to stability analysis in decision support for damaged passenger ships." WMU Journal of Maritime Affairs 18, no. 3 (2019): 477–94. http://dx.doi.org/10.1007/s13437-019-00186-8.

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Abstract A decision support system with damage stability analysis has been recognized as an important tool for passenger ships. Various software applications have been developed and taken into use over the years, without a direct link to any compelling requirement, set forth in the international regulatory framework. After the Costa Concordia accident, new regulations have been established, setting minimum requirements for a decision support system, as an extension to a loading computer. Yet, more advanced systems have been developed recently, aiming at providing valuable additional informatio

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Reynolds, Tera L., Patricia R. DeLucia, Karen A. Esquibel, et al. "Evaluating a handheld decision support device in pediatric intensive care settings." JAMIA Open 2, no. 1 (2019): 49–61. http://dx.doi.org/10.1093/jamiaopen/ooy055.

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Abstract Objective To evaluate end-user acceptance and the effect of a commercial handheld decision support device in pediatric intensive care settings. The technology, pac2, was designed to assist nurses in calculating medication dose volumes and infusion rates at the bedside. Materials and Methods The devices, manufactured by InformMed Inc., were deployed in the pediatric and neonatal intensive care units in 2 health systems. This mixed methods study assessed end-user acceptance, as well as pac2’s effect on the cognitive load associated with bedside dose calculations and the rate of administ

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Delvaux, Nicolas, Bert Vaes, Bert Aertgeerts, et al. "Coding Systems for Clinical Decision Support: Theoretical and Real-World Comparative Analysis." JMIR Formative Research 4, no. 10 (2020): e16094. http://dx.doi.org/10.2196/16094.

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Background Effective clinical decision support systems require accurate translation of practice recommendations into machine-readable artifacts; developing code sets that represent clinical concepts are an important step in this process. Many clinical coding systems are currently used in electronic health records, and it is unclear whether all of these systems are capable of efficiently representing the clinical concepts required in executing clinical decision support systems. Objective The aim of this study was to evaluate which clinical coding systems are capable of efficiently representing

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Ehnfors, M., A. Fruhling, A. Ehrenberg, and M. Fossum. "An Evaluation of the Usability of a Computerized Decision Support System for Nursing Homes." Applied Clinical Informatics 02, no. 04 (2011): 420–36. http://dx.doi.org/10.4338/aci-2011-07-ra-0043.

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SummaryBackground: Computerized decision support systems (CDSSs) have the potential to significantly improve the quality of nursing care of older people by enhancing the decision making of nursing personnel. Despite this potential, health care organizations have been slow to incorporate CDSSs into nursing home practices.Objective: This study describes facilitators and barriers that impact the ability of nursing personnel to effectively use a clinical CDSS for planning and treating pressure ulcers (PUs) and malnutrition and for following the suggested risk assessment guidelines for the care of

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Nurulita, Khiara, Nurcahya PradanaTaufik Prakisya, and Dwi Maryono. "Utilization Method Simple Additive Weighting in Decision Support Systems to Determine Outstanding Students." Jurnal Media Informasi Teknologi 1, no. 2 (2024): 71–82. http://dx.doi.org/10.69616/mit.v1i2.189.

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Giving awards to outstanding students is one of the motivators so that students develop, improve, and maintain their achievements in the academic/non-academic field so that healthy competition arises between students in positive terms. However, in determining student achievement the determining factor is only based on the results of the national exam scores. The drawback is that it is considered subjective because students who have achievements do not necessarily get good test scores so a system is designed that can assist in determining outstanding students, namely the Decision Support System

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Nikitin, A. N., I. A. Cheshyk, S. A. Kalinichenko, and O. A. Shurankova. "Models of radionuclides behavior in "soil-plant" chain for decision support systems." "Radiation and Risk" Bulletin of the National Radiation and Epidemiological Registry 31, no. 3 (2022): 57–76. http://dx.doi.org/10.21870/0131-3878-2022-31-3-57-76.

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The main objectives for semi-mechanistic models enhancement are justified in the article. The "soil-plant" chain is an essential part of radioisotopes flows from nuclear accident depositions to human beings. Therefore a model which describes this system should be integrated into decision support systems for liquidation consequences of accidents with releasing radioisotopes into the environment, evaluation effectiveness of measures for radiation protection, and designing hazardous radiation facilities. Such a model must show rather exact forecast results, flexibility and wide application area c

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Rousseau, Robert, James Easter, William Elm, and Scott Potter. "Decision-Centered Testing (DCT): Evaluating Joint Human-Computer Cognitive Work." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 3 (2005): 322–26. http://dx.doi.org/10.1177/154193120504900323.

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In order to test the effectiveness of a human operator paired with a decision support system, it is necessary to complement current testing practices addressing software validation, human performance, and usability. Decision Centered Testing (DCT) aims at testing the effectiveness of operators teamed with Decision Support Systems (DSS) in any challenging work domain. DCT is grounded in a Cognitive Systems Engineering (CSE) framework, where the concept of a joint cognitive system (JCS) is central. DCT aims at evaluating the decision-making effectiveness across identified 'error prone' regions i

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Janardhan Deepa and Jayashree Jayaraman. "Adaptive Learning Systems for Data Conversion in EHRs through Machine Learning." Advance Sustainable Science Engineering and Technology 7, no. 2 (2025): 0250211. https://doi.org/10.26877/aqvgnq17.

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Healthcare data management has advanced with Electronic Health Records (EHRs), enhancing the efficiency of medical procedures. Machine learning applied to EHRs transitions healthcare from reactive to proactive, supporting the cost-efficiency and sustainability goals of smart cities. However, digitizing medical records introduces security risks, especially from internal threats, necessitating strong detection systems. Research into machine learning techniques, such as decision trees, random forests, and support vector machines (SVMs), shows their effectiveness in detecting EHR breaches. Balanci

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Gutenstein, Marc, John W. Pickering, and Martin Than. "Development of a digital clinical pathway for emergency medicine: Lessons from usability testing and implementation failure." Health Informatics Journal 25, no. 4 (2018): 1563–71. http://dx.doi.org/10.1177/1460458218779099.

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Clinical pathways are used to support the management of patients in emergency departments. An existing document-based clinical pathway was used as the foundation on which to design and build a digital clinical pathway for acute chest pain, with the aim of improving clinical calculations, clinician decision-making, documentation, and data collection. Established principles of decision support system design were used to build an application within the existing electronic health record, before testing with a multidisciplinary team of doctors using a think-aloud protocol. Technical authoring was s

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Wiggerthale, Julius, and Christoph Reich. "Explainable Machine Learning in Critical Decision Systems: Ensuring Safe Application and Correctness." AI 5, no. 4 (2024): 2864–96. https://doi.org/10.3390/ai5040138.

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Machine learning (ML) is increasingly used to support or automate decision processes in critical decision systems such as self driving cars or systems for medical diagnosis. These systems require decisions in which human lives are at stake and the decisions should therefore be well founded and very reliable. This need for reliability contrasts with the black-box nature of many ML models, making it difficult to ensure that they always behave as intended. In face of the high stakes involved, the resulting uncertainty is a significant challenge. Explainable artificial intelligence (XAI) addresses

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