Meta-design knowledge for Clinical Decision Support Systems

Miah, Shah Jahan; Blake, Jacqueline; Kerr, Donald

doi:10.3127/ajis.v24i0.2049

Cited by 6 publications

(3 citation statements)

References 44 publications

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“…A novel design knowledge by extracting insights from a representative case of innovative Clinical Decision Support System (CDSS) development. The case is characterised by a specific architecture and six design principles [29]. [30] executed a novel emergency decision support system to enhance emergency managers' decision-making capabilities during crises by integrating diverse data sources.…”

Section: Decision Support Systems (Dss) Architecturementioning

confidence: 99%

A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

Mohamad Jazli Shafizan Jaafar

2024

jes

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This paper introduces a conceptual architecture for Fuzzy Risk-Based Decision Support Systems (R+DSS). This architecture is designed to provide a comprehensive and efficient approach to decision-making procedures in various domains involving assessing and controlling potential risks. The proposed architecture exhibits versatility in its applicability across multiple fields, such as finance, healthcare, engineering, and environmental management. It incorporates these components flexibly and scalable while also being user-friendly. The framework employs fuzzy logic principles such as membership functions, rule sets, and inference methods to facilitate a thorough evaluation of the risk that accommodates the inherent uncertainties and imprecisions characteristic of real-world risk scenarios. The Fuzzy Inference Engine is a versatile and resilient risk analysis tool capable of accommodating diverse data and systems, enabling effective risk mitigation strategies. The adaptability of this architecture to effectively handle complex, uncertain and dynamic environments makes it a promising tool for decision-makers looking to improve risk assessment and management protocols.

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Section: Decision Support Systems (Dss) Architecturementioning

confidence: 99%

A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

Mohamad Jazli Shafizan Jaafar

2024

jes

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“…For example, physician order entry systems help reduce time and errors in the medication process and provide effective medication to patients (Davidson & Chismar, 2007). Such clinical IT allows physicians to save time by managing all of their clinical jobs automatically (e.g., Shah et al, 2020;Zobair et al, 2021). For example, telehealth and telemedicine systems allow physicians to remotely treat patients and monitor their progress,…”

Section: H5mentioning

confidence: 99%

The Impacts of Role Overload and Role Conflict on Physicians’ Technology Adoption

Park

Zhang

et al. 2023

AJIS

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Technology adoption is an important solution for physicians to increase work efficiency, and thus deal with role conflict among their multiple job roles. Prior studies have not investigated how multiple job roles and role conflict influence physicians’ technology adoption intentions. Based on role strain theory and role identity theory, we present a model of physicians’ technology adoption intentions to support their primary (clinical care) versus secondary (teaching or research) job roles. We test the model using surveys with 156 physicians at nine medical schools in Korea. The results of our data analysis largely support our hypotheses. Role overload in each of their job roles increases role conflict between any pair of associated roles. Furthermore, role conflict between a physician’s primary and secondary role is affected more by role overload in the secondary role than by overload in the primary role. Moreover, the impact of role conflict on technology adoption intentions is also influenced by the hierarchical relationship between two roles. This study contributes to technology adoption research by demonstrating how physicians’ job characteristics affect technology adoption.

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“…The most decisive organizational factor in DSS design. Because organizational structure, processes and culture greatly determine decision-making (Freier and Schumann, 2021; Miah et al , 2020). Therefore, this research requires the identification of KM processes in the organization.…”

Section: Relevant Theoriesmentioning

confidence: 99%

Decision support system for fish quarantine measures in Indonesia

Hidayat

Satuti

Sensuse

et al. 2022

VJIKMS

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Purpose Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions. Design/methodology/approach This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS. Findings The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules. Originality/value This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

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Meta-design knowledge for Clinical Decision Support Systems

Cited by 6 publications

References 44 publications

A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

The Impacts of Role Overload and Role Conflict on Physicians’ Technology Adoption

Decision support system for fish quarantine measures in Indonesia

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