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Dr. Michiel Meulendijk

Dr. Michiel Meulendijk

Data Scientist & Researcher in Medical Informatics

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PRESOMATIC

The PRESOMATIC study aims at aiding general practitioners with the early recognition of somatic symptom disorders.

As a researcher and data scientist, I created the data processing pipeline through which the hypotheses were tested.

Software & Publications

    Author Senior Researcher & Data ScientistPosted on October 1, 2017August 8, 2018Categories ResearchTags research

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    I am an information scientist and data expert (data scientist, infrastructure architect, software developer) in the medical domain.

    My fields of work include data analytics, semantic interoperability, governance and FAIR principles, natural language processing, and decision-support systems.

    Latest Publication

    14 entries « ‹ 1 of 14 › »
    Hardenbol, Alec Xander; Knols, Bram; Louws, Mathijs; Meulendijk, Michiel C; Askari, Marjan: Usability aspects of medication-related decision support systems in the outpatient setting: A systematic literature review. Health Informatics Journal, 2018. (Type: Journal Article | Abstract | Links | BibTeX)
    @article{Hardenbol2018,
    title = {Usability aspects of medication-related decision support systems in the outpatient setting: A systematic literature review},
    author = {Alec Xander Hardenbol and Bram Knols and Mathijs Louws and Michiel C Meulendijk and Marjan Askari},
    doi = {10.1177/1460458218813732},
    year = {2018},
    date = {2018-11-30},
    journal = { Health Informatics Journal},
    abstract = {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. Evidence could mainly be found for Effectiveness and showed high rates of positive results in reducing medication errors. To date, the effects of Efficiency and Satisfaction of clinical decision support systems regarding medication prescription remain understudied. Usability aspects such as memorability, learnability, adaptability, shortcuts and consistency require more attention. Studies are needed for better insight into the user model and to design a knowledge/task model for clinical decision support systems regarding medication prescription.},
    keywords = {},
    pubstate = {published},
    tppubtype = {article}
    }

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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. Evidence could mainly be found for Effectiveness and showed high rates of positive results in reducing medication errors. To date, the effects of Efficiency and Satisfaction of clinical decision support systems regarding medication prescription remain understudied. Usability aspects such as memorability, learnability, adaptability, shortcuts and consistency require more attention. Studies are needed for better insight into the user model and to design a knowledge/task model for clinical decision support systems regarding medication prescription.

    Close

    • doi:10.1177/1460458218813732

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    14 entries « ‹ 1 of 14 › »

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