Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries

Patrick Skov Johansen; Rune Møberg Jacobsen; Lukas Bjørn Leer Bysted; Mikael B. Skov; Eleftherios Papachristos

doi:10.18573/book3.y

Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries

Patrick Skov Johansen, Rune Møberg Jacobsen, Lukas Bjørn Leer Bysted, Mikael B. Skov, Eleftherios Papachristos

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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Abstract

Advances in Machine Learning (ML) provide new opportunities for
augmenting work practice. In this paper, we explored how an ML-based suggestion system can augment Danish medical secretaries in their daily tasks of handling patient referrals and allocating patients to a hospital ward. Through a usercentred design process, we studied the work context and processes of two medical
secretaries. This generated a model of how a medical secretary would assess a
visitation suggestion, and furthermore, it provided insights into how a system
could fit into the medical secretaries’ daily tasks. We present our system design
and discuss how our contribution may be of value to HCI practitioners designing
for work augmentation in similar contexts.

Original language	English
Title of host publication	Human Computer Interaction and Emerging Technologies : Workshop Proceedings from the INTERACT 2019 Workshops
Publisher	Cardiff University Press
Publication date	2020
Pages	191-196
ISBN (Electronic)	978-1-911653-09-7
DOIs	https://doi.org/10.18573/book3.y https://doi.org/10.18573/book3.y
Publication status	Published - 2020
Event	INTERACT 2019: The 17th IFIP TC.13 International Conference on Human-Computer Interaction - Paphos, Cyprus Duration: 2 Sep 2019 → 6 Sep 2019 Conference number: 17 http://interact2019.org

Conference

Conference	INTERACT 2019
Number	17
Country	Cyprus
City	Paphos
Period	02/09/2019 → 06/09/2019
Internet address	http://interact2019.org

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Johansen, P. S., Jacobsen, R. M., Bysted, L. B. L., Skov, M. B., & Papachristos, E. (2020). Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries. In Human Computer Interaction and Emerging Technologies: Workshop Proceedings from the INTERACT 2019 Workshops (pp. 191-196). Cardiff University Press. https://doi.org/10.18573/book3.y, https://doi.org/10.18573/book3.y

Johansen, Patrick Skov ; Jacobsen, Rune Møberg ; Bysted, Lukas Bjørn Leer ; Skov, Mikael B. ; Papachristos, Eleftherios. / Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries. Human Computer Interaction and Emerging Technologies: Workshop Proceedings from the INTERACT 2019 Workshops. Cardiff University Press, 2020. pp. 191-196

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title = "Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries",

abstract = "Advances in Machine Learning (ML) provide new opportunities foraugmenting work practice. In this paper, we explored how an ML-based suggestion system can augment Danish medical secretaries in their daily tasks of handling patient referrals and allocating patients to a hospital ward. Through a usercentred design process, we studied the work context and processes of two medicalsecretaries. This generated a model of how a medical secretary would assess avisitation suggestion, and furthermore, it provided insights into how a systemcould fit into the medical secretaries{\textquoteright} daily tasks. We present our system designand discuss how our contribution may be of value to HCI practitioners designingfor work augmentation in similar contexts.",

author = "Johansen, {Patrick Skov} and Jacobsen, {Rune M{\o}berg} and Bysted, {Lukas Bj{\o}rn Leer} and Skov, {Mikael B.} and Eleftherios Papachristos",

year = "2020",

doi = "10.18573/book3.y",

language = "English",

pages = "191--196",

booktitle = "Human Computer Interaction and Emerging Technologies",

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Johansen, PS, Jacobsen, RM, Bysted, LBL, Skov, MB & Papachristos, E 2020, Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries. in Human Computer Interaction and Emerging Technologies: Workshop Proceedings from the INTERACT 2019 Workshops. Cardiff University Press, pp. 191-196, INTERACT 2019, Paphos, Cyprus, 02/09/2019. https://doi.org/10.18573/book3.y, https://doi.org/10.18573/book3.y

Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries. / Johansen, Patrick Skov; Jacobsen, Rune Møberg; Bysted, Lukas Bjørn Leer; Skov, Mikael B.; Papachristos, Eleftherios.

Human Computer Interaction and Emerging Technologies: Workshop Proceedings from the INTERACT 2019 Workshops. Cardiff University Press, 2020. p. 191-196.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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DO - 10.18573/book3.y

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Johansen PS, Jacobsen RM, Bysted LBL, Skov MB , Papachristos E. Designing a Machine Learning-Based System to Augment the Work Processes of Medical Secretaries. In Human Computer Interaction and Emerging Technologies: Workshop Proceedings from the INTERACT 2019 Workshops. Cardiff University Press. 2020. p. 191-196 https://doi.org/10.18573/book3.y, https://doi.org/10.18573/book3.y