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When every minute matters : using predictive analytics of intervention durations to support hospital scheduling
Oberste, Luis
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Aydingül, Okan
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Jussupow, Ekaterina
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Heinzl, Armin
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URL:
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https://aisel.aisnet.org/pacis2021/221/
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Document Type:
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Conference or workshop publication
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Year of publication:
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2021
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Book title:
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PACIS 2021 : Pacific Asia Conference on Information Systems, 12th to 14th July 2021, Dubai
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The title of a journal, publication series:
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PACIS Proceedings
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Volume:
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2021, 221
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Page range:
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1-9
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Conference title:
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PACIS 2021
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Location of the conference venue:
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Online
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Date of the conference:
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12.-14.07.2021
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Place of publication:
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Atlanta, GA
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Publishing house:
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AISeL
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Publication language:
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English
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Institution:
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Business School > ABWL, Organisation u. Wirtschaftsinformatik I (Heinzl)
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Subject:
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004 Computer science, internet
330 Economics
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Keywords (English):
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Predictive analytics, treatment durations, hospital scheduling, healthcare
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Abstract:
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Clinical interventions subordinate to medical pathways are characterized by patient-specific complications and variability of process durations. At the same time, estimating these durations is critical for developing accurate schedules. However, data of clinical information systems are recorded primarily for reporting, liability, and billing purposes; the systems do not fully capture detailed process information. Very little work has been done on predicting these types of durations for scheduling, other than using experts’ estimates or historical averages. We evaluate how predictive analytics based on patient-specific features can help develop estimates of otherwise unknown process durations, taking infusion chemotherapy as an example. We highlight the challenges of using clinical real-life data and discuss how we plan to address these challenges in the future.
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Additional information:
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Online-Ressource
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Oberste, Luis
;
Aydingül, Okan
;
Jussupow, Ekaterina
;
Heinzl, Armin
Google Scholar:
Oberste, Luis
;
Aydingül, Okan
;
Jussupow, Ekaterina
;
Heinzl, Armin
ORCID:
Oberste, Luis ; Aydingül, Okan ; Jussupow, Ekaterina  ORCID: 0000-0002-3009-076X ; Heinzl, Armin
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