Abstract
The quality must be present external in consultation services, either to satisfy the needs of the users and/or to maximize the use of the resources. For this reason, administrators require the necessary information and knowledge to support them in decision-making processes. This paper presents a time series-based model, to predict absenteeism and attendance at the outpatient service. The CRISP-DM methodology, typical of data analytics, was used to explore the models. It was found that the ARIMA model was the one that obtained the lowest absolute and quadratic error. In addition, based on the time series predictions, it was determined that the number of absences to external medicine consultations is around 10% per day. This information can be used to reduce the attention time lost due to absences.
Original language | English |
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Title of host publication | Communication and Smart Technologies - Proceedings of ICOMTA 2021 |
Editors | Álvaro Rocha, Daniel Barredo, Paulo Carlos López-López, Iván Puentes-Rivera |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 3-12 |
Number of pages | 10 |
ISBN (Print) | 9789811657917 |
DOIs | |
State | Published - 2022 |
Event | International Conference on Communication and Applied Technologies, ICOMTA 2021 - Bogotá, Colombia Duration: 1 Sep 2021 → 3 Sep 2021 |
Publication series
Name | Smart Innovation, Systems and Technologies |
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Volume | 259 SIST |
ISSN (Print) | 2190-3018 |
ISSN (Electronic) | 2190-3026 |
Conference
Conference | International Conference on Communication and Applied Technologies, ICOMTA 2021 |
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Country/Territory | Colombia |
City | Bogotá |
Period | 1/09/21 → 3/09/21 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keywords
- Data analytics
- External consultation services
- Time series