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Timing errors and temporal uncertainty in clinical databases—A narrative review
A firm concept of time is essential for establishing causality in a clinical setting. Review of critical incidents and generation of study hypotheses require a robust understanding of the sequence of events but conducting such work can be problematic when timestamps are recorded by independent and u...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433547/ https://www.ncbi.nlm.nih.gov/pubmed/36060541 http://dx.doi.org/10.3389/fdgth.2022.932599 |
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author | Goodwin, Andrew J. Eytan, Danny Dixon, William Goodfellow, Sebastian D. Doherty, Zakary Greer, Robert W. McEwan, Alistair Tracy, Mark Laussen, Peter C. Assadi, Azadeh Mazwi, Mjaye |
author_facet | Goodwin, Andrew J. Eytan, Danny Dixon, William Goodfellow, Sebastian D. Doherty, Zakary Greer, Robert W. McEwan, Alistair Tracy, Mark Laussen, Peter C. Assadi, Azadeh Mazwi, Mjaye |
author_sort | Goodwin, Andrew J. |
collection | PubMed |
description | A firm concept of time is essential for establishing causality in a clinical setting. Review of critical incidents and generation of study hypotheses require a robust understanding of the sequence of events but conducting such work can be problematic when timestamps are recorded by independent and unsynchronized clocks. Most clinical models implicitly assume that timestamps have been measured accurately and precisely, but this custom will need to be re-evaluated if our algorithms and models are to make meaningful use of higher frequency physiological data sources. In this narrative review we explore factors that can result in timestamps being erroneously recorded in a clinical setting, with particular focus on systems that may be present in a critical care unit. We discuss how clocks, medical devices, data storage systems, algorithmic effects, human factors, and other external systems may affect the accuracy and precision of recorded timestamps. The concept of temporal uncertainty is introduced, and a holistic approach to timing accuracy, precision, and uncertainty is proposed. This quantitative approach to modeling temporal uncertainty provides a basis to achieve enhanced model generalizability and improved analytical outcomes. |
format | Online Article Text |
id | pubmed-9433547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94335472022-09-02 Timing errors and temporal uncertainty in clinical databases—A narrative review Goodwin, Andrew J. Eytan, Danny Dixon, William Goodfellow, Sebastian D. Doherty, Zakary Greer, Robert W. McEwan, Alistair Tracy, Mark Laussen, Peter C. Assadi, Azadeh Mazwi, Mjaye Front Digit Health Digital Health A firm concept of time is essential for establishing causality in a clinical setting. Review of critical incidents and generation of study hypotheses require a robust understanding of the sequence of events but conducting such work can be problematic when timestamps are recorded by independent and unsynchronized clocks. Most clinical models implicitly assume that timestamps have been measured accurately and precisely, but this custom will need to be re-evaluated if our algorithms and models are to make meaningful use of higher frequency physiological data sources. In this narrative review we explore factors that can result in timestamps being erroneously recorded in a clinical setting, with particular focus on systems that may be present in a critical care unit. We discuss how clocks, medical devices, data storage systems, algorithmic effects, human factors, and other external systems may affect the accuracy and precision of recorded timestamps. The concept of temporal uncertainty is introduced, and a holistic approach to timing accuracy, precision, and uncertainty is proposed. This quantitative approach to modeling temporal uncertainty provides a basis to achieve enhanced model generalizability and improved analytical outcomes. Frontiers Media S.A. 2022-08-18 /pmc/articles/PMC9433547/ /pubmed/36060541 http://dx.doi.org/10.3389/fdgth.2022.932599 Text en Copyright © 2022 Goodwin, Eytan, Dixon, Goodfellow, Doherty, Greer, McEwan, Tracy, Laussen, Assadi and Mazwi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Goodwin, Andrew J. Eytan, Danny Dixon, William Goodfellow, Sebastian D. Doherty, Zakary Greer, Robert W. McEwan, Alistair Tracy, Mark Laussen, Peter C. Assadi, Azadeh Mazwi, Mjaye Timing errors and temporal uncertainty in clinical databases—A narrative review |
title | Timing errors and temporal uncertainty in clinical databases—A narrative review |
title_full | Timing errors and temporal uncertainty in clinical databases—A narrative review |
title_fullStr | Timing errors and temporal uncertainty in clinical databases—A narrative review |
title_full_unstemmed | Timing errors and temporal uncertainty in clinical databases—A narrative review |
title_short | Timing errors and temporal uncertainty in clinical databases—A narrative review |
title_sort | timing errors and temporal uncertainty in clinical databases—a narrative review |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433547/ https://www.ncbi.nlm.nih.gov/pubmed/36060541 http://dx.doi.org/10.3389/fdgth.2022.932599 |
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