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Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations?
Advance care planning (ACP) facilitates end-of-life care, yet many die without it. Timely and accurate mortality prediction may encourage ACP. However, performance of predictors typically differs among sub-populations (e.g., rural vs. urban) and worsens over time (“concept drift”). Therefore, we ass...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317873/ https://www.ncbi.nlm.nih.gov/pubmed/37395923 http://dx.doi.org/10.1007/s10916-023-01962-z |
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author | Handler, Jonathan Lee, Olivia J. Chatrath, Sheena McGarvey, Jeremy Fitch, Tyler Jose, Divya Vozenilek, John |
author_facet | Handler, Jonathan Lee, Olivia J. Chatrath, Sheena McGarvey, Jeremy Fitch, Tyler Jose, Divya Vozenilek, John |
author_sort | Handler, Jonathan |
collection | PubMed |
description | Advance care planning (ACP) facilitates end-of-life care, yet many die without it. Timely and accurate mortality prediction may encourage ACP. However, performance of predictors typically differs among sub-populations (e.g., rural vs. urban) and worsens over time (“concept drift”). Therefore, we assessed performance equity and consistency for a novel 5-to-90-day mortality predictor across various demographies, geographies, and timeframes (n = 76,812 total encounters). Predictions were made for the first day of included adult inpatient admissions on a retrospective dataset. AUC-PR remained at 29% both pre-COVID (throughout 2018) and during COVID (8 months in 2021). Pre-COVID-19 recall and precision were 58% and 25% respectively at the 12.5% certainty cutoff, and 12% and 44% at the 37.5% cutoff. During COVID-19, recall and precision were 59% and 26% at the 12.5% cutoff, and 11% and 43% at the 37.5% cutoff. Pre-COVID, compared to the overall population, recall was lower at the 12.5% cutoff in the White, non-Hispanic subgroup and at both cutoffs in the rural subgroup. During COVID-19, precision at the 12.5% cutoff was lower than that of the overall population for the non-White and non-White female subgroups. No other significant differences were seen between subgroups and the corresponding overall population. Overall performance during COVID was unchanged from pre-pandemic performance. Although some comparisons (especially precision at the 37.5% cutoff) were underpowered, precision at the 12.5% cutoff was equitable across most demographies, regardless of the pandemic. Mortality prediction to prioritize ACP conversations can be provided consistently and equitably across many studied timeframes and sub-populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-023-01962-z. |
format | Online Article Text |
id | pubmed-10317873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-103178732023-07-05 Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? Handler, Jonathan Lee, Olivia J. Chatrath, Sheena McGarvey, Jeremy Fitch, Tyler Jose, Divya Vozenilek, John J Med Syst Original Paper Advance care planning (ACP) facilitates end-of-life care, yet many die without it. Timely and accurate mortality prediction may encourage ACP. However, performance of predictors typically differs among sub-populations (e.g., rural vs. urban) and worsens over time (“concept drift”). Therefore, we assessed performance equity and consistency for a novel 5-to-90-day mortality predictor across various demographies, geographies, and timeframes (n = 76,812 total encounters). Predictions were made for the first day of included adult inpatient admissions on a retrospective dataset. AUC-PR remained at 29% both pre-COVID (throughout 2018) and during COVID (8 months in 2021). Pre-COVID-19 recall and precision were 58% and 25% respectively at the 12.5% certainty cutoff, and 12% and 44% at the 37.5% cutoff. During COVID-19, recall and precision were 59% and 26% at the 12.5% cutoff, and 11% and 43% at the 37.5% cutoff. Pre-COVID, compared to the overall population, recall was lower at the 12.5% cutoff in the White, non-Hispanic subgroup and at both cutoffs in the rural subgroup. During COVID-19, precision at the 12.5% cutoff was lower than that of the overall population for the non-White and non-White female subgroups. No other significant differences were seen between subgroups and the corresponding overall population. Overall performance during COVID was unchanged from pre-pandemic performance. Although some comparisons (especially precision at the 37.5% cutoff) were underpowered, precision at the 12.5% cutoff was equitable across most demographies, regardless of the pandemic. Mortality prediction to prioritize ACP conversations can be provided consistently and equitably across many studied timeframes and sub-populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-023-01962-z. Springer US 2023-07-03 2023 /pmc/articles/PMC10317873/ /pubmed/37395923 http://dx.doi.org/10.1007/s10916-023-01962-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Handler, Jonathan Lee, Olivia J. Chatrath, Sheena McGarvey, Jeremy Fitch, Tyler Jose, Divya Vozenilek, John Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title | Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title_full | Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title_fullStr | Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title_full_unstemmed | Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title_short | Can a 5-to-90-day Mortality Predictor Perform Consistently Across Time and Equitably Across Populations? |
title_sort | can a 5-to-90-day mortality predictor perform consistently across time and equitably across populations? |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317873/ https://www.ncbi.nlm.nih.gov/pubmed/37395923 http://dx.doi.org/10.1007/s10916-023-01962-z |
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