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External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients
PURPOSE: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. METHODS:...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9686262/ https://www.ncbi.nlm.nih.gov/pubmed/36422821 http://dx.doi.org/10.1007/s41999-022-00719-0 |
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author | Damoiseaux-Volman, Birgit A. van Schoor, Natasja M. Medlock, Stephanie Romijn, Johannes A. van der Velde, Nathalie Abu-Hanna, Ameen |
author_facet | Damoiseaux-Volman, Birgit A. van Schoor, Natasja M. Medlock, Stephanie Romijn, Johannes A. van der Velde, Nathalie Abu-Hanna, Ameen |
author_sort | Damoiseaux-Volman, Birgit A. |
collection | PubMed |
description | PURPOSE: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. METHODS: We used an Electronic Health Records (EHR) dataset with hospitalized patients (≥ 70), admitted for ≥ 24 h between 2016 and 2021. Inpatient falls were extracted from structured and free-text data. We assessed the association between JHFRAT and falls using logistic regression. For test accuracy, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was measured by the AUC. For calibration, we plotted the predicted fall probability with the actual probability of falls. For time-related effects, we calculated the AUC per 6 months (using data of patients admitted during the 6 months’ time interval) and plotted these different AUC values over time. Furthermore, we compared the model (JHFRAT and falls) with and without adjusting for seasonal influenza, COVID-19, spring, summer, fall or winter periods. RESULTS: Data included 17,263 admissions with at least 1 JHFRAT measurement, a median age of 76 and a percentage female of 47%. The in-hospital fall prevalence was 2.5%. JHFRAT [OR = 1.11 (1.03–1.20)] and its subcategories were significantly associated with falls. For medium/high risk of falls (JHFRAT > 5), sensitivity was 73%, specificity 51%, PPV 4% and NPV 99%. The overall AUC was 0.67, varying over time between 0.62 and 0.71 (for 6 months’ time intervals). Seasonal influenza did affect the association between JHFRAT and falls. COVID-19, spring, summer, fall or winter did not affect the association. CONCLUSIONS: Our results show an association between JHFRAT and falls, a low discrimination by JHFRAT for older inpatients and over-prediction in the calibration. Improvements in the fall-risk assessment are warranted to improve efficiency. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41999-022-00719-0. |
format | Online Article Text |
id | pubmed-9686262 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-96862622022-11-28 External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients Damoiseaux-Volman, Birgit A. van Schoor, Natasja M. Medlock, Stephanie Romijn, Johannes A. van der Velde, Nathalie Abu-Hanna, Ameen Eur Geriatr Med Research Paper PURPOSE: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. METHODS: We used an Electronic Health Records (EHR) dataset with hospitalized patients (≥ 70), admitted for ≥ 24 h between 2016 and 2021. Inpatient falls were extracted from structured and free-text data. We assessed the association between JHFRAT and falls using logistic regression. For test accuracy, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was measured by the AUC. For calibration, we plotted the predicted fall probability with the actual probability of falls. For time-related effects, we calculated the AUC per 6 months (using data of patients admitted during the 6 months’ time interval) and plotted these different AUC values over time. Furthermore, we compared the model (JHFRAT and falls) with and without adjusting for seasonal influenza, COVID-19, spring, summer, fall or winter periods. RESULTS: Data included 17,263 admissions with at least 1 JHFRAT measurement, a median age of 76 and a percentage female of 47%. The in-hospital fall prevalence was 2.5%. JHFRAT [OR = 1.11 (1.03–1.20)] and its subcategories were significantly associated with falls. For medium/high risk of falls (JHFRAT > 5), sensitivity was 73%, specificity 51%, PPV 4% and NPV 99%. The overall AUC was 0.67, varying over time between 0.62 and 0.71 (for 6 months’ time intervals). Seasonal influenza did affect the association between JHFRAT and falls. COVID-19, spring, summer, fall or winter did not affect the association. CONCLUSIONS: Our results show an association between JHFRAT and falls, a low discrimination by JHFRAT for older inpatients and over-prediction in the calibration. Improvements in the fall-risk assessment are warranted to improve efficiency. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41999-022-00719-0. Springer International Publishing 2022-11-23 2023 /pmc/articles/PMC9686262/ /pubmed/36422821 http://dx.doi.org/10.1007/s41999-022-00719-0 Text en © The Author(s), under exclusive licence to European Geriatric Medicine Society 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Paper Damoiseaux-Volman, Birgit A. van Schoor, Natasja M. Medlock, Stephanie Romijn, Johannes A. van der Velde, Nathalie Abu-Hanna, Ameen External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title | External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title_full | External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title_fullStr | External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title_full_unstemmed | External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title_short | External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients |
title_sort | external validation of the johns hopkins fall risk assessment tool in older dutch hospitalized patients |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9686262/ https://www.ncbi.nlm.nih.gov/pubmed/36422821 http://dx.doi.org/10.1007/s41999-022-00719-0 |
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