Cargando…
Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER)
OBJECTIVES: To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident. DESIGN: Observational, retrospective case–control study. SETTING: Nursing homes. PARTICIPANTS: A total of 1668 (824 in part...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098923/ https://www.ncbi.nlm.nih.gov/pubmed/33941626 http://dx.doi.org/10.1136/bmjopen-2020-042941 |
_version_ | 1783688502187130880 |
---|---|
author | Milosevic, Vanja Linkens, Aimee Winkens, Bjorn Hurkens, Kim P G M Wong, Dennis van Oijen, Brigit P C van der Kuy, Hugo M Mestres-Gonzalvo, Carlota |
author_facet | Milosevic, Vanja Linkens, Aimee Winkens, Bjorn Hurkens, Kim P G M Wong, Dennis van Oijen, Brigit P C van der Kuy, Hugo M Mestres-Gonzalvo, Carlota |
author_sort | Milosevic, Vanja |
collection | PubMed |
description | OBJECTIVES: To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident. DESIGN: Observational, retrospective case–control study. SETTING: Nursing homes. PARTICIPANTS: A total of 1668 (824 in part I, 844 in part II) NH-residents from the Netherlands were included. Data of participants from part I were excluded in part II. PRIMARY AND SECONDARY OUTCOME MEASURES: Development and validation of a fall risk CR in NH-residents. Logistic regression analysis was conducted to identify the fall risk-variables in part I. With these, three CRs were developed (ie, at the day of the fall incident and 3 days and 5 days prior to the fall incident). The overall prediction quality of the CRs were assessed using the area under the receiver operating characteristics (AUROC), and a cut-off value was determined for the predicted risk ensuring a sensitivity ≥0.85. Finally, one CR was chosen and validated in part II using a new retrospective data set. RESULTS: Eleven fall risk-variables were identified in part I. The AUROCs of the three CRs form part I were similar: the AUROC for models I, II and III were 0.714 (95% CI: 0.679 to 0.748), 0.715 (95% CI: 0.680 to 0.750) and 0.709 (95% CI: 0.674 to 0.744), respectively. Model III (ie, 5 days prior to the fall incident) was chosen for validation in part II. The validated AUROC of the CR, obtained in part II, was 0.603 (95% CI: 0.565 to 0.641) with a sensitivity of 83.41% (95% CI: 79.44% to 86.76%) and a specificity of 27.25% (95% CI 23.11% to 31.81%). CONCLUSION: Medication data and resident characteristics alone are not sufficient enough to develop a successful CR with a high sensitivity and specificity to predict fall risk in NH-residents. TRIAL REGISTRATION NUMBER: Not available. |
format | Online Article Text |
id | pubmed-8098923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-80989232021-05-18 Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) Milosevic, Vanja Linkens, Aimee Winkens, Bjorn Hurkens, Kim P G M Wong, Dennis van Oijen, Brigit P C van der Kuy, Hugo M Mestres-Gonzalvo, Carlota BMJ Open Pharmacology and Therapeutics OBJECTIVES: To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident. DESIGN: Observational, retrospective case–control study. SETTING: Nursing homes. PARTICIPANTS: A total of 1668 (824 in part I, 844 in part II) NH-residents from the Netherlands were included. Data of participants from part I were excluded in part II. PRIMARY AND SECONDARY OUTCOME MEASURES: Development and validation of a fall risk CR in NH-residents. Logistic regression analysis was conducted to identify the fall risk-variables in part I. With these, three CRs were developed (ie, at the day of the fall incident and 3 days and 5 days prior to the fall incident). The overall prediction quality of the CRs were assessed using the area under the receiver operating characteristics (AUROC), and a cut-off value was determined for the predicted risk ensuring a sensitivity ≥0.85. Finally, one CR was chosen and validated in part II using a new retrospective data set. RESULTS: Eleven fall risk-variables were identified in part I. The AUROCs of the three CRs form part I were similar: the AUROC for models I, II and III were 0.714 (95% CI: 0.679 to 0.748), 0.715 (95% CI: 0.680 to 0.750) and 0.709 (95% CI: 0.674 to 0.744), respectively. Model III (ie, 5 days prior to the fall incident) was chosen for validation in part II. The validated AUROC of the CR, obtained in part II, was 0.603 (95% CI: 0.565 to 0.641) with a sensitivity of 83.41% (95% CI: 79.44% to 86.76%) and a specificity of 27.25% (95% CI 23.11% to 31.81%). CONCLUSION: Medication data and resident characteristics alone are not sufficient enough to develop a successful CR with a high sensitivity and specificity to predict fall risk in NH-residents. TRIAL REGISTRATION NUMBER: Not available. BMJ Publishing Group 2021-05-03 /pmc/articles/PMC8098923/ /pubmed/33941626 http://dx.doi.org/10.1136/bmjopen-2020-042941 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Pharmacology and Therapeutics Milosevic, Vanja Linkens, Aimee Winkens, Bjorn Hurkens, Kim P G M Wong, Dennis van Oijen, Brigit P C van der Kuy, Hugo M Mestres-Gonzalvo, Carlota Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title | Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title_full | Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title_fullStr | Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title_full_unstemmed | Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title_short | Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER) |
title_sort | fall incidents in nursing home residents: development of a predictive clinical rule (finder) |
topic | Pharmacology and Therapeutics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098923/ https://www.ncbi.nlm.nih.gov/pubmed/33941626 http://dx.doi.org/10.1136/bmjopen-2020-042941 |
work_keys_str_mv | AT milosevicvanja fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT linkensaimee fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT winkensbjorn fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT hurkenskimpgm fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT wongdennis fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT vanoijenbrigitpc fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT vanderkuyhugom fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder AT mestresgonzalvocarlota fallincidentsinnursinghomeresidentsdevelopmentofapredictiveclinicalrulefinder |