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Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application

The aim was to explore the effectiveness of a tracing methodology combined with failure mode and effect analysis (FMEA) for managing falls in pregnant women during the perioperative period of interventional prenatal diagnosis. Using the tracing methodology, the process was evaluated and analyzed usi...

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Autores principales: Yang, Hao, Luo, Wanying, Guo, Liping, Zhu, Hui, Peng, Wentao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627635/
https://www.ncbi.nlm.nih.gov/pubmed/37933047
http://dx.doi.org/10.1097/MD.0000000000035477
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author Yang, Hao
Luo, Wanying
Guo, Liping
Zhu, Hui
Peng, Wentao
author_facet Yang, Hao
Luo, Wanying
Guo, Liping
Zhu, Hui
Peng, Wentao
author_sort Yang, Hao
collection PubMed
description The aim was to explore the effectiveness of a tracing methodology combined with failure mode and effect analysis (FMEA) for managing falls in pregnant women during the perioperative period of interventional prenatal diagnosis. Using the tracing methodology, the process was evaluated and analyzed using FMEA after reviewing data, on-site interview, case tracking and on-site inspection, and improvement measures were proposed for the existing risk factors, and the fall-related quality indicators, satisfaction with fall-related health education, and risk priority number were compared before and after implementation. Effectiveness analysis for interventional prenatal diagnosis of perioperative maternal falls risk management resulted in a significant decrease in risk priority number (P < .01), a significant increase in the rate of correct fall risk identification and assessment, correct handover rate of pregnant women at risk of falls, correct intervention rate of pregnant women at high risk of falls, and effective coverage of falls-related health education (P < .01), a significant increase in satisfaction with falls-related health education (P < .001), and the incidence of falls among pregnant women decreased from 0.12% to 0%. The use of tracking methodology combined with FMEA can reduce the risk of perioperative maternal falls in interventional prenatal diagnosis and improve the safety of maternal visits.
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spelling pubmed-106276352023-11-07 Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application Yang, Hao Luo, Wanying Guo, Liping Zhu, Hui Peng, Wentao Medicine (Baltimore) 6600 The aim was to explore the effectiveness of a tracing methodology combined with failure mode and effect analysis (FMEA) for managing falls in pregnant women during the perioperative period of interventional prenatal diagnosis. Using the tracing methodology, the process was evaluated and analyzed using FMEA after reviewing data, on-site interview, case tracking and on-site inspection, and improvement measures were proposed for the existing risk factors, and the fall-related quality indicators, satisfaction with fall-related health education, and risk priority number were compared before and after implementation. Effectiveness analysis for interventional prenatal diagnosis of perioperative maternal falls risk management resulted in a significant decrease in risk priority number (P < .01), a significant increase in the rate of correct fall risk identification and assessment, correct handover rate of pregnant women at risk of falls, correct intervention rate of pregnant women at high risk of falls, and effective coverage of falls-related health education (P < .01), a significant increase in satisfaction with falls-related health education (P < .001), and the incidence of falls among pregnant women decreased from 0.12% to 0%. The use of tracking methodology combined with FMEA can reduce the risk of perioperative maternal falls in interventional prenatal diagnosis and improve the safety of maternal visits. Lippincott Williams & Wilkins 2023-11-03 /pmc/articles/PMC10627635/ /pubmed/37933047 http://dx.doi.org/10.1097/MD.0000000000035477 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 6600
Yang, Hao
Luo, Wanying
Guo, Liping
Zhu, Hui
Peng, Wentao
Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title_full Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title_fullStr Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title_full_unstemmed Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title_short Fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
title_sort fall risk management in interventional prenatal diagnosis perioperative pregnant women based on tracking methodology and failure mode and effect analysis application
topic 6600
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627635/
https://www.ncbi.nlm.nih.gov/pubmed/37933047
http://dx.doi.org/10.1097/MD.0000000000035477
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