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报告一家国家级精神病院住院患者的体验与满意度:一项基于随机森林算法的研究

Reporting Inpatients' Experiences and Satisfaction in a National Psychiatric Facility: A Study Based on the Random Forest Algorithm.

作者信息

Haji Eman A, Ebrahim Ahmed H, Fardan Hassan, Jahrami Haitham

机构信息

Ministry of Health, Manama, Kingdom of Bahrain.

College of Graduate Studies and Research, Ahlia University, Manama, Kingdom of Bahrain.

出版信息

J Patient Exp. 2022 Jan 4;9:23743735211069819. doi: 10.1177/23743735211069819. eCollection 2022.

DOI:10.1177/23743735211069819
PMID:35005221
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8733350/
Abstract

Understanding psychiatric inpatients' experiences is important to establish a culture of patient-centric care and promote trust in healthcare. This study aimed to evaluate nine dimensions of patients' experiences and investigate their association with patient satisfaction, revisit intention, and positive word-of-mouth (WoM) recommendation. Cross-sectional questionnaire data from five years of surveying (2016-2020) in the main psychiatric hospital in Bahrain were statistically analyzed, involving 763 psychiatric inpatients with an overall 65.6 ± 17.2 length of stay (days). The findings show that across the five years 2016-2020, the overall reported satisfaction was "very high" (4.75 ± 0.44) with no significant differences between these five years (F [4, 758] = 0.66,  = 0.620). The experience of confidentiality received the highest rating (4.72 ± 0.45). The experiences of ease of access, hospitality quality, and quality of responsiveness to one's needs significantly correlated with revisit intention ( ˂ 0.05). Patients with high satisfaction had greater potential for revisit intention (r [761] = 0.08,  = 0.027), which was associated with WoM recommendation (r [761] = 0.08,  = 0.033). Overall, men were less likely than women to experience convenient access to psychiatric wards. The findings of the Random Forest algorithm indicate the tendency of female patients with short-term stays to demonstrate lower satisfaction rates, and thus innovative approaches are needed when managing these groups' psychiatric problems.

摘要

了解精神科住院患者的经历对于建立以患者为中心的护理文化和促进对医疗保健的信任非常重要。本研究旨在评估患者经历的九个维度,并调查它们与患者满意度、回访意愿和积极口碑推荐之间的关联。对巴林主要精神病医院五年(2016 - 2020年)调查的横断面问卷数据进行了统计分析,涉及763名精神科住院患者,平均住院时间为65.6±17.2天。研究结果表明,在2016 - 2020年这五年间,总体报告的满意度为“非常高”(4.75±0.44),这五年间无显著差异(F[4, 758] = 0.66,P = 0.620)。保密性体验获得了最高评分(4.72±0.45)。就医便利性、接待质量和对需求的响应质量体验与回访意愿显著相关(P<0.05)。高满意度患者有更大的回访意愿可能性(r[761] = 0.08,P = 0.027),这与口碑推荐相关(r[761] = 0.08,P = 0.033)。总体而言,男性比女性更难方便地进入精神科病房。随机森林算法的结果表明,短期住院的女性患者有满意度较低的趋势,因此在管理这些群体的精神问题时需要创新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f73/8733350/e829ba602295/10.1177_23743735211069819-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f73/8733350/e829ba602295/10.1177_23743735211069819-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f73/8733350/e829ba602295/10.1177_23743735211069819-fig1.jpg

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Exploring drivers of patient satisfaction using a random forest algorithm.使用随机森林算法探索患者满意度的驱动因素。
BMC Med Inform Decis Mak. 2021 May 13;21(1):157. doi: 10.1186/s12911-021-01519-5.
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Effective Analysis of Inpatient Satisfaction: The Random Forest Algorithm.住院患者满意度的有效分析:随机森林算法
Heliyon. 2023 Mar 23;9(4):e14744. doi: 10.1016/j.heliyon.2023.e14744. eCollection 2023 Apr.
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J Patient Exp. 2020 Dec;7(6):1642-1647. doi: 10.1177/2374373520967807. Epub 2020 Oct 21.
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