Saadah Loai M, Alnatour Dalal B, Hadidi Mumen S, Samara Fadia F, Shakhshir Sana S, Alnsour Wafa'a M, Saket Maisa K
Department of Clinical Pharmacy, Faculty of Pharmacy, Applied Science Private University.
Patient Protection Coalition, Amman, Jordan.
J Patient Saf. 2025 Aug 1;21(5):317-323. doi: 10.1097/PTS.0000000000001326. Epub 2025 Feb 17.
High-quality universal health care coverage for all patients is the common theme in patient rights. However, pertinent investigations on this topic within the context of Jordanian health care are absent. This systematic review, coupled with a pooled artificial intelligence analysis of the data in retrieved studies, paves the way for such research by pooling data sets sourced from across the Middle East and North Africa (MENA) region.
National Library of Medicine (NLM), through its secondary database of primary literature (PubMed), was queried with the terms "Patient" and "Rights" in April 2024. Quantitative surveys from MENA containing individual item assessments mapped to 1 of the 7 domains of Jordan National Patient Rights Charter were pooled. Finally, factors extracted for all studies were then used to build an artificial neural network (ANN) to test the hypothesis that information asymmetry in both awareness and practice of patient rights exist even among health care providers.
A total of 8 studies with 131 survey items were identified in the MENA region. All items tested either knowledge (awareness) or practice (implementation) of respondents regards patient rights except for 25 items in one study which measured both. ANN converged to a best net of multilayer feedforward with 3 hidden nodes. Patient right domain, from Jordanian Patient Rights Charter, ranked first and respondent type second as most important among the variables. However, there was huge and statistically significant asymmetry between students 0.602 (0.499 to 0.853), patients 0.627 (0.518 to 0.636), and nurses 0.492 (0.340 to 0.786) on one side and clinicians 1.166 (1.025 to 1.258) on the other side in the ANN model (both paired t test and Wilcoxon signed rank test P <0.0001) for any pairwise comparisons.
Jordan National Patient Charter can fit any patient right item one could think of in the infinite space of patient rights. Huge information asymmetry exists in both awareness and implementation between practicing professionals and society but also among the different health professions.
为所有患者提供高质量的全民医疗覆盖是患者权利的共同主题。然而,在约旦医疗保健背景下,缺乏关于这一主题的相关调查。本系统综述,结合对检索研究中的数据进行的汇总人工智能分析,通过汇总来自中东和北非(MENA)地区的数据集,为这类研究铺平了道路。
2024年4月,通过国家医学图书馆(NLM)的原始文献二级数据库(PubMed),以“患者”和“权利”为关键词进行查询。汇总了来自中东和北非地区的定量调查,这些调查包含映射到约旦国家患者权利宪章7个领域之一的单项评估。最后,从所有研究中提取的因素被用于构建一个人工神经网络(ANN),以检验以下假设:即使在医疗保健提供者中,患者权利的认知和实践中也存在信息不对称。
在中东和北非地区共确定了8项研究,包含131个调查项目。除一项研究中的25个项目同时测量了受访者对患者权利的知识(认知)和实践(实施)外,所有项目均测试了受访者对患者权利的知识(认知)或实践(实施)。人工神经网络收敛到一个具有3个隐藏节点的多层前馈最佳网络。在变量中,约旦患者权利宪章中的患者权利领域排名第一,受访者类型排名第二。然而,在人工神经网络模型中,学生0.602(0.499至0.853)、患者0.627(0.518至0.636)和护士0.492(0.340至0.786)与临床医生1.166(1.025至1.258)之间存在巨大且具有统计学意义的不对称(配对t检验和Wilcoxon符号秩检验P<0.0001),适用于任何成对比较。
约旦国家患者宪章可以涵盖在患者权利的无限空间中人们能想到的任何患者权利项目。在执业专业人员与社会之间以及不同医疗专业之间,在认知和实施方面都存在巨大的信息不对称。