Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
Department of Health Information Management and Medical Informatics, School of Health Management and Information Science, Iran University of Medical Sciences, Tehran, Iran.
BMC Nephrol. 2022 Jun 21;23(1):219. doi: 10.1186/s12882-022-02841-4.
Prediction of graft survival for Kidney Transplantation (KT) is considered a risky task due to the scarcity of donating organs and the use of health care resources. The present study aimed to design and evaluate a smartphone-based application to predict the survival of KT in patients with End-Stage Renal Disease (ESRD).
Based on the initial review, a researcher-made questionnaire was developed to assess the information needs of the application through urologists and nephrologists. By using information obtained from the questionnaire, a checklist was prepared, and the information of 513 patients with kidney failure was collected from their records at Sina Urological Research Center. Then, three data mining algorithms were applied to them. The smartphone-based application for the prediction of kidney transplant survival was designed, and a standard usability assessment questionnaire was used to evaluate the designed application.
Three information elements related to the required data in different sections of demographic information, sixteen information elements related to patient clinical information, and four critical capabilities were determined for the design of the smartphone-based application. C5.0 algorithm with the highest accuracy (87.21%) was modeled as the application inference engine. The application was developed based on the PhoneGap framework. According to the participants' scores (urologists and nephrologists) regarding the usability evaluation of the application, it can be concluded that both groups participating in the study could use the program, and they rated the application at a "good" level.
Since the overall performance or usability of the smartphone-based app was evaluated at a reasonable level, it can be used with certainty to predict kidney transplant survival.
由于捐赠器官的稀缺性和医疗资源的使用，预测肾移植（KT）的移植物存活率被认为是一项风险任务。本研究旨在设计和评估一种基于智能手机的应用程序，以预测终末期肾病（ESRD）患者 KT 的存活率。
基于初步审查，研究人员制作了一份问卷，通过泌尿科医生和肾病学家评估应用程序的信息需求。通过使用从问卷中获得的信息，编制了一份清单，并从 Sina 泌尿科研究中心的记录中收集了 513 名肾衰竭患者的信息。然后，将三种数据挖掘算法应用于这些患者。设计了一种基于智能手机的预测肾移植存活率的应用程序，并使用标准的可用性评估问卷对设计的应用程序进行了评估。
确定了三个与人口统计学信息不同部分所需数据相关的信息元素、与患者临床信息相关的十六个信息元素以及四个与设计基于智能手机的应用程序相关的关键功能。C5.0 算法以最高的准确性（87.21%）被建模为应用程序推理引擎。该应用程序是基于 PhoneGap 框架开发的。根据参与者（泌尿科医生和肾病学家）对应用程序可用性评估的评分，可以得出结论，参与研究的两组人员都可以使用该程序，他们将应用程序评为“良好”水平。
由于智能手机应用程序的整体性能或可用性评估达到了合理的水平，因此可以肯定地用于预测肾移植的存活率。
