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首页> 外文期刊>Artificial intelligence in medicine >Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax
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Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax

机译:使用Arden语法评估可移动健康支持的临床决策支持系统在肿瘤门诊中进行营养分类的可行性

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BackgroundNutritional screening procedures followed by regular nutrition monitoring for oncological outpatients are no standard practice in many European hospital wards and outpatient settings. As a result, early signs of malnutrition are missed and nutritional treatment is initiated when patients have already experienced severe weight loss.ObjectiveWe report on a novel clinical decision support system (CDSS) for the global assessment and nutritional triage of the nutritional condition of oncology outpatients. The system combines clinical and laboratory data collected in the clinical setting with patient-generated data from a smartphone application for monitoring the patients’ nutritional status. Our objective is to assess the feasibility of a CDSS that combines the aforementioned data sources and describe its integration into a hospital information system. Furthermore, we collected patients’ opinions on the value of the system, and whether they would regard the system as a useful aid in coping with their condition.Materials and methodsThe system implements the Patient-Generated Subjective Global Assessment (PG-SGA) to monitor nutritional status in the outpatient setting. A smartphone application is used to collect patient-generated data by performing weekly mini-surveys on patients concerning their eating habits, weight, and overall well-being. Data are uploaded on completion of each mini-survey and stored on a secure server at the Medical University of Vienna (MUV). The data are then combined with relevant clinical information from the Vienna General Hospital (VGH) information system. The knowledge base for the CDSS is implemented in medical logic modules (MLMs) using Arden Syntax. A three-month pilot clinical trial was performed to test the feasibility of the system. Qualitative questionnaires were used to obtain the patients’ opinions on the usability and personal value of the system during the four-week test period.ResultsWe used the existing separation between the scientific and clinical data domains in the secured network environment (SNE) at the MUV and VGH to our advantage by importing, storing, and processing both patient-generated and routine data in the scientific data domain. To limit exposure to the SNE, patient-generated data stored outside the SNE were imported to the scientific domain once a day. The CDSS created for nutritional assessment and triage comprised ten MLMs, each including either a sub-assessment or the final results of the PG-SGA. Finally, an interface created for the hospital information system showed the results directly in clinical routine. In all 22 patients completed the clinical study. The results of the questionnaires showed that 91% of the patients were generally happy with the usability of the system, 91% believed that the application was of additional value in detecting cancer-related malnutrition, and 82% found it helpful as a long-term monitoring tool.Discussion and conclusionDespite strict protection of the clinical data domain, a CDSS employing patient-generated data can be integrated into clinical routine. The CDSS discussed in this report combined the information entered into a smartphone application with clinical data in order to inform the physician of a patient's nutritional status and thus permit suitable and timely intervention. The initial results show that the smartphone application was well accepted by patients, who considered it useful, but not many oncological outpatients were willing to participate in the clinical study because they did not possess an Android phone or lacked smartphone expertise. Furthermore, the results indicate that patient-generated data could be employed to augment clinical data and calculate metrics such as the PG-SGA without excessive effort by using a secure intermediate location as the locus of data storage and processing.
机译:背景技术在许多欧洲医院的病房和门诊患者中,营养筛查程序以及定期对肿瘤科门诊病人进行营养监测并不是标准做法。因此,当患者已经严重体重减轻时,就会错过营养不良的早期迹象,并开始进行营养治疗。目的我们报告一种新型临床决策支持系统(CDSS),用于肿瘤门诊患者营养状况的全球评估和营养分类。该系统将在临床环境中收集的临床和实验室数据与从智能手机应用程序生成的患者生成的数据结合在一起,以监控患者的营养状况。我们的目标是评估结合上述数据源的CDSS的可行性,并描述将其集成到医院信息系统中的可能性。此外,我们收集了患者对系统价值的意见,以及他们是否认为该系统对应对病情有用。材料和方法该系统实施患者生成的主观全局评估(PG-SGA)进行监控门诊环境中的营养状况。智能手机应用程序用于通过每周对患者进行有关他们的饮食习惯,体重和整体健康状况的小型调查来收集患者生成的数据。每次完成小型调查后,都会上载数据,并将其存储在维也纳医科大学(MUV)的安全服务器上。然后将数据与来自维也纳总医院(VGH)信息系统的相关临床信息相结合。 CDSS的知识库是使用Arden语法在医学逻辑模块(MLM)中实现的。进行了为期三个月的临床试验,以测试该系统的可行性。在四个星期的测试期间内,使用定性问卷来获取患者对系统可用性和个人价值的意见。结果我们在MUV的安全网络环境(SNE)中使用了现有的科学和临床数据域之间的隔离VGH通过在科学数据领域导入,存储和处理患者生成的数据和常规数据来发挥我们的优势。为了限制接触SNE,每天将患者存储在SNE外部的数据导入科学领域。为营养评估和分类而创建的CDSS包含十个MLM,每个MLM都包括PG-SGA的子评估或最终结果。最后,为医院信息系统创建的界面直接在临床常规中显示结果。全部22例患者均完成了临床研究。问卷调查结果显示,总体上,有91%的患者对系统的可用性感到满意; 91%的患者认为,该应用程序对于检测与癌症相关的营养不良具有附加价值; 82%的患者长期来看对系统有帮助讨论和结论尽管对临床数据域进行了严格保护,但使用患者生成数据的CDSS可以集成到临床程序中。本报告中讨论的CDSS将输入到智能手机应用程序中的信息与临床数据结合起来,以便告知医生患者的营养状况,从而可以进行适当及时的干预。初步结果表明,智能手机应用程序已被患者广泛接受,认为这是有用的,但由于没有Android手机或缺乏智能手机专业知识,很少有肿瘤门诊患者愿意参加临床研究。此外,结果表明,通过使用安全的中间位置作为数据存储和处理的场所,可以将患者生成的数据用于增强临床数据并计算指标(例如PG-SGA)而无需付出过多的努力。

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