Souza-Pereira Leonice, Pombo Nuno, Ouhbi Sofia, Felizardo Virginie, Garcia Nuno
Instituto Federal do Triângulo Mineiro - Campus Uberlândia Centro, Brasil; Instituto de Telecomunicações, Lisboa, Portugal; Universidade da Beira Interior, Covilhã, Portugal.
Instituto de Telecomunicações, Lisboa, Portugal; Universidade da Beira Interior, Covilhã, Portugal.
Comput Methods Programs Biomed. 2020 Oct;195:105565. doi: 10.1016/j.cmpb.2020.105565. Epub 2020 May 23.
A Clinical Decision Support System (CDSS) aims to assist physicians, nurses and other professionals in decision-making related to the patient's clinical condition. CDSSs deal with pertinent and critical data, and special care should be taken in their design to ensure the development of usable, secure and reliable tools.
This paper aims to investigate existing literature dealing with the development process of CDSSs for monitoring chronic diseases, analysing their functionalities and characteristics, and the software engineering representation in their design.
A systematic literature review (SLR) is conducted to analyse the literature on CDSSs for monitoring chronic diseases and the application of software engineering techniques in their design.
Fourteen included studies revealed that the most addressed disease was diabetes (42.8%) and the most commonly proposed approach was diagnostic (85.7%). Regarding data sources, the studies show a predominance on the use of databases (85.7%), with other data sources such as sensors (42.8%) and self-report (28.6%) also being considered. Analysing the representation for engineering techniques, we found Behaviour diagrams (42.8%) to be the most frequent, closely followed by Structural diagrams (35.7%) and others (78.6%) being largely mentioned. Some studies also approached the requirement specification (21.4%). The most common target evaluation was the performance of the system (64.2%) and the most common metric was accuracy (57.1%).
We conclude that software engineering, in its completeness, has scarce representation in studies focused on the development of CDSSs for chronic diseases.
临床决策支持系统（CDSS）旨在协助医生、护士和其他专业人员做出与患者临床状况相关的决策。CDSS处理相关且关键的数据，在其设计过程中应特别注意，以确保开发出可用、安全且可靠的工具。
本文旨在研究有关用于监测慢性病的CDSS开发过程的现有文献，分析其功能和特性，以及其设计中的软件工程表示。
进行系统的文献综述（SLR），以分析有关用于监测慢性病的CDSS的文献以及软件工程技术在其设计中的应用。
纳入的14项研究表明，提及最多的疾病是糖尿病（42.8%），最常提出的方法是诊断（85.7%）。关于数据来源，研究表明数据库的使用占主导地位（85.7%），其他数据来源如传感器（42.8%）和自我报告（28.6%）也被考虑在内。分析工程技术的表示，我们发现行为图（42.8%）最为常见，其次是结构图（35.7%），其他（78.6%）也被大量提及。一些研究还涉及需求规格说明（21.4%）。最常见的目标评估是系统性能（64.2%），最常见的指标是准确性（57.1%）。
我们得出结论，在专注于慢性病CDSS开发的研究中，软件工程的完整呈现较少。
