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. Objective: 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. Methods: 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. Results: 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%). Conclusion: 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进行与患者临床状况有关的决策。CDSS处理相关的关键数据，在设计时应格外小心，以确保开发可用，安全和可靠的工具。目的：本文旨在研究有关CDSS的开发过程以监测慢性病，分析其功能和特性以及其设计中的软件工程表示形式的现有文献。方法：进行系统的文献综述（SLR），以分析用于监测慢性疾病的CDSS文献，并在其设计中应用软件工程技术。结果： 14项包括研究在内的研究表明，最受关注的疾病是糖尿病（42.8％），最常用的方法是诊断性（85.7％）。在数据来源方面，研究表明，数据库的使用占主要地位（85.7％），传感器（42.8％）和自我报告（28.6％）等其他数据来源也被考虑在内。通过分析工程技术的表示，我们发现行为图（42.8％）是最常见的，紧随其后的是结构图（35.7％）和其他（78.6％）。一些研究也达到了要求规格（21.4％）。最常见的目标评估是系统的性能（64.2％），最常见的指标是准确性（57.1％）。结论：我们得出的结论是，软件工程的完整性在针对慢性疾病CDSS的研究中几乎没有代表。