Clinical decision support systems for chronic diseases: A Systematic literature review

Leonice Souza-Pereira, Nuno Pombo, Sofia Ouhbi, Virginie Felizardo, Nuno Garcia

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number105565
JournalComputer Methods and Programs in Biomedicine
Volume195
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Chronic disease
  • Clinical decision support systems
  • Software engineering

ASJC Scopus subject areas

  • Software
  • Health Informatics
  • Computer Science Applications

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