Diagnosing, Managing, and Controlling COVID-19 using Clinical Decision Support Systems: A Study to Introduce CDSS Applications

Area of Science:

• Medical Informatics
• Infectious Diseases
• Health Information Management

Background:

• Coronavirus disease (COVID-19) poses a significant global health security threat.
• Effective management and control strategies are crucial to mitigate disease spread and impact.
• Clinical Decision Support Systems (CDSS) offer potential solutions for improving COVID-19 response.

Purpose of the Study:

• To identify and introduce the applications of CDSS in the diagnosis, management, and control of COVID-19.
• To explore how CDSS can enhance security and reduce the impact of emerging infectious diseases.
• To provide foundational knowledge for designing and implementing CDSS in real-world healthcare settings.

Main Methods:

• A cross-sectional study design was employed.
• Literature review and expert consultations informed the study.
• A two-round Delphi method involving 19 experts was used to achieve consensus on CDSS applications.

Main Results:

• 35 potential CDSS applications were identified across diagnosis, medication, monitoring, and health services.
• Consensus was reached on 30 CDSS applications through the Delphi method.
• Top-rated applications included "monitoring vital signs" and "CT scan analysis for infection diagnosis."

Conclusions:

• CDSS have a vital role in the diagnosis, management, and control of COVID-19.
• Implementing identified CDSS applications can prevent severe complications and fatalities.
• This research provides essential insights for the practical design and deployment of CDSS in infectious disease management.