JMIR Publications

ABSTRACT

Background:

Integrating algorithm-based clinical decision support (CDS) systems poses significant challenges in evaluating their actual clinical value. Such CDS systems are traditionally assessed via controlled but resource-intensive clinical trials.

Objective:

This paper presents a review protocol for pre-implementation in silico evaluation methods to enable broadened impact analysis under simulated environments before clinical trials.

Methods:

We propose a scoping review protocol that follows an enhanced Arksey and O’Malley framework and PRISMA-ScR guidelines to investigate the scope and research gaps in the in silico evaluation of algorithm-based CDS models—specifically CDS decision-making endpoints and objectives, evaluation metrics used, and simulation paradigms employed to assess potential impacts.

Results:

The databases searched are PubMed, Embase, CINAHL, PsycInfo, Cochrane, IEEEXplore, Web of Science, and arXiv. A two-stage screening process identified pertinent articles. The information extracted from articles is iteratively refined. The review will employ thematic, trend, and descriptive analyses to meet scoping aims.

Conclusions:

The study’s findings will be published and presented in forums combining artificial intelligence and machine learning, clinical decision-making, and health technology impact analysis; ultimately, we aim to bridge the development-deployment gap through in silico evaluation-based potential impact assessments.