Related Experiment Video
Updated: Oct 29, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Replication studies in the clinical decision support literature-frequency, fidelity, and impact
Enrico Coiera1, Huong Ly Tong1
1Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Objective:
To assess the frequency, fidelity, and impact of replication studies in the clinical decision support system (CDSS) literature.
Materials And Methods:
A PRISMA-compliant review identified CDSS replications across 28 health and biomedical informatics journals. Included articles were assessed for fidelity to the original study using 5 categories: Identical, Substitutable, In-class, Augmented, and Out-of-class; and 7 IMPISCO domains: Investigators (I), Method (M), Population (P), Intervention (I), Setting (S), Comparator (C), and Outcome (O). A fidelity score and heat map were generated using the ratings.
Results:
From 4063 publications matching search criteria for CDSS research, only 12/4063 (0.3%) were ultimately identified as replications. Six articles replicated but could not reproduce the results of the Han et al (2005) CPOE study showing mortality increase and, over time, changed from truth testing to generalizing this result. Other replications successfully tested variants of CDSS technology (2/12) or validated measurement instruments (4/12).
Discussion:
A replication rate of 3 in a thousand studies is low even by the low rates in other disciplines. Several new reporting methods were developed for this study, including the IMPISCO framework, fidelity scores, and fidelity heat maps. A reporting structure for clearly identifying replication research is also proposed.
Conclusion:
There is an urgent need to better characterize which core CDSS principles require replication, identify past replication data, and conduct missing replication studies. Attention to replication should improve the efficiency and effectiveness of CDSS research and avoiding potentially harmful trial and error technology deployment.
More Related Videos
18:10Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Published on: June 16, 2011
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Comparing Copy Number Variations and SNPs
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Clinical Trials
There are four phases in a clinical trial. A phase one...
Statistical Software for Data Analysis and Clinical Trials
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Therapeutic Drug Monitoring: Affecting Factors