Time to evaluate decision support systems for antimicrobial prescribing outside the hospital

• Published in: The Lancet infectious diseases Vol. 22; no. 10; pp. 1408 - 1409
• Main Author: Delory, Tristan
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.10.2022; Elsevier Limited
• Subjects: Antibiotics; Antiinfectives and antibacterials; Antimicrobial agents; Artificial intelligence; Bacterial infections; Clusters; Comment; Contamination; Cost analysis; Decision support systems; Electronic health records; Electronic medical records; Hospitals; Infectious diseases; Intervention
• ISSN: 1473-3099; 1474-4457; 1474-4457
• DOI: 10.1016/S1473-3099(22)00356-5

[...]the data from the Lugano and Bellinzona hospitals, which were naive sites, are interesting because they provide external validation to the trial. [...]these designs are logistically and analytically complex, costly, and potentially subject to numerous biases.8 As cluster size increases, these trials have diminishing returns in power and precision, and to increase trial efficiency, the number and size of the cluster should be determined simultaneously, not independently. Because of the absence of allocation concealment, contamination can occur, and the effect of the intervention is likely to be influenced by the amount of adoption of the intervention at the cluster level. [...]real-world data at the individual level could be used to emulate target trials to produce real-world evidence.9 Future improvements of CDSSs in the hospital setting will come from integrating individual level laboratory and microbiological data, and possibly personal medical history through electronic health records, to personalise CDSS-derived recommendations in complex cases of infection.