| Use of and training about these systems |
Using CDSS in the NHS environment is burdensome because responsive hardware is unavailable. CDSS may inhibit junior doctor decisions with atypical cases, and will have training implications. The interface for CDSS varies too much, which has training and safety implications. Low-quality and erroneous inputs will result in authoritative but misleading advice outputs.
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| Clinical governance and CDSS |
CDSS need to be continuously reviewed and updated by an expert team including EPR clinicians, pharmacists, nurses and medical informaticians or a responsible group of professionals or specialty society to ensure safe evidence-based practice. To minimise alert fatigue, CDSS alert threshold levels need to be targeted to high-risk errors. It is important for organisations to be in contact with CDSS suppliers so suppliers can update the software if necessary. Need to apply clinical governance processes, eg an audit trial to allow effectiveness and impact to be assessed.
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| Regulation and evaluation of CDSS |
Regulation has been too lax compared to drugs, especially where high-risk decisions are being supported. Standards for testing these systems, and the results of these tests, should be peer reviewed and openly available eg in a register of tested CDSS and their test results with easily understood explanations of their reliability and validity. The feasibility and rigour of regulation and testing of AI depends on user and setting. Patient-used devices with embedded AI could be disruptive to the NHS if not sufficiently specific eg they could overload dermatologists with suspected melanoma. Need for an NHS-approved list of apps and AI for the public and professionals to avert chaos.
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