Questionnaire about clinical decision support systems

Thank you for completing this form.
There is considerable concern and activity around the NHS and Government about the safety and impact of medical algorithms, AI, machine learning black boxes and clinical decision support systems (CDSS). For example, NHS England has developed its Code of Conduct on the procurement and use of these tools, several recent reports have both advocated greater use of AI in healthcare and discussed the potential risks, and Sir Mark Walport organised a cross-government workshop on this topic in 2018.

To ensure that the MHRA, NICE, the NHSX AI lab and others – as well as CDSS developers – are properly briefed about these issues, we are giving you an opportunity to share your experience (both benefits and harms) with AI, machine learning etc. This will help the FCI formulate its position on the NHS England Code of Conduct, the MHRA’s approach to regulating these systems, etc.

Completing this survey may require some reflection on patient safety, quality improvement and / or informatics.

It will provide extremely useful information to the Faculty and in turn to the NHS England working groups reviewing the NHS Code of Conduct.

Please arrange for this questionnaire to be completed by Friday 17 September 2021.
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For the purpose of this survey, a clinical decision support system (CDSS) is a computer system that generates patient-specific advice or risk estimates to support clinical decisions. Examples include:

  • A prescribing advisor that either suggests a drug, or calculates the correct dosage of a drug (eg. warfarin) according to patient features, NICE or BNF recommendations etc.
  • An ECG, lab test or lung function test interpreter that give an interpretation of the meaning of test results – as opposed to simply indicating that a lab test is out of range
  • An algorithm derived from a large dataset that predicts important clinical outcomes, like NHSPredict for breast cancer mortality, QRisk2 for cardiac mortality or the CHADS2 risk score for risk of stroke in patients with AF.

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