Safety assurance of autonomous IV medication management systems (SAM)
Research type
Research Study
Full title
Safety assurance of autonomous intravenous medication management systems – requirements and strategies (SAM)
IRAS ID
252028
Contact name
Mark Sujan
Contact email
Sponsor organisation
Human Reliability Associates
Duration of Study in the UK
1 years, 5 months, 28 days
Research summary
Safety assurance of autonomous intravenous medication management systems – requirements and strategies (SAM)
Background: Many medication errors happen in the NHS every year causing harm to patients that could be avoided. Preparation and administration of medications for intravenous (IV) infusion are particularly error prone, because the processes are complicated and staff need to check many different pieces of information. It is known that people are frequently unreliable at such checking tasks. It might be possible to reduce IV medication errors by introducing automation. For example, a computer could check important issues such as patient identity, drug name, and the appropriate rate of giving the medication. Going one step further, intelligent automation (autonomous systems) could even take decisions on its own. For example, an intelligent infusion device could determine when to stop an infusion based on the patient's physiology. This could make care much more personalised, responsive and precise.
Research gap: We do not really understand how patients and staff feel about the safety of such automated and autonomous IV medication management systems. What kind of safety assurance would they require? What kind of safety evidence should the regulator require of manufacturers and healthcare providers? Are existing ways of assessing risk and safety suited to this new class of intelligent devices?
Research approach: We will undertake a systematic review of the literature to find out what we already know on this topic. We will then do interviews with patients, clinical staff, hospital managers, manufacturers and regulators to find out what their thoughts about the safety assurance of such intelligent devices are. Finally, we will work with a clinical team to assess the suitability of existing methods for safety analysis for a prototype system. The prototype is not used in clinical practice, but it has all the relevant functions and can work with simulated data.
REC name
West of Scotland REC 4
REC reference
18/WS/0203
Date of REC Opinion
9 Nov 2018
REC opinion
Unfavourable Opinion