Expert comments

Comments on this technology were invited from clinical experts working in the field and relevant patient organisations. The comments received are individual opinions and do not represent NICE's view.

Five experts commented on this briefing. All experts were familiar with and had used this technology before.

Level of innovation

Three out of 5 experts considered the technology to be novel, with 2 further stating innovation with objectivity through the combination of continuous performance tasks and motor (physical) activity, differing from existing, largely subjective neurodevelopmental assessments. One expert stated that, despite being novel, its efficacy is uncertain. The other 2 experts stated that the technology is already used in established practice and is no longer new. Three experts stated that the technology is the first in a new class of procedures. All experts explained that QbTest is to be used as an addition to standard care and not as a replacement.

Potential patient impact

Four out of 5 experts stated a positive impact on patients with suspected attention deficit hyperactivity disorder (ADHD). The other expert stated there are other symptoms outside of the measurements of QbTest and the symptom measurements should not be considered exclusive. One expert described a positive experience for patients and families when using QbTest with regards to objective measurement of ADHD. They also stated it is a more detailed assessment beyond categorical diagnosis. One expert also stated clinicians found value in the ability to assess medication treatment effects using QbTest. Two experts stated that results can be helpful in supporting negative clinical diagnoses of ADHD. Two experts also found use of the technology particularly helpful with young girls where the presentation may be less clear and in those who may 'mask' their symptoms.

Potential system impact

All experts explained the potential beneficial impact of the technology is the reduction in timescale required to reach a diagnostic decision. A reduction in subjective diagnoses and an increase in clinician confidence with regards to diagnostic decision making was found. One expert alluded to the real-world evaluation by an academic health science network (AHSN), which showed a significant reduction in clinician time (20% to 30%) and diagnosis time without loss of diagnostic accuracy. One expert explained that using QbTest allows clinicians to evaluate the impact of medication and make informed decisions about medication. One expert stated the technology is already incorporated within their department in the ADHD pathway.

General comments

All experts stated that the technology is likely to be cost saving due to clinician time saving and efficiency of the pathway. Two experts referred to the real-world demonstrator as evidence. Two experts referred to the regional evaluation by the East Midlands AHSN, where there was a return on investment from 3 trusts adopting the technology. One expert highlighted the economic evaluation of the AQUA trial alluding to both cost saving and cost effectiveness of the technology compared with standard care. Two experts stated this is dependent on how the technology is used.

All experts stated that minimal room adaptation is required, with 4 experts stating that staff training is provided by the company, Qbtech Ltd, with support available anytime. One expert stated that clinicians may mistakenly use QbTest as a standalone tool and that this is not the fault of the technology. Four experts had no experience of adverse effects when using the technology, with 1 expert not commenting.

Two experts reiterated the importance of recognising the technology as an additional decision aid to routine clinical assessment of ADHD and not a standalone. One expert also raised a concern about whether the technology helps measure ADHD or whether it measures impulsivity, hyperactivity and inattention. One expert also alluded to uncertainty about which QbTest scores and which cut-off points – when adjusting for prevalence of ADHD and type of clinical controls – are most helpful in predicting ADHD diagnosis and treatment response.