Royal Papworth Respiratory Support and Sleep Centre

In conversation with Dr Ian Smith

Wednesday, January 16, 2019

Dr Ian E Smith is a Consultant Chest Physician and Deputy Medical Director of the Royal Papworth Respiratory Support and Sleep Centre. He specialises in ventilatory failure and sleep medicine with expertise in weaning, domiciliary ventilation, sleep apnoea and non-respiratory sleep disorders including narcolepsy and parasomnias. He was a founder of the regional Motor Neurone Disease care network and a co-author of the recent NICE guidelines for people with MND. He is Vice Chair of the UK Association of Respiratory Technicians and Physiologists sleep section, co-authored the British Thoracic Society position statement on driving and sleep apnoea and is the current President of the East Anglian Thoracic Society. In addition Dr Smith is an Associate Lecturer at the University of Cambridge and has held a number of key educational posts.

 Welcome to Respiratory Futures Dr Ian Smith, could you please give us some background to the Royal Papworth Respiratory Support and Sleep Centre?

Our centre is a fully accredited sleep centre where we look after all non-respiratory and respiratory sleep disorders.

The respiratory services involved include domiciliary non-invasive ventilation, an invasive ventilation weaning programme and invasive mechanical ventilation in the community.

The sleep services include providing specialist opinions about Sleep Apnoea (OSA) and other sleep disorders, providing CPAP and alternative therapies and arranging follow-up support.

We also perform more than 100 clinical polysomnographies per month, provide the National Ataxia Telangiectasia Service for adults and are actively involved in sleep research.


How does the centre work across the local area?

There are no really large cities or towns in East Anglia and so the population is spread quite thinly across the region. We have found that the best way to deliver our services is in close collaboration with the community. The centre runs a number of outreach clinics, with diagnostics taking place in the patients’ homes.

This has especially meant a focus on working with GPs including identifying Practices to host diagnostic equipment from which data can be sent into the clinic. This model was piloted in a few practices and was seen to greatly reduce journey times for patients and significantly sped up the referral pathway resulting in the service being adopted across Cambridge CCG.

Our work with GPs has grown sporadically often through Practices volunteering. The aim is for the majority of screenings for OSA to take place in the community and we are working at the moment to finesse and grow the service.


We understand that you’ve had a big boost in finessing your service via a grant opportunity from the EU. What can you tell us about that project?

Yes, we’ve been delighted to be selected to work as part of an EU funded project called ‘Track and Know’ which is aimed at increasing the efficient exploitation of Big Data, applying new analysis techniques in the transport, mobility, motor insurance and health sectors. The project is interested in efficient and scalable smart services and looking at how novel applications, services and operation business models can be supported using Big Data.

Big Data

Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.

The Royal Papworth Respiratory Support and Sleep Centre’s community service is the healthcare project which makes up the health sector section of ‘Track and Know’. The aim is to develop the best possible community service with services provided in optimal locations. We are in the early stages of development, having hosted an initial workshop in December 2018. The project will consist of several key areas of work:

  • Tracking the journeys that patients make for tests: We have records of over 40000 journeys made by sleep centre patients to our hospital and outreach centres to have tests done.
  • Adding relevant variables: the journey data will be compared to a number of variables including road conditions, traffic density and public transport options.
  • Location analysis: technical partners across Europe will then use this data to model the service and give feedback on the best locations for outreach services and diagnostic equipment.
  • Mapping location suggestions to anticipated need: we will then look at population data for each ward across the CCG to consider risk factors such as obesity, hypertension, age and gender and see if the optimised location suggestions match up with this anticipated need.
  • Investigating referral behaviour from GP partners: this mapping will also allow us to see which practices send the most referrals and how this matches against the positive and negative results and the a priori risk status of that local population.
  • Tracking diagnostic equipment in real time: we will then be able to follow, in real time, where our equipment is as part of out-reach services which we hope will allow us to reduce the number of journeys and the amount of time spent on travel. This may allow the service to be more efficient and so expand to other places and conduct more studies with less equipment. We think that we have 3 or 4 times more equipment than would be needed if the service was as efficient as it could possibly be.


This sounds like a fascinating project, will you be using the Big Data in other ways?

Yes, as a side branch of the main project with our EU partners, we are also at the planning stage for a project to take the opportunity of the Big Data repository to investigate driving behaviour for people with untreated and treated OSA. This will be about finding ways to measure drivers’ performance and will include the efficiency of driving in terms of the use of petrol as well as the risk of crashes.

We know that drivers with OSA are 3 or 4 times more at risk of crashes than the population average but that when OSA is treated that risk returns to the baseline. What we don’t know for sure at the moment is what the characteristics behind driving are that create this risk.

In order to find out more we plan to monitor people’s driving before and after treatment to identify the changes in their driving. We will recruit participants before their diagnostic test, this will give us a sample of people who turn out not to have OSA to serve as a benchmark and a proportion who do for whom we can measure the changes.

We plan to monitor people’s driving using an app which can be downloaded onto their mobile phone.

This project will have interesting implications for driving licensing. There are some people who have OSA and are sleepy which can be dangerous for driving but some with OSA who are safe to drive even without treatment. If we can understand more about the dangerous driving characteristics it may be possible to show the DVLA that some people with OSA are safe to drive straight away by differentiating between those who are sleepy and those who are not.

This allows us to avoid the situation which exists in the US where lots of professional drivers are mandated to use CPAP equipment in order to safeguard their driving licence even though they have no symptoms.


And does this part of the project have implications for vocational drivers?

Absolutely, vocational drivers are more at risk than average of OSA because of their sedentary work patterns and time spent away from home and tendency to eat fast food on the go. It has proved difficult to engage them in studies because there is a fear of losing driving licences and so employment.

We hope our study could be another way interact with this population at risk. If we can show that some people with OSA are not dangerous even though they have symptoms then we can reassure drivers that their licences are not at risk. This would allow us to encourage them to come in and get diagnosed and treated for their symptoms.

Similarly by offering an app which can be downloaded and used anonymously we may be able to show some drivers that their driving is in fact dangerous which could make them face up to the risks and encourage them to seek treatment.


Thank you very much for telling us about your project. It might be useful for readers to know about some of the things you have learnt and the challenges you are facing.

I think one of the key learning points for us has been about what is available in terms of technology. We have an electronic patient record and so we’re accumulating lots of data but that system didn’t come with a search engine, and in any case scanned documents, such as GP referrals and paper forms filled out by patients, are saved as image files which can’t be simply be searched. We are now aiming to use some of the funding from this project to purchase software which will allow interrogation of all of our records so that we can use them in an intelligent way.

Similarly the driving behaviours project is something that would not have come along without access to our technical partners who are supporting us with the development of the monitoring app.

A big challenge has been that we have found that our NHS systems run on the minimum capacity and the systems related to this project require a lot of computing power. As a result we are in the process of identifying quiet times in the hospital when we can negotiate to use the computing power we need to run the system.


And what is the timescale of your project?

We are about 9 months in to what is a 3 year project so we will be looking at completing in 2021.


It sounds like there will be some interesting possible wider applications of your work?

Yes, we envisage that the outcome of the project will be a package that delivers home sleep services efficiently which is something that could then be distributed in order to assist other centres across the UK.

The prevalence of OSA is influenced by age and obesity. Demographic trends suggest that the demand for services will only go up and up so finding better ways of screening patients at home or in the community will be crucial to reducing the impact on hospital services.

There are also various other pieces of equipment  for example holter monitors of ECG, which are generally issued from hospitals  which might also be better stored and distributed from GP surgeries but with data sent for reporting in specialist centres. Our service model would be useful for creating community services in other medical areas.


Thank you very much Dr Ian Smith, we wish you the very best for your project. We will keep in touch and look forward to sharing your outcomes and service model in due course.


Related links:

Royal Papworth Respiratory Service and Sleep Centre:

Track and Know Project: