John Williams

Dr John Williams

Senior Clinical Research Fellow


Poh N, Bull S, Tirunagari S, Williams JG, Cole N, Farmer C, de Lusignan S (2017) Identifying Progressive CKD from Primary Care Records ? a Study Protocol,
Rayner L., Sherlock J., Creagh-Brown B., Williams J., de Lusignan S. (2017) The prevalence of COPD in England: An ontological approach to case detection in primary care,Respiratory Medicine132pp. 217-225 Elsevier


Chronic obstructive pulmonary disease (COPD) is a significant cause of morbidity and mortality in England, however estimates of its prevalence vary considerably. Routinely collected and coded primary care data can be used to monitor disease prevalence, however reliance upon diagnostic codes alone is likely to miss cases.


We devised an ontological approach to COPD case detection and implemented it in a large primary care database to identify definite and probable cases of COPD. We used this to estimate the prevalence of COPD in England.


Use of this approach to detect definite COPD cases yielded a prevalence of 2.57% (95% CI 2.55?2.60) in the total population, 4.56% (95%CI 4.52?4.61) in those aged e 35 and 5.41% (95% CI 5.36?5.47) in ex or current smokers. The ontological approach identified an additional 10,543 definite cases compared with using diagnostic codes alone. Prevalence estimates were higher than the 1.9% prevalence currently reported by the UK primary care pay for performance (P4P) disease register. COPD prevalence when definite and probable cases were combined was 3.02% (95% CI 3.0?3.05) in the total population, 5.38% (95% CI 5.33?5.42) in those aged e 35 and 6.46% (95% CI 6.46-6.40-6.56) in ex or current smokers.


We demonstrate a robust reproducible method for COPD case detection in routinely collected primary care data. Our calculated prevalence differed significantly from current estimates based upon P4P data, suggesting that the burden of COPD in England is greater than currently predicted.

ter Avest E., Lambert E., de Coverly R., Tucker H., Griggs J., Wilson M. H., Ghorbangholi A., Williams J., Lyon R.M. (2019) Live video footage from scene to aid helicopter emergency medical service dispatch: a feasibility study,Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine2755 BMC


Obtaining accurate information from a 112 caller is key to correct tasking of Helicopter Emergency Medical Services (HEMS). Being able to view the incident scene via video from a mobile phone may assist HEMS dispatch by providing more accurate information such as mechanism of injury and/or injuries sustained. The objective of this study is to describe the acceptability and feasibility of using live video footage from the mobile phone of a 112 caller as an HEMS dispatch aid.


Live footage is obtained via the 112 caller?s mobile phone camera through the secure GoodSAM app?s Instant-on-scene" platform. Video footage is streamed directly to the dispatcher, and not stored. During the feasibility trial period, dispatchers noted the purpose for which they used the footage and rated ease of use and any technical- and operational issues they encountered. A subjective assessment of caller acceptance to use video was conducted.


Video footage from scene was attempted for 21 emergency calls. The leading reasons listed by the dispatchers to use live footage were to directly assess the patient (18/21) and to obtain information about the mechanism of injury and the scene (11/21). HEMS dispatchers rated the ease of use with a 4.95 on a 5-point scale (range 4?5). All callers gave permission to stream from their telephone camera. Video footage from scene was successfully obtained in 19 calls, and was used by the dispatcher as an aid to send (5) or stand down (14) a Helicopter Emergency Medical Services team.


Live video footage from a 112 caller can be used to provide dispatchers with more information from the scene of an incident and the clinical condition of the patient(s). The use of mobile phone video was readily accepted by the 112 caller and the technology robust. Further research is warranted to assess the impact video from scene could have on HEMS dispatching.