SOLVE magazine Issue 03 2021 | Page 3


Life-saving NEWS from old health data

B edside monitoring of hospital patients that draws on big data analytics is saving lives by detecting early the signals pointing to a developing medical emergency . First developed in a collaboration between the University of Portsmouth and Portsmouth Hospitals University NHS Trust , the early warning system is finding its way to patient care around the world .

The system draws on the vast accumulation of vital signs data – the temperature readings , blood pressure , pulse and breathing rates – that indicate the direction in which a patient ’ s health is travelling . The data also , crucially , includes details of what happened to the patient – if people recovered or if they succumbed to infections , cardiac failure or other poor outcomes .
To a new breed of data scientists , such data that links measurements and outcomes offers unprecedented opportunities to innovate clinical practices . Professor Jim Briggs of the University of Portsmouth is one of these scientists .
“ We knew what patient outcomes were from anonymised hospital data . Statistical and artificial intelligence ( AI ) analysis allowed us to see which particular combinations of vital signs were most likely to lead to bad outcomes ,” Professor Briggs says . “ The idea was to then use those signals to distinguish the high-risk patients earlier and alert nurses and doctors .”
The resulting predictive model is called ViEWS ( VitalPAC Early Warning Score ) because it uses data collected by a handheld device ( called VitalPAC ) that is being rolled out across British hospitals so nurses can record vital signs digitally . ViEWS was developed by a larger collaboration that included clinicians Gary Smith and Paul Schmidt and data manager Paul Meredith , all from Portsmouth Hospitals , and Professor Briggs ’ colleague Professor David Prytherch . Those trials showed that ViEWS saves lives – an estimated 200 lives in one year in Portsmouth alone . The impact is that dramatic .
Over the past 10 years , lessons learnt through the development of ViEWS have informed standards set by the Royal College of Physicians ( RCP ) for assessing the severity of acute illness . Those insights are now embedded in the National Early Warning Score ( NEWS ).
NEWS relies on measurements of seven vital signs to assess risk . The higher the risk , the higher the score . What the physicians struggled with is the same issue the Portsmouth team mastered : where to set the thresholds that trigger a warning ?
For example , the RCP recommended a score of three in any single category ( such as blood pressure ) meets the threshold for a warning . But the Portsmouth analysis found that when other vital sign measures were mostly normal , a score of three means a patient isn ’ t any sicker than someone with a combined score of four or five .
“ Our analysis found that aggregate scores – that take into account changes across all vital signs – are more important than any single vital sign ,” Professor Briggs says .
The threshold analysis attracted keen international attention .
“ We calculated that an aggregate figure of five to trigger an alert saves lives without adding to the workload of medical staff . Basically NEWS allows workloads to be targeted towards patients that need attention the most .” A second version of NEWS , called NEWS2 , has now been published and is mandated for use in all acute hospitals and ambulance services . NEWS2 has also been adopted worldwide , including by hospitals in Europe , India and the USA .
“ People keep inventing early warning systems , but our algorithms keep coming out ahead because of how we set the thresholds , incorporating lessons learnt using big data ,” Professor Briggs says .
When COVID-19 hit , the Portsmouth team was able to quickly crunch additional data and showed that NEWS2 was also effective for managing patients . The World Health Organization now recommends the use of NEWS2 for the clinical management of suspected or confirmed COVID-19 patients .
Aiding this international uptake was the decision to publish the ViEWS model rather than commercialise it , and the RCP also deciding to make NEWS and NEWS2 freely available .
“ For me , the motivation was the opportunity to work with some amazing clinicians and to be able to really make a difference to clinical practices ,” Professor Briggs says . “ There are people around the country – around the world – who perhaps wouldn ’ t be alive today if it hadn ’ t been for the Portsmouth team ’ s work .”
Next on the research agenda ? A project to assess how frequently nurses should do the rounds and take people ’ s vital signs . “ This is an ongoing evolution where data scientists and clinicians can join forces in a process of innovation that is really about learning the deeper , subtler or complex lessons hidden in data that virtually every hospital holds ,” Professor Briggs says .
ISSUE 03 / 2021