title: 'Errors' and omissions in paper-based early warning scores: the association with changes in vital signs--a database analysis.
abstract: OBJECTIVE
  To understand factors associated with errors using an established paper-based early warning score (EWS) system. We investigated the types of error, where they are most likely to occur, and whether 'errors' can predict subsequent changes in patient vital signs.
  
  
  METHODS
  Retrospective analysis of prospectively collected early warning system database from a single large UK teaching hospital.
  
  
  RESULTS
  16,795 observation sets, from 200 postsurgical patients, were collected. Incomplete observation sets were more likely to contain observations which should have led to an alert than complete observation sets (15.1% vs 7.6%, p<0.001), but less likely to have an alerting score correctly calculated (38.8% vs 30.0%, p<0.001). Mis-scoring was much more common when leaving a sequence of three or more consecutive observation sets with aggregate scores of 0 (55.3%) than within the sequence (3.0%, p<0.001). Observation sets that 'incorrectly' alerted were more frequently followed by a correctly alerting observation set than error-free non-alerting observation sets (14.7% vs 4.2%, p<0.001). Observation sets that 'incorrectly' did not alert were more frequently followed by an observation set that did not alert than error-free alerting observation sets (73.2% vs 45.8%, p<0.001).
  
  
  CONCLUSIONS
  Missed alerts are particularly common in incomplete observation sets and when a patient first becomes unstable. Observation sets that 'incorrectly' alert or 'incorrectly' do not alert are highly predictive of the next observation set, suggesting that clinical staff detect both deterioration and improvement in advance of the EWS system by using information not currently encoded within it. Work is urgently needed to understand how best to capture this information.
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Oxford, UK.
authors.forename: David A
authors.initials: DA
authors.lastname: Clifton
authors.affiliation: Centre for Statistics in Medicine, University of Oxford, Oxford, UK.
authors.forename: Lei
authors.initials: L
authors.lastname: Clifton
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Oxford, UK.
authors.forename: Dona-Maria
authors.initials: DM
authors.lastname: Sandu
authors.affiliation: Centre of Postgraduate Medical Research & Education (CoPMRE), the School of Health & Social Care, Bournemouth University, Bournemouth, UK.
authors.forename: G B
authors.initials: GB
authors.lastname: Smith
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Oxford, UK.
authors.forename: Lionel
authors.initials: L
authors.lastname: Tarassenko
authors.affiliation: Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
authors.forename: Sarah A
authors.initials: SA
authors.lastname: Vollam
authors.affiliation: Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Watkinson
mesh_terms: D000368:Aged; D016208:Databases, Factual; D013505:Digestive System Surgical Procedures; D005260:Female; D006760:Hospitalization; D006784:Hospitals, Teaching; D006801:Humans; D008297:Male; D008875:Middle Aged; D011183:Postoperative Complications / Q000175:diagnosis*; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D006113:United Kingdom; D055986:Vital Signs
keywords: Early warning system; Patient safety; vital signs monitoring