title: REFINE (REducing Falls in In-patieNt Elderly) using bed and bedside chair pressure sensors linked to radio-pagers in acute hospital care: a randomised controlled trial.
abstract: BACKGROUND
  falls in hospitals are a major problem and contribute to substantial healthcare burden. Advances in sensor technology afford innovative approaches to reducing falls in acute hospital care. However, whether these are clinically effective and cost effective in the UK setting has not been evaluated.
  
  
  METHODS
  pragmatic, parallel-arm, individual randomised controlled trial of bed and bedside chair pressure sensors using radio-pagers (intervention group) compared with standard care (control group) in elderly patients admitted to acute, general medical wards, in a large UK teaching hospital. Primary outcome measure number of in-patient bedside falls per 1,000 bed days.
  
  
  RESULTS
  1,839 participants were randomised (918 to the intervention group and 921 to the control group). There were 85 bedside falls (65 fallers) in the intervention group, falls rate 8.71 per 1,000 bed days compared with 83 bedside falls (64 fallers) in the control group, falls rate 9.84 per 1,000 bed days (adjusted incidence rate ratio, 0.90; 95% confidence interval [CI], 0.66-1.22; P = 0.51). There was no significant difference between the two groups with respect to time to first bedside fall (adjusted hazard ratio (HR), 0.95; 95% CI: 0.67-1.34; P= 0.12). The mean cost per patient in the intervention group was £7199 compared with £6400 in the control group, mean difference in QALYs per patient, 0.0001 (95% CI: -0.0006-0.0004, P= 0.67).
  
  
  CONCLUSIONS
  bed and bedside chair pressure sensors as a single intervention strategy do not reduce in-patient bedside falls, time to first bedside fall and are not cost-effective in elderly patients in acute, general medical wards in the UK.
  
  
  BACKGROUND
  isrctn.org identifier: ISRCTN44972300.
authors.affiliation: Department of Health Care of Older People, Nottingham University Hospitals NHS Trust, QMC Campus, Derby Road, Nottingham, NG72UH Nottingham, UK.
authors.forename: Opinder
authors.initials: O
authors.lastname: Sahota
authors.forename: Avril
authors.initials: A
authors.lastname: Drummond
authors.forename: Denise
authors.initials: D
authors.lastname: Kendrick
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Grainge
authors.forename: Catherine
authors.initials: C
authors.lastname: Vass
authors.forename: Tracey
authors.initials: T
authors.lastname: Sach
authors.forename: John
authors.initials: J
authors.lastname: Gladman
authors.forename: Mark
authors.initials: M
authors.lastname: Avis
mesh_terms: D000058:Accidental Falls / Q000191:economics / Q000517:prevention & control*; D000368:Aged; D000369:Aged, 80 and over; D001513:Beds / Q000191:economics; D003362:Cost-Benefit Analysis; D004739:England / Q000453:epidemiology; D004867:Equipment Design; D005260:Female; D017721:Hospital Costs; D006784:Hospitals, Teaching / Q000191:economics; D006801:Humans; D015994:Incidence; D007297:Inpatients; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D019057:Quality-Adjusted Life Years; D058998:Remote Sensing Technology / Q000191:economics; D012307:Risk Factors; D013997:Time Factors; D014160:Transducers, Pressure / Q000191:economics
keywords: bed sensors; falls; in-patient falls; older people