title: The most dangerous hospital or the most dangerous equation?
abstract: BACKGROUND
  Hospital mortality rates are one of the most frequently selected indicators for measuring the performance of NHS Trusts. A recent article in a national newspaper named the hospital with the highest or lowest mortality in the 2005/6 financial year; a report by the organization Dr Foster Intelligence provided information with regard to the performance of all NHS Trusts in England.
  
  
  METHODS
  Basic statistical theory and computer simulations were used to explore the relationship between the variations in the performance of NHS Trusts and the sizes of the Trusts. Data of hospital standardised mortality ratio (HSMR) of 152 English NHS Trusts for 2005/6 were re-analysed.
  
  
  RESULTS
  A close examination of the information reveals a pattern which is consistent with a statistical phenomenon, discovered by the French mathematician de Moivre nearly 300 years ago, described in every introductory statistics textbook: namely that variation in performance indicators is expected to be greater in small Trusts and smaller in large Trusts. From a statistical viewpoint, the number of deaths in a hospital is not in proportion to the size of the hospital, but is proportional to the square root of its size. Therefore, it is not surprising to note that small hospitals are more likely to occur at the top and the bottom of league tables, whilst mortality rates are independent of hospital sizes.
  
  
  CONCLUSIONS
  This statistical phenomenon needs to be taken into account in the comparison of hospital Trusts performance, especially with regard to policy decisions.
authors.affiliation: Biostatistics Unit, Centre for Epidemiology and Biostatistics, University of Leeds, 30/32 Hyde Terrace, Leeds, LS2 9LN, UK. y.k.tu@leeds.ac.uk
authors.forename: Yu-Kang
authors.initials: YK
authors.lastname: Tu
authors.forename: Mark S
authors.initials: MS
authors.lastname: Gilthorpe
mesh_terms: D003198:Computer Simulation; D004739:England / Q000453:epidemiology; D006276:Health Facility Size / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006779:Hospitals, Public / Q000145:classification / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D008485:Medical Audit; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000706:statistics & numerical data; D010343:Patient Admission / Q000706:statistics & numerical data; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D013222:State Medicine