title: Developing a summary hospital mortality index: retrospective analysis in English hospitals over five years.
abstract: OBJECTIVE
  To develop a transparent and reproducible measure for hospitals that can indicate when deaths in hospital or within 30 days of discharge are high relative to other hospitals, given the characteristics of the patients in that hospital, and to investigate those factors that have the greatest effect in changing the rank of a hospital, whether interactions exist between those factors, and the stability of the measure over time.
  
  
  METHODS
  Retrospective cross sectional study of admissions to English hospitals.
  
  
  METHODS
  Hospital episode statistics for England from 1 April 2005 to 30 September 2010, with linked mortality data from the Office for National Statistics.
  
  
  METHODS
  36.5 million completed hospital admissions in 146 general and 72 specialist trusts.
  
  
  METHODS
  Deaths within hospital or within 30 days of discharge from hospital.
  
  
  RESULTS
  The predictors that were used in the final model comprised admission diagnosis, age, sex, type of admission, and comorbidity. The percentage of people admitted who died in hospital or within 30 days of discharge was 4.2% for males and 4.5% for females. Emergency admissions comprised 75% of all admissions and 5.5% died, in contrast to 0.8% who died after an elective admission. The percentage who died with a Charlson comorbidity score of 0 was 2% in contrast with 15% who died with a score greater than 5. Given these variables, the relative standardised mortality rates of the hospitals were not noticeably changed by adjusting for the area level deprivation and number of previous emergency visits to hospital. There was little evidence that including interaction terms changed the relative values by any great amount. Using these predictors the summary hospital mortality index (SHMI) was derived. For 2007/8 the model had a C statistic of 0.911 and accounted for 81% of the variability of between hospital mortality. A random effects funnel plot was used to identify outlying hospitals. The outliers from the SHMI over the period 2005-10 have previously been identified using other mortality indicators.
  
  
  CONCLUSIONS
  The SHMI is a relatively simple tool that can be used in conjunction with other information to identify hospitals that may need further investigation.
authors.affiliation: ScHARR, University of Sheffield, Sheffield S1 4DA, UK. m.j.campbell@sheffield.ac.uk
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Campbell
authors.forename: Richard M
authors.initials: RM
authors.lastname: Jacques
authors.forename: James
authors.initials: J
authors.lastname: Fotheringham
authors.forename: Ravi
authors.initials: R
authors.lastname: Maheswaran
authors.forename: Jon
authors.initials: J
authors.lastname: Nicholl
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003430:Cross-Sectional Studies; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D004739:England / Q000453:epidemiology; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006761:Hospitals / Q000592:standards*; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D019984:Quality Indicators, Health Care / Q000592:standards*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D017678:Sex Distribution; D055815:Young Adult