title: Improving the Estimation of Risk-Adjusted Grouped Hospital Standardized Mortality Ratios Using Cross-Jurisdictional Linked Administrative Data: A Retrospective Cohort Study.
abstract: BACKGROUND
  Hospitals and death registries in Australia are operated under individual state government jurisdictions. Some state borders are located in heavily populated areas or are located near to major capital cities. Mortality indicators for hospital located near state borders may not be estimated accurately if patients are lost as they cross state borders. The aim of this study was to evaluate how cross-jurisdictional linkage of state hospital and death records across state borders may improve estimation of the hospital standardized mortality ratio (HSMR), a tool used in Australia as a hospital performance indicator.
  
  
  METHODS
  Retrospective cohort study of 7.7 million hospital patients from July 2004 to June 2009. Inhospital deaths and deaths within 30 days of hospital discharge from four state jurisdictions were used to estimate the standardized mortality ratio of hospital groups defined by geography and type of hospital (grouped HSMR) under three record linkage scenarios, as follows: (1) cross-jurisdictional person-level linkage, (2) within-jurisdictional (state-based) person-level linkage, and (3) unlinked records. All public and private hospitals in New South Wales, Queensland, Western Australia, and public hospitals in South Australia were included in this study. Death registrations from all four states were obtained from state-based registries of births, deaths, and marriages.
  
  
  RESULTS
  Cross-jurisdictional linkage identified 11,116 cross-border hospital transfers of which 170 resulted in a cross-border inhospital death. An additional 496 cross-border deaths occurred within 30 days of hospital discharge. The inclusion of cross-jurisdictional person-level links to unlinked hospital records reduced the coefficient of variation among the grouped HSMRs from 0.19 to 0.15; the inclusion of 30-day deaths reduced the coefficient of variation further to 0.11. There were minor changes in grouped HSMRs between cross-jurisdictional and within-jurisdictional linkages, although the impact of cross-jurisdictional linkage increased when restricted to regions with high cross-border hospital use.
  
  
  CONCLUSIONS
  Cross-jurisdictional linkage modified estimates of grouped HSMRs in hospital groups likely to receive a high proportion of cross-border users. Hospital identifiers will be required to confirm whether individual hospital performance indicators change.
authors.affiliation: Centre for Population Health Research, Curtin University , Perth, WA , Australia.
authors.forename: Katrina
authors.initials: K
authors.lastname: Spilsbury
authors.affiliation: Centre for Population Health Research, Curtin University, Perth, WA, Australia; Data Linkage, Department of Health WA, Perth, WA, Australia.
authors.forename: Diana
authors.initials: D
authors.lastname: Rosman
authors.affiliation: Centre for Population Health Research, Curtin University , Perth, WA , Australia.
authors.forename: Janine
authors.initials: J
authors.lastname: Alan
authors.affiliation: PHRN Centre for Data Linkage, Centre for Population Health Research, Curtin University , Perth, WA , Australia.
authors.forename: Anna M
authors.initials: AM
authors.lastname: Ferrante
authors.affiliation: PHRN Centre for Data Linkage, Centre for Population Health Research, Curtin University , Perth, WA , Australia.
authors.forename: James H
authors.initials: JH
authors.lastname: Boyd
authors.affiliation: Centre for Population Health Research, Curtin University , Perth, WA , Australia.
authors.forename: James B
authors.initials: JB
authors.lastname: Semmens
keywords: cohort studies; cross-jurisdictional record linkage; epidemiology; hospital standardized mortality ratios; risk adjustment