Hospital stroke volume and case-fatality revisited

Med Care. 2010 Feb;48(2):149-56. doi: 10.1097/MLR.0b013e3181bd4df1.


Background: A few studies have found an inverse association between hospital patient volume and case-fatality among stroke patients. However, the different stroke categorizations used in these studies might have influenced the findings. Furthermore, the relevance of the association observed remains questionable given that the relatively small magnitude may not support volume-based referral policies. We re-examined this association in a large nationwide study, paying attention to the influence of volume categorizations.

Methods: Applying multilevel logistic regression, we re-examined the relationship between hospital stroke volume and 7-day case-fatality using admissions data obtained from Statistics Netherlands on 73,077 stroke patients for the years 2000 to 2004. Different cut-offs were used to categorize hospitals in volume groups. We also examined the implications of a volume based referral strategy.

Results: Stroke patients in high-volume hospitals had decreased risk of dying within 7 days of admission even when different hospital categorizations are applied. For instance, the odds ratio was 0.45(95% CI 0.20-0.99) in high-volume(>200 case-volume) versus low-volume(<50 case-volume) hospitals, but 0.89(95% CI 0.79-1.00) in high-volume(>250 case-volume) versus low-volume (< or =250 case-volume) hospitals. Ignoring travel time and workload implications an optimistic volume-based referral policy would save 183 patients when all patients are referred to the >200 case-volume hospital. A nontransfer policy aimed at reducing mortality by 10% in all those hospitals would save 1260 patients.

Conclusion: Stroke patients in low-volume versus high-volume hospitals have higher odds of dying. This finding may not lend itself to a substantial volume-based referral strategy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Female
  • Hospital Mortality
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Netherlands / epidemiology
  • Outcome and Process Assessment, Health Care*
  • Patient Admission / statistics & numerical data*
  • Patient Transfer*
  • Retrospective Studies
  • Stroke / classification
  • Stroke / mortality*