OBJECTIVE: To show the influence of variations in case mix on clinical outcome indicators for patients admitted to hospital with acute stroke. DESIGN: "Before and after" cohort study, with prospective, consecutive identification of patients and prospective follow up; multiple logistic regression analyses to correct for case mix variations. SETTING: University teaching hospital. SUBJECTS: 216 patients with stroke identified before the introduction of an organised stroke service, and 252 patients with stroke identified after its introduction. MAIN OUTCOME MEASURES: Case fatality at 30 days and 12 months; for survivors at 12 months, proportions of patients who were independent (according to the Oxford handicap scale) and of those living at home. RESULTS: Crude outcome data suggested that patients in the cohort identified after the introduction of the stroke service were significantly more likely to be alive, independent, and living at home than patients managed before the stroke service. After adjustment for age and sex these "improvements" were less impressive but still significant. After adjustment for many other possible prognostic indicators, however, the differences between the two groups for all four outcomes were non-significant, suggesting that the "improvements" may have been entirely due to differences in case mix between the two cohorts, rather than the new stroke service. CONCLUSIONS: Variations in case mix have a crucial influence on the interpretation of outcome data, and this is particularly important in non-randomised comparative studies. Such studies, comparing performance within and between different provider units, are likely to become increasingly common in the new reformed NHS. To allow meaningful interpretation, these studies must try to correct for case mix.
OBJECTIVE: To show the influence of variations in case mix on clinical outcome indicators for patients admitted to hospital with acute stroke. DESIGN: "Before and after" cohort study, with prospective, consecutive identification of patients and prospective follow up; multiple logistic regression analyses to correct for case mix variations. SETTING: University teaching hospital. SUBJECTS: 216 patients with stroke identified before the introduction of an organised stroke service, and 252 patients with stroke identified after its introduction. MAIN OUTCOME MEASURES: Case fatality at 30 days and 12 months; for survivors at 12 months, proportions of patients who were independent (according to the Oxford handicap scale) and of those living at home. RESULTS: Crude outcome data suggested that patients in the cohort identified after the introduction of the stroke service were significantly more likely to be alive, independent, and living at home than patients managed before the stroke service. After adjustment for age and sex these "improvements" were less impressive but still significant. After adjustment for many other possible prognostic indicators, however, the differences between the two groups for all four outcomes were non-significant, suggesting that the "improvements" may have been entirely due to differences in case mix between the two cohorts, rather than the new stroke service. CONCLUSIONS: Variations in case mix have a crucial influence on the interpretation of outcome data, and this is particularly important in non-randomised comparative studies. Such studies, comparing performance within and between different provider units, are likely to become increasingly common in the new reformed NHS. To allow meaningful interpretation, these studies must try to correct for case mix.
Authors: E B Keeler; K L Kahn; D Draper; M J Sherwood; L V Rubenstein; E J Reinisch; J Kosecoff; R H Brook Journal: JAMA Date: 1990-10-17 Impact factor: 56.272
Authors: J Bamford; P Sandercock; M Dennis; C Warlow; L Jones; K McPherson; M Vessey; G Fowler; A Molyneux; T Hughes Journal: J Neurol Neurosurg Psychiatry Date: 1988-11 Impact factor: 10.154
Authors: William L Palmer; Alex Bottle; Charlie Davie; Charles A Vincent; Paul Aylin Journal: Int J Qual Health Care Date: 2013-04-12 Impact factor: 2.038
Authors: Ron W H Heijnen; Silvia M A A Evers; Trudy D E M van der Weijden; Martien Limburg; Jos M G A Schols Journal: BMC Public Health Date: 2010-05-26 Impact factor: 3.295