Het volume van chirurgische ingrepen en de impact ervan op ... - KCE

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210 Volume Outcome KCE reports 113 7.3.6.2 Analysis by surgeon IN-HOSPITAL MORTALITY, BY SURGEON The funnel plot (Figure 7.18) of the in-hospital mortality in function of the number of operations done by surgeon shows that six relatively small to medium-sized hospitals were situated outside the limits of the expected variability. Figure 7.18: Hip fracture surgery: Funnel plot of the in-hospital mortality rate, by surgeon DESCRIPTION OF DIFFERENCES IN CHARACTERISTICS ACCORDING TO THE VOLUME CATEGORY OF THE SURGEON Table 7.44 presents the patient characteristics by surgeon volume tertile. Patients operated by low-volume surgeons (i.e. less than 9 hip fracture surgeries in 2004) are slightly younger (mean age 77.8 years) and are more likely to be male (27.3%) than those operated by medium- or high-volume surgeons (more than 17 procedures per year). On the other hand, however, patients of low-volume surgeons have a lower Charlson index score and a lower severity of index. In-hospital mortality was very comparable between low- and high-volume surgeons i.e., respectively, 6.8 and 6.7%. Medium-volume surgeons, on the other hand, had slightly lower in-hospital mortality (6.0%).
KCE Reports 113 Volume Outcome 211 Table 7.44: Hip fracture surgery: Differences in case-mix and outcomes by volume category of surgeon Tertile based on volume ≤8 > 8 and > 17 ≤17 All Number surgeons 234 225 216 675 Number stays 960 2874 6100 9934 Male % 27.3 24.6 25.2 25.3 Age Mean 77.8 78.8 79.5 79.2 Std 13.4 12.5 11.7 12.1 Charlson index score Mean 1.1 1.2 1.3 1.2 Std 1.6 1.6 1.7 1.7 Charlson ≥ 3 % 15.7 17.2 18.6 17.9 Severity index (APR-DRG) 1 % 23.6 23.1 21.8 22.3 2 % 38.3 36.7 39.3 38.5 3 % 30.7 32.6 31.7 31.9 4 % 7.3 7.6 7.2 7.3 In-hospital mortality % 6.8 6.0 6.7 6.5 RELATION MORTALITY BETWEEN SURGEON VOLUME AND IN-HOSPITAL The effects from the logistic regression are presented in Table 7.45 for in-hospital mortality. Without adjustment for case mix, an increase of 10% of the surgeon had no significant effect on the in-hospital mortality as the effect was -0.05% (-1.33%, +1.23%). After adjustment, the effect is increased but is still not significant at -0.68% (-2.05%, 0.69%). The odds for mortality are doubled in case of male patient, they are slightly higher when age increased by 1 year and they are more than doubled by an increase of 1 category in the Charlson index score. Table 7.45: Hip fracture surgery: Correlation-corrected logistic regression (GEE) estimates of determinants of in-hospital mortality (surgeon volume) Model without adjustment for case mix Effect 1 95% CI Surgeon volume (increase of 10%) -0.05 -1.33 1.23 Model with adjustment for case mix Effect1 95% CI Surgeon volume (increase of 10%) -0.68 -2.05 0.69 Odds Ratio 95% CI Sex (male vs. female) 1.98 1.65 2.36 Age (increase of 1 year) 1.06 1.05 1.07 Charlson score (increase of 1 category) 2.13 1.98 2.29 1 Effect of 10% increase in volume of surgeon on the odds of in-hospital mortality 7.3.7 Discussion 7.3.7.1 External validation of the definition of the procedure According to the Dutch guidelines on osteoporosis from 2002, there would have been 15 290 patients above 55 years for hip fracture hospitalized in the Netherlands in 1999. 339 Considering the number of persons of more than 55 years, if the same incidence was observed in Belgium, there would be 12 120 hospitalizations of patients of more than 55 years, which is of course inferior to the 15 230 patients hospitalized for hip fracture identified by the data extraction, all ages included.
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