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

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208 Volume Outcome KCE reports 113 7.3.5 Definition of outcomes Death Common outcome measures are mortality, loss of independence, loss of mobility and residual pain. Complications associated with hip fracture surgery can be divided in two kinds. Those associated with immobilization include development of deep vein thrombosis, pulmonary embolism, pneumonia, and muscular atrophy; those associated with the surgical procedure include postoperative infection, loss of fixation and nonunion. The latter complications can give cause for a re-intervention. 337 The literature review (see Table 2.1 on page 16) only identified in-hospital mortality as outcome measure for proximal femur fracture. With 645 deaths on a total of 9 934 cases (Table 7.41), in-hospital mortality after hip fracture surgery was 6.49% (6.02%, 7.00%). Table 7.41: Hip fracture surgery: In-hospital mortality (index stay) Number number % 95% CI total outcome outcome 9 934 645 6.49 6.02 7.00 7.3.6 Volume outcome relationship 7.3.6.1 Analysis by hospital IN-HOSPITAL MORTALITY, BY HOSPITAL Figure 7.17 shows that only one hospital was outside the expected 99.8% limits of variability. The horizontal line represents the overall in-hospital mortality rate over all hospitals i.e. 6.5%. Figure 7.17: Hip fracture surgery: Funnel plot of in-hospital mortality, by hospital
KCE Reports 113 Volume Outcome 209 DESCRIPTION OF DIFFERENCES IN CHARACTERISTICS ACCORDING TO THE VOLUME CATEGORY OF THE HOSPITAL Table 7.42 shows the case mix and patient characteristics in function of the volume operated by hospital, classified by tertile. Regardless of the tertile, 75% of the patient population was female and had a mean age of 79.2 years. Compared with medium- and high-volume hospitals (more than 110 hip fracture surgeries in 2004), patients in smallvolume hospitals (less than 60 procedures) had slightly different characteristics: there were more men (29.0%), they were slightly younger (mean age 78.1 years) and they had a higher severity index (34.1% with SOI = 3, 7.6% with SOI = 4). Their Charlson index score was similar, though. Table 7.42: Hip fracture surgery: Differences in case-mix and outcomes by volume category of hospital Tertile based on volume ≤59 >59 and >110 ≤96 All Number hospitals 39 37 37 113 Number stays 1712 2891 5331 9934 Male % 29.0 25.3 24.0 25.3 Age Mean 78.1 79.1 79.6 79.2 Std 13.0 12.2 11.7 12.1 Charlson index score Mean 1.2 1.3 1.2 1.2 Std 1.6 1.7 1.7 1.7 Charlson ≥ 3 % 18.5 19.0 17.1 17.9 Severity index (APR-DRG) 1 % 23.8 22.3 21.9 22.3 2 % 34.6 39.6 39.1 38.5 3 % 34.1 30.9 31.7 31.9 4 % 7.6 7.2 7.3 7.3 In-hospital mortality % 6.4 6.3 6.6 6.5 RELATION MORTALITY BETWEEN HOSPITAL VOLUME AND IN-HOSPITAL The results of the logistic regression are presented in Table 7.43. There is no significant association between a 10% increase in hospital volume and the in-hospital mortality as the effect was +0.48% (-1.22%, 2.17%), without adjusting for case-mix differences. After adjustment for case mix, an increase of 1 category Charlson score was translated by a more than doubling of the in-hospital mortality; the odds ratio being 2.13 (1.99, 2.28). Being a male gave the same effect (odds for mortality: 1.99; 1.64, 2.40). Both effects were statistically significant. On the contrary, an increase of 10% of the hospital volume still had no significant effect (+0.61%; -1.24%, 2.47%). Table 7.43: Hip fracture surgery: Correlation-corrected logistic regression (GEE) estimates of determinants of in-hospital mortality Model without adjustment for case mix Effect 1 95% CI Hospital volume (increase of 10%) 0.48 -1.22 2.17 Model with adjustment for case mix Effect 1 95% CI Hospital volume (increase of 10%) 0.61 -1.24 2.47 Odds Ratio 95% CI Sex (male vs. female) 1.99 1.64 2.40 Age (increase of 1 year) 1.06 1.05 1.07 Charlson score (increase of 1 category) 2.13 1.99 2.28 1 Effect of 10% increase in volume of hospital on the odds of in-hospital mortality
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