Het volume van chirurgische ingrepen en de impact ervan op ... - KCE
Het volume van chirurgische ingrepen en de impact ervan op ... - KCE
Het volume van chirurgische ingrepen en de impact ervan op ... - KCE
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42 Volume Outcome <strong>KCE</strong> reports 113<br />
date would therefore have <strong>en</strong>ormous implications for the pati<strong>en</strong>t. Wh<strong>en</strong> a<br />
hospital, on the other hand, <strong>en</strong>co<strong>de</strong>s a <strong>de</strong>ath in the MCD, this has no<br />
consequ<strong>en</strong>ces for the pati<strong>en</strong>t concerned since MCD data are only used for<br />
financing the hospital.<br />
3. Complication rate during in<strong>de</strong>x admission or readmission: retrieved from the<br />
MCD. The problem with this outcome is that it relies heavily on the quality of<br />
the hospital coding. Since the rec<strong>en</strong>t <strong>KCE</strong> report by Gillet et al. pointed out<br />
that complication data based on MCD cannot be used for hospital<br />
b<strong>en</strong>chmarking, only <strong>de</strong>scriptive analyses are performed on the complication<br />
rate. 111<br />
4.3 STATISTICAL ANALYSES ON VOLUME OUTCOME<br />
RELATIONSHIP<br />
4.3.1 Funnel Plots<br />
Funnel plots as <strong>de</strong>scribed in Chapter 2, are used as a first informal assessm<strong>en</strong>t of the<br />
<strong>volume</strong>-outcome relationship.<br />
4.3.2 Risk adjustm<strong>en</strong>t<br />
For all procedures, differ<strong>en</strong>t risk factors are tak<strong>en</strong> into account in the regression<br />
mo<strong>de</strong>ls (no matter their statistical significance). These factors are<br />
1. pati<strong>en</strong>t’s age (as a linear variable)<br />
2. pati<strong>en</strong>t’s g<strong>en</strong><strong>de</strong>r<br />
3. principal diagnosis of admission (as categories combined based on frequ<strong>en</strong>cies<br />
and <strong>impact</strong> on mortality)<br />
4. Charlson score (co-morbidity)<br />
5. stage (for cancer procedures).<br />
The severity of illness (SOI) which is <strong>en</strong>co<strong>de</strong>d in the MCD was not used for risk<br />
adjustm<strong>en</strong>t. The reason for this <strong>de</strong>cision is the fact that SOI is <strong>en</strong>co<strong>de</strong>d at the <strong>en</strong>d of the<br />
admission which implies that the pati<strong>en</strong>t’s complications are tak<strong>en</strong> into account.<br />
4.3.2.1 Charlson score<br />
The Charlson score is a validated score based on pati<strong>en</strong>t’s co-morbidities, which<br />
predicts the 1-year mortality. 112-114 The Charlson score is the sum of some pre<strong>de</strong>fined<br />
weights attributed to some specific conditions (see Table 2.1). The higher the score, the<br />
higher the probability of 1-year mortality is. In the regression mo<strong>de</strong>ls applied in this<br />
report, the score is transformed into a five level scale 0, 1, 2, 3 and 4 respectively for<br />
scores 0, 1-2, 3-4, 5-6- and > 6, and is analyzed as a continuous variable, as suggested by<br />
D’Hoore. 114 The information on co-morbidities is retrieved from the variable ‘secondary<br />
diagnosis’ which is <strong>en</strong>co<strong>de</strong>d in the MCD.