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“Traffic light system” as an indicator for risky patients: which factors are mainly responsible?

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Session Details

Session Title: Cataract I
Session Date/Time: Friday 26/02/2016 | 10:30-12:30
Paper Time: 11:51
Venue: MC3 Room
First Author: : J.Förster GERMANY
Co Author(s): :    T. Herbst              

Abstract Details


Although cataract surgery has become a standardized and safe procedure, adverse events like capsule ruptures still occur. The overall outcome of medical care is not solely determined by medical findings, but also by other factors (e.g. patient satisfaction). The present study wants to find out, which variables are mainly responsible for non-satisfactory outcomes. Therefore, we reverted to our quality measurement system called “Quality Index Bellevue” (QIB).


For a general analysis, we included numerous pre-, peri- and postoperative findings (in the form of raw data or transformed QIBs) in order to identify significant time-depending changes. The measurement system “Quality Index Bellevue” transfers each medical finding into a quality index and bases upon the German school grading system. nordblick Augenklinik Bellevue


The QiB system is built up of three subarea QiBs, which includes measurable and subjectively ascertained findings as well as different aspects of patient satisfaction. Data collection occurred using the “Quality Network Bellevue” (QNB). The nordBLICK Eye Hospital Bellevue is actually connected to 44 established ophthalmologists. With the help of special software, findings have been collected for more than 48.000 patient cases. First of all, we conducted a factor analysis in order to reduce the pool of possible explanatory variables. As a second step, stepwise discriminant analyses were performed in order to identify explanatory variables for different outcome qualities.


After a first factor analysis, we reduced the pool of possible explanatory variables to three (BCVA, co-morbidities, age). A discriminant analyses shows that the risk for worse quality outcome (QIB ≥ 4.0) increases with age, numbers of comorbidities and a small preoperative visual acuity. Further possible factors tend to have a significant influence. Since data collection is still in process, further data analyses will follow.


A “traffic light system” for surgeons, which identifies patients showing a higher risk for complications, seems to desirable in order to prevent complications. With the help of a factor and a discriminant analysis, we first reduced the pool of possible explanatory variables and then tried to quantify their relative explanatory power. First results show that the variables age, co-morbidities and preoperative BCVA seem to have the greatest explanatory power with regard to outcome quality. In future, the implementation of these results into a simple “traffic light system” for the surgeon is the next step.

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