The VLAD is a graphical representation of the result quality for a selected number of cardiac surgical interventions. The interventions are listed chronologically on the x-axis (1 – n). The result quality of the interventions is added together on the y-axis, a positive outcome causes the curve to rise by the risk-adapted expected mortality and a negative outcome causes it to fall by (1 – risk-adapted expected mortality). In this way, the expected risk of the intervention is taken into account. If there is a high degree of uniformity regarding the average risk, the graph can be expected to oscillate about the zero axis. Better results than predicted are recognised as a climbing graph.
Published in Chapter:
Model Based Decision Making in Cardiac Surgery
Oskar Staudinger (University for Health Sciences, Med Informatics and Tech, Austria), Bettina Staudinger (University for Health Sciences, Med Informatics and Tech, Austria), Herwig Ostermann (University for Health Sciences, Med Informatics and Tech, Austria), Martin Grabenwöger (University of Vienna, Vienna, Austria), and Bernhard Tilg (University for Health Sciences, Med Informatics and Tech, Austria)
Copyright: © 2008
|Pages: 12
DOI: 10.4018/978-1-59904-881-9.ch094
Abstract
The development of models for risk stratification in cardiac surgery goes back a number of years. In 1989, the Society of Thoracic Surgeons (STS) created the first database version for use in the USA. In the year 2005 alone, the data from 234,532 operations were recorded in a structured way by 654 participating institutes. The value of these collected data is described by Ferguson (Ferguson, Dziuban, Edwards, Eiken, Shroyer, & Pairolero, 2000): “Because of their collective efforts, the goal to establish the STS National Data Base as a ‘gold standard’ worldwide for process and outcomes analysis related to cardiothoracic surgery is becoming a reality.” The number of research projects deriving from this is correspondingly large (The Society of Thoracic Surgeons National Database Access and Publications Task Force, 2006).