In Germany, orthopedic and trauma surgery rank first in the number of alleged malpractice claims amongst all medical disciplines. Thus, the German Association of Trauma and Orthopedic Surgery, together with the Bavarian Chamber of Physicians, set out to identify potential predictors of approved malpractice claims to improve process quality. In a case-control study, 164 cases of approved malpractice claims were matched according to age and gender to 336 controls of rejected claims, based on the 2004 to 2006 dataset of the Bavarian Chamber of Physicians. Potential predictors of acceptance of an alleged incident were modeled by uni- and multivariate logistic regression analysis. The final model explained 71% of the probability of acceptance of an asserted claim. It contained three medical consequences (i.e. delayed healing, reoperation, and loss of motion), one specific entity (i.e. fracture) and one socio-demographic variable (i.e. professional driver) as independent predictors of acceptance. Insufficient or lacking explanation of the planned procedure to patients or relatives and / or lacking informed consent (odds ratio [OR] 2.33, 95% confidence interval [CI]1.23-4.43), as well as inappropriate, low-quality, or erroneously interpreted imaging (OR 1.90, 95% CI 1.06-3.41) independently contributed to the likelihood of acceptance of a legal claim. Strict adherence to the principles of surgical quality assurance in terms of transparent patient information and joint informed consent procedures, as well as intransigent radiological imaging are mandatory to foster surgeon-patients-relationships and to avoid later legal claims.

Das Fachgebiet Unfallchirurgie und Orthopädie führt in allen Berichterstattungen der jüngeren Vergangenheit in der Anzahl von Vorwürfen potentieller Behandlungsfehler. Daher wurde das Thema vom Grundsatzausschuss der Deutschen Gesellschaft für Unfallchirurgie e.V. (DGU) aufgegriffen, um gemeinsam mit der Bayerischen Landesärztekammer (BLÄK) Gründe eine Analyse der Schadensfälle vorzunehmen und Strategien für deren Vermeidung zum Schutz der Patienten zu entwickeln.

Most of the recent results in computational geometry apply to the solution of discrete geometric problems. The purpose of this dissertation is to investigate a computational problem in the field of analytic geometry, and to show how the solution of this problem can be used to develop dimension independent iterative algorithms for the solution of discrete geometric problems. The basic structure we use in studying d-dimensional analytic geometry is an ellipsoid. We first show that the study of d-dimensional ellipsoids is based upon results from linear algebra, matrix theory, and finite dimensional Euclidean spaces. This work illustrates that ellipsoids can be represented in a form which can be analyzed easily, independent of dimension. The problem in analytic geometry we consider is the following. Given a set of n points in d-dimensional space, compute the smallest (in volume) ellipsoid which contains the points. This ellipsoid is called the Minimum Spanning Ellipsoid (MSE) of the points. We provide an algorithm to compute the MSE in worst-case time O(n('2)) independent fo dimension. Insights to this algorithm are obtained by first studying the two-dimensional case, and then considering the d-dimensional case. Next, the use of MSE's in solving a discrete geometric problem is studied. An iterative algorithm to determine if a point is inside a convex object with n vertices is provided. The dimension independent nature of this algorithm indicates that minimum spanning ellipsoids can be very useful in solving other finite dimensional geometric problems, such as linear programming.

An algorithm to find the minimum spanning ellipse of a convex set of points in the plane, i.e., the ellipse of minimum area containing the set, is described. The result for higher dimensions is suggested, along with a brief discussion of possible applications.