Abdominal Complications of Ventriculoperitoneal Shunts in Children
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- 作者：Brian D. Coley ; Edward J. Kosnik
- 关键词：Author Keywords ; Congenital heart disease ; outcomes ; risk analysis ; risk models ; statistics
- 刊名：Seminars in Ultrasound, CT, and MRI
- 出版年：2006
- 出版时间：April 2006
- 年：2006
- 卷：27
- 期：2
- 页码：152-160
- 全文大小：907 K
文摘
No medical discipline has been more shaped, driven, and scrutinized by outcomes data than cardiac surgery. Unlike high-volume operations for acquired heart disease, congenital heart disease is considerably more heterogeneous, many anomalies are rare, and outcomes after surgical correction are highly variable. How, then, can outcome of institutional programs be compared fairly? Growing in popularity among congenital heart surgeons are methods of comparison that rely fundamentally on expert opinion about perceived complexity of treatment. They may be broadly calibrated using administrative or registry outcomes data. This approach, one of two suggested by Aristotle, characterized pre-Newtonian science, in which observed data played a secondary role. This contrasts sharply with the second approach suggested by Aristotle and revived by Newton in the 18th century that places data at its center: “Let the data speak for themselves.” The latter is the basis for contemporary methods of risk-adjusted comparisons. The proposed international collection of a uniform set of congenital heart surgery data elements, a well-conceived and internationally accepted ontology of congenital heart disease, accurate understanding of established incremental risk factor concepts and their role in risk adjustment, advent of powerful data analysis techniques that include new types of predictive modeling, and wide understanding of risk-adjusted comparison suggest there is ample motivation and opportunity for letting data speak for themselves. There is no evidence that a data-centric approach, based on Aristotle’s and Newton’s ideas that liberated 18th century science, has failed and should be abandoned.