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Ann Thorac Surg 1997;64:927
© 1997 The Society of Thoracic Surgeons
Division of Cardiothoracic Surgery, University of Florida Health Science Center, Jacksonville, Florida
Principles of pulmonary surgery have traditionally been derived from the reported experience of observational data. Results of these studies have been of enormous value, but although this type of information has served the thoracic surgery community well up to this point, we should recognize that technologic advances now allow us to carry our research efforts to a more advanced level.
Specifically, we need not confine our analyses to the interpretation of observational data. Certainly much can be gained from prospective as well as retrospective observations, but sophisticated statistical techniques now allow us to use clinical information in innovative ways. A variety of statistical algorithms allow patient risk factors to be mathematically manipulated to generate clinical predictions of practical importance. This type of risk analysis may predict either diagnosis or outcome. Many of these statistical tools have proved valuable in other clinical areas, but there has been little application in pulmonary surgery.
It appears possible to develop statistical tools that can assist in the diagnosis of pulmonary lesions with a high degree of accuracy [1]. Such predictive tools are not designed to dictate treatment, but rather serve as one of the diagnostic tests available for patient evaluation. Although this concept may strike some as radical, it should be pointed out that we presently use diagnostic tools that are more invasive, more expensive, and less accurate.
It should be possible to predict a variety of operative outcomes as well. In the arena of cardiac surgery, risk models using preoperative patient risk factors to predict operative outcome have been used extensively in the last few years. These models determine the net impact of all important risk factors to generate a prediction of operative mortality. Such models in pulmonary surgery could have considerable value in patient counseling and medical decision-making. As with diagnostic models, the outcome models should not dictate management, but rather serve as one piece of the puzzle to be considered along with more traditional data.
The outcome models may also serve as powerful quality assurance/quality improvement tools. There is universal agreement that the use of raw mortality data is inadequate to determine quality of care. All patients do not have the same risk, thereby making a system of risk adjustment absolutely mandatory. Statistical risk models allow a patient population to be broken down into subgroups of similar risk. This risk stratification, in turn, allows high-risk patients of one institution to be compared against high-risk patients from another population, the later population ideally representing an accepted standard of care. This allows patients of similar risk to be compared against a standard, so that a meaningful assessment of operative results can be obtained.
Furthermore, in this day of ubiquitous computer systems and global networks, we need not restrict our data sources to those institutions inclined to report their results to medical journals. Such institutions often have specialized referral bases and regional differences that are not likely to represent a true national benchmark for thoracic surgery. In addition, those centers having mediocre results will not rush this information to print, so published data almost certainly reflect optimal rather than typical results. Present database technology can facilitate the accumulation of surgical information from a wide variety of centers to obviate each of these problems. In addition, the availability of a large patient population will generally increase the reliability of statistical studies and will allow for more detailed analyses of uncommon entities.
There have been enormous advances in the practice of general thoracic surgery in the last few years, but the techniques for analyzing our results have simply not kept pace with existing technology. In his Presidential Address to The Society of Thoracic Surgeons, Doctor John R. Benfield focused on this issue and charged the membership to develop meaningful risk assessment techniques in pulmonary surgery [2]. This is no small order, but its undeniable wisdom and vision mandates our initiative and our full cooperation. Enrollment in the Pulmonary Surgery module of The Society of Thoracic Surgeons National Database represents one contribution to this end. Although this participation will be quite valuable, it will not totally address the issue. Almost certainly it will be necessary for innovative leaders in thoracic surgery to step forward with creative new analytic techniques to fully exploit the information at our disposal.
Footnotes
Address reprint requests to Dr Edwards, Division of Cardiothoracic Surgery, University of Florida Health Science Center, 653-2 W Eighth St, Jacksonville, FL 32209-6511.
References
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