LAUSR

Diagnostic radiology is a specialty of medicine that is uniquely dedicated to the diagnostic process, and it is the only specialty that provides contributing information (and opinion) toward the diagnostic formulation of almost every hospitalized patient throughout the developed world today. As such, one can reasonably conclude that radiology contributes substantially to both successful diagnosis, and to diagnostic error as well, although the actual balance of each contribution is difficult to assess. Diagnostic error in radiology also represents a microcosm of the more general problem and illustrates in very unique ways both the cognitive origins of diagnostic error and the many system-related complexities that can contribute. There is much to be learned about the global causes of diagnostic error by studying how they play out in this one specialty. Radiology also represents a role model for how diagnostic error can be effectively addressed, as illustrated by the many and detailed efforts of the American College of Radiology (ACR) to define effective interventions to reduce error and harm, as described in some detail in a contribution from Allen et al. [1]. The ACR was a key sponsor of the National Academy of Medicine’s major report on Improving Diagnosis in Healthcare, and it is one of the pioneering professional societies that has recognized diagnostic error as a priority problem. A unique approach to studying diagnostic errors involving radiology is the study of closed malpractice claims. Dana Siegal et al. [2] explore over 1300 such cases collected through the CRICO Strategies Comparative Benchmarking System over a 5-year period. The analysis provides many lessons for improving diagnosis, both through insights provided by individual cases and the trends that emerged. Over half of the cases involved lapses in detecting or interpreting images, and a quarter involved breakdowns in communicating imaging results effectively. Several of the articles in this special issue represent contributions from the guest editors: Kevin Johnson [3] presents the central role of Bayes’ theorem and Bayesian reasoning on the diagnostic process and a very nice graphical way for learners to visually appreciate the power of this approach. Bruno [4] points out that radiology is practiced in an environment of very high uncertainty, and some of what we consider to be radiologic interpretive error is actually best understood as a reflection of that fundamental uncertainty. One could argue that the entire role of diagnostic radiology is to reduce the level of uncertainty for the clinician sufficiently to allow the physician to act, and radiology has succeeded once that goal is accomplished, even when the radiological impression does not match the final diagnostic outcome. The fundamental processes of diagnosis are reviewed, as well as radiology’s role in the overall diagnostic process, and the various types of error to which radiologists are particularly prone. Remediation strategies to reduce error and resulting harms to patients are discussed. Jim Duncan [5] of the Washington University in St. Louis shines a bright light on the problem of clinician information overload and attempts to place the role of radiology within the framework of Claude Shannon’s mathematical theory of communication (better known as “information theory”). Dr. Duncan illustrates the complex and nonlinear relationship that exists between “data” and “information,” the former being objective but lacking context and the latter being more difficult to ascertain, but having the benefit of being “actionable.” He proposes that the action – in the form of a clinical intervention for a particular patient – can occur only when the level of uncertainty in the diagnostic information has been reduced to an acceptable level, which may be radiology’s central role. *Corresponding author: Mark L. Graber, SIDM, 5 Hitching Post, Plymouth, MA 02360, USA, E-mail: [email protected] Michael Bruno: Division of Emergency Radiology, Department of Radiology, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA, E-mail: [email protected] Kevin Johnson: Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA, E-mail: [email protected] Nick Argy: Health Law Management and Policy, Boston University Medical Campus, Boston, MA, USA, E-mail: [email protected]