The American Journal of Medicine
Volume 121, Issue 5, Supplement , Pages S30-S33, May 2008

Expanding Perspectives on Misdiagnosis

  • Beth Crandall, BS

      Affiliations

    • Klein Associates Division, Applied Research Associates, Fairborn, Ohio, USA
    • Corresponding Author InformationRequests for reprints should be addressed to Beth Crandall, Klein Associates Division, Applied Research Associates, 1750 Commerce Center Boulevard North, Fairborn, Ohio 45324-6362.
    • ,
  • Robert L. Wears, MD, MS

      Affiliations

    • Department of Emergency Medicine, University of Florida Health Science Center, Jacksonville, Florida, USA

Article Outline

 

A significant insight to emerge from the review of the diagnostic failure literature by Drs. Berner and Graber1 is that the gaps in our knowledge far exceed the soundly established areas, particularly if we focus on empirical findings based on real-world work by real physicians. This lack of knowledge about the nature of diagnostic problems seems odd, given the current climate of concern and concentrated effort to address safety issues in healthcare, and especially given the centrality of diagnosis in the minds of practitioners. How is it that our knowledge about diagnosis—historically the most central aspect of clinical practice and one that directs the trajectory of tests, procedures, treatment choices, medications, and interventions—has been so impoverished?

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Gaps in research and analysis 

The knowledge gap does not appear to be due to lack of interest in how physicians arrive at a diagnosis. There has been considerable research aimed at identifying and describing the diagnostic process and the nature of diagnostic reasoning. However, the lack of progress in applying research findings to the messy world of clinical practice suggests that we might benefit from examination of an expanded set of questions. There are at least 5 areas in which a change of direction might lead to sustained progress.

Diagnostic Models 

A great deal of the work to date has assumed that diagnostic thinking is best described by highly rationalized analytic models of reasoning (e.g., the hypothetico-deductive or the Bayesian probabilistic models2, 3), with little or no consideration of alternative approaches. There are some exceptions, including criticisms of this view (see Berg and colleagues4, 5 and Toulmin6), Norman's research on clinical reasoning,7, 8 and Patel and colleagues'9 studies of medical decision making. Nevertheless, the prevailing view in healthcare continues to be that analytic models of reasoning describe optimal diagnostic process, i.e., that they are normative. If physicians are not employing these analytic processes, the assertion is that they ought to be.

Surprisingly, research in a number of complex fields has demonstrated that under conditions of uncertainty, time pressure, shifting and conflicting goals, high risk, and responsibility for dealing with multiple other actors in the situation, experts seldom engage in highly analytic modes of decision making. Rather, under these conditions, experts are most likely to use fast and generally sufficient strategies. These strategies (and the methods employed to study them) have been described within a research paradigm referred to as “naturalistic decision making.”10, 11, 12, 13 These findings indicate that we need to better understand the full range of decision making and diagnostic strategies employed by physicians and the contexts of their use.

Static Versus Dynamic Decision Problems 

Most of the research performed regarding diagnosis in medical contexts has concerned static decision problems: only 1 decision needs to be made, the situation does not change, and the alternatives are clear. (A typical example is deciding whether a radiograph contains a fracture). However, much of the work of medicine concerns dynamic decision problems: (1) a series of interdependent decisions and/or actions is required to reach the goal; (2) the situation changes over time, sometimes very rapidly; (3) goals shift or are redefined. Decisions that the clinician make change the milieu, resulting in a new challenge to resolve.14 In contrast to static problems, in dynamic problems there is no theory or process element even close to being considered normative, either for approaching the problem or for establishing a particular sequence of decisions and/or actions as correct.

Problem Detection and Recognition 

One of the greatest holes in our current knowledge base is the failure to address issues of problem detection and recognition. Diagnostic problems do not present themselves fully formed like pebbles lying on a beach. The understanding that an event represents a “problem” must instead be constructed from circumstances that are puzzling, troubling, uncertain, and possibly irrelevant. In order to discern the problem contained within a particular set of circumstances, practitioners must make sense of an uncertain and disorganized set of conditions that initially make little sense.15, 16 Here, much of the work of diagnosis consists of preconscious acts of perception10, 17, 18, 19 and sense making by clinicians who use a variety of strategies to discern the real-world context.13 Given a stream of passing phenomena, distinguishing between items that are relevant or irrelevant, and those that must be accounted for compared with those that can be discounted, creates a preconscious framing that bounds the problem of diagnosis before it is ever consciously considered. This is an important task that has been inadequately studied. If we are going to understand how problems are missed or misunderstood, we need to understand the processes involved in their detection and recognition.

Centrality 

Traditionally, diagnosis has been considered medicine's central task, but it might be useful to entertain the possibility that this emphasis may be misdirected. Having a solid diagnosis often makes much of clinical work easier. However, the lack of a firm diagnosis does not relieve the practitioner of the necessity to take action, and by taking action, risk that the world will be changed, perhaps in unintended ways. Thus, one might argue that the central task of medicine is not diagnosis, but management, especially management in the face of uncertainty. Stated another way, the central question of clinical work might not be, “What is the diagnosis?” but rather, “What should we do now?”

Individual Versus Distributed Cognition 

Most research on diagnostic decision making has concentrated almost entirely on what goes on inside physicians' minds, focusing on internal mental processes, including various cognitive biases and simplifying heuristics. Although understanding the individual physician's cognitive work is clearly necessary, it is not sufficient. Clinicians do their work while embedded in a complex milieu of people, artifacts, procedures, and organizations. All these factors can contribute or detract from diagnostic performance in complex ways; the possibility that the diagnostic process may go awry for reasons other than the physician's reasoning abilities needs more attention. Considering physicians and their environment as joint cognitive systems,20 where cognition and expertise are distributed across multiple people, objects, and procedures within a clinical setting,21 offers a way to widen the tight focus from “inside the physician's head” so that we can begin to examine this larger, and far more complex, scenario.

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Complexities surrounding diagnosis 

One reason we know so little about diagnostic problems may be the complexity of the systems and work processes that surround diagnosis. We know that differences in diagnostic performances exist, but we do not understand diagnostic failure in any deep or detailed way. In the emergency department, for example, the physician's diagnostic process is carried out within the context of large numbers of patients, many of whom have multiple problems; there is little time, resources are constrained, and conditions are chaotic. Some possibilities worth considering include:

•Context: In what situations, and under what conditions, are diagnostic failures most and least prevalent? We need to understand the real-world contexts in which medical diagnosis occurs.

•Team influences: The individual physician is surrounded by other healthcare providers, including other clinicians, who share responsibility for patient care and outcome. How does the distributed nature of patient care foster or prevent diagnostic failure? In the field of aviation, implementation of crew resource management (CRM) has been credited with significant improvements in aviation safety. CRM requires that the pilot in the second seat voice concern to the captain and take assertive action if those matters are ignored. Is aviation's example a useful analogue? In what ways is it applicable?

•System influences: Some hospital systems have been highly successful in addressing patient safety issues such as medication errors and nosocomial infections. Presumably, the prevalence and severity of diagnostic failure vary considerably among hospital systems. This leads to the question, What system-level practices foster diagnostic quality?

•Individual differences: All physicians make mistakes but they appear to occur more frequently among some practitioners, even within a given specialty.22, 23 We know that with experience, diagnostic performance improves but that such progress is not invariant. Some physicians become extraordinarily skilled at evaluation and are recognized by their peers as the “go to” person for the toughest diagnostic challenges. Understanding the elements leading to such expertise would surely be informative, as would gleaning why experience appears to enhance the diagnostic performance of some physicians more than others.

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Designing effective feedback mechanisms 

Identifying the sources of diagnostic failure is a critical first step towards creating feedback systems that provide leverage on the problem. Finding ways to provide feedback on diagnostic performance seems an important venue for improvement, however many difficulties exist. Thus, simply providing feedback is not a “magic bullet” automatically leading to improvement. Learning specialists have found that feedback has greatest impact when it is specific, detailed, and timely.24 These 3 issues, and a 4th—the differential values assigned to different types of failure—represent significant challenges to designing effective feedback systems for physicians.

Specificity 

Providing overall data about diagnostic error rates in physicians is unlikely to get us very far. Grouped data and general findings leave too much room for individual physicians to distance themselves from the findings. However, the processes by which individual physicians' diagnostic performance might be tracked, tagged, and reported back to them are not immediately apparent or readily available.

Detail 

To be effective, feedback must give physicians information that illuminates contingent relationships and causal sequences. Otherwise, they are left with unhelpful admonitions such as “work harder, don't make mistakes, maintain a high index of suspicion.” Feedback needs to provide clinicians with sufficient information so that they can move in an adaptive direction. The simpler the system, the more helpful statistical quality control data are as a basis for self-correction. Highly complex systems may prove insufficient because they create dense forests of information that people—even highly educated, experienced people—have a great deal of difficulty navigating. More data are not necessarily helpful. In many cases, people do not need more data; they need help in making meaning of the data they have.

Timeliness 

The timeliness of feedback, especially regarding diagnostic performance, may be particularly problematic, as the “final diagnosis” often is not known for some time and, indeed, sometimes is never known. Furthermore, in some settings, delayed feedback can disastrously worsen, rather than improve, performance.14

Differential Value 

Finally, simple feedback mechanisms may lead physicians to become systematically inaccurate in undesirable ways, owing to differences in value ascribed to various types of failures. For example, feedback to an emergency physician showing that he/she discharged a patient who subsequently proved to have an acute myocardial infarction is likely to have a much different impact on behavior than feedback showing that a patient admitted for chest pain proved not to have an acute coronary syndrome. The former is likely to be viewed as an adverse event with a significant affective impact while the latter may be perceived as a nonevent.

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Conclusion 

Diagnostic failures are both manifestly important and difficult to comprehend in useful ways. We need to provide a rich fabric of information that allows members of the medical community to see what works and what does not, to hone diagnostic skill, and to hold one another accountable for the quality of diagnoses. To do this, we need to enlarge our notions of the nature of clinical work and of human performance in complex, conflicted, and uncertain contexts.

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Author disclosures 

The authors report the following conflicts of interest with the sponsor of this supplement article or products discussed in this article:

Beth Crandall, BS, has no financial arrangement or affiliation with a corporate organization or a manufacturer of a product discussed in this article.

Robert L. Wears, MD, MS, has no financial arrangement or affiliation with a corporate organization or a manufacturer of a product discussed in this article.

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References 

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 Statement of Author Disclosures: Please see the Author Disclosures section at the end of this article.

PII: S0002-9343(08)00153-8

doi:10.1016/j.amjmed.2008.02.002

The American Journal of Medicine
Volume 121, Issue 5, Supplement , Pages S30-S33, May 2008

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