Lessons in clinical reasoning ‒ pitfalls, myths, and pearls: a case of confusion, disequilibrium, and "picking at the air"

OBJECTIVES

Defects in human cognition commonly result in clinical reasoning failures that can lead to diagnostic errors.

CASE PRESENTATION

A 43-year-old female was brought to the emergency department with 4-5 days of confusion, disequilibrium resulting in several falls, and hallucinations. Further investigation revealed tachycardia, diaphoresis, mydriatic pupils, incomprehensible speech and she was seen picking at the air. Given multiple recent medication changes, there was initial concern for serotonin syndrome vs. an anticholinergic toxidrome. She then developed a fever, marked leukocytosis, and worsening encephalopathy. She underwent lumbar puncture and aspiration of an identified left ankle effusion. Methicillin sensitive staph aureus (MSSA) grew from blood, joint, and cerebrospinal fluid cultures within 18 h. She improved with antibiotics and incision, drainage, and washout of her ankle by orthopedic surgery.

CONCLUSIONS

Through integrated commentary on the diagnostic reasoning process from clinical reasoning experts, this case underscores how multiple cognitive biases can cascade sequentially, skewing clinical reasoning toward erroneous conclusions and driving potentially inappropriate testing and treatment. A fishbone diagram is provided to visually demonstrate the major factors that contributed to the diagnostic error. A case discussant describes the importance of structured reflection, a tool to promote metacognitive analysis, and the application of knowledge organization tools such as illness scripts to navigate these cognitive biases.

What Makes Some Diseases More Typical than Others? A Survey on the Impact of Disease Characteristics and Professional Background on Disease Typicality

Health professionals tend to perceive some diseases as more typical than others. If disease typicalities have implications for health professionals or health policy makers' handling of different diseases, then it is of great social, epistemic, and ethical interest. Accordingly, it is important to find out what makes health professionals rank diseases as more or less typical. This study investigates the impact of various factors on how typical various diseases are perceived to be by health professionals. In particular, we study the influence of broad disease categories, such as somatic versus psychological/behavioral conditions, and a wide range of more specific disease characteristics, as well as the health professional's own background. We find that professional background strongly impacted disease typicality. All professionals (MD, RN, physiotherapists and psychologists) considered somatic conditions to be more typical than psychological/behavioral. As expected, psychologists also found psychological/behavioral conditions to be more typical than did other groups. Professions of respondents could be well predicted from their individual typicality judgments, with the exception of physiotherapists and nurses who had very similar judgment profiles. We also demonstrate how various disease characteristics impact typicality for the different professionals. Typicality showed moderate to strong positive correlations with condition severity and mortality, and only non-severe conditions were rated as atypical. Hence, studying how different disease characteristics and occupational background influences health professionals' perception of disease typicality is the first and important step toward a more general study of how typicality influences disease handling.

Exploring the sources and mechanisms of cognitive errors in medical diagnosis with associative memory models

BACKGROUND

One of the central challenges of third millennium medicine is the abatement of medical errors. Among the most frequent and hardiest causes of misdiagnosis are cognitive errors produced by faulty medical reasoning. These errors have been analyzed from the perspectives of cognitive psychology and empirical medical studies. We introduce a neurocognitive model of medical diagnosis to address this issue.

METHODS

We construct a connectionist model based on the associative nature of human memory to explore the non-analytical, pattern-recognition mode of diagnosis. A context-dependent matrix memory associates signs and symptoms with their corresponding diseases. The weights of these associations depend on the frequencies of occurrence of each disease and on the different combinations of signs and symptoms of each presentation of that disease. The system receives signs and symptoms and by a second input, the degree of diagnostic uncertainty. Its output is a probabilistic map on the set of possible diseases.

RESULTS

The model reproduces different kinds of well-known cognitive errors in diagnosis. Errors in the model come from two sources. One, dependent on the knowledge stored in memory, varies with the accumulated experience of the physician and explains age-dependent errors and effects such as epidemiological masking. The other is independent of experience and explains contextual effects such as anchoring.

CONCLUSIONS

Our results strongly suggest that cognitive biases are inevitable consequences of associative storage and recall. We found that this model provides valuable insight into the mechanisms of cognitive error and we hope it will prove useful in medical education.

Improving diagnosis by improving education: a policy brief on education in healthcare professions

Diagnostic error is increasingly recognized as a major patient safety concern. Efforts to improve diagnosis have largely focused on safety and quality improvement initiatives that patients, providers, and health care organizations can take to improve the diagnostic process and its outcomes. This educational policy brief presents an alternative strategy for improving diagnosis, centered on future healthcare providers, to improve the education and training of clinicians in every health care profession. The hypothesis is that we can improve diagnosis by improving education. A literature search was first conducted to understand the relationship of education and training to diagnosis and diagnostic error in different health care professions. Based on the findings from this search we present the justification for focusing on education and training, recommendations for specific content that should be incorporated to improve diagnosis, and recommendations on educational approaches that should be used. Using an iterative, consensus-based process, we then developed a driver diagram that categorizes the key content into five areas. Learners should: 1) Acquire and effectively use a relevant knowledge base, 2) Optimize clinical reasoning to reduce cognitive error, 3) Understand system-related aspects of care, 4) Effectively engage patients and the diagnostic team, and 5) Acquire appropriate perspectives and attitudes about diagnosis. These domains echo recommendations in the National Academy of Medicine’s report Improving Diagnosis in Health Care. The National Academy report suggests that true interprofessional education and training, incorporating recent advances in understanding diagnostic error, and improving clinical reasoning and other aspects of education, can ultimately improve diagnosis by improving the knowledge, skills, and attitudes of all health care professionals.

Use of clinical simulation to improve diagnostic reasoning in nursing

Abstract Objectives: Propose a methodology for the construction of simulated scenarios and cases to improve diagnostic reasoning in nursing. Method: A methodological study was conducted using theories and concepts from the dual processing theory to develop cases and scenarios of clinical simulation for diagnostic reasoning in nursing through proper use of analytical and non-analytical reasoning. Results and discussion: This study presents and discusses issues of the theoretical framework and operational elements: structure of scenarios, preparation of simulation, briefing, debriefing, and modeling, incorporating any required content. The methodology articulates content that is compatible with analytical reasoning, non-analytical studies and diagnostic accuracy measurements of clinical validation studies. Conclusion: This study demonstrated the feasibility of modeling simulated cases that combine dual processing with diagnostic reasoning in nursing. Implications: Contribution to learning in a safer simulated environment, adopting theoretical bases from studies on human reasoning.

Faculty Development Directed at Curricular Reforms Designed to Improve Patient Outcomes

Three initiatives involving quality of patient outcomes that evolved in the late 1990s must be considered in the design of 21st century undergraduate medical curricula. They involve (1) the question of how to best teach and assess medical competencies, (2) growing concerns regarding the frequency and severity of error in medical care, and (3) the role physicians might play in weaving together the overlapping elements of population-, community-, and systems-based practice into a codified approach to medical care. With these initiatives in mind, the University of North Texas Health Science Center Texas College of Osteopathic Medicine has formed an Academy of Medical Educators whose goal is to develop faculty programs intended to expedite curricular modifications and reforms.