An Introduction to Clinical Reasoning (Strong Diagnosis)

Summary

In the 'Strong Diagnosis' series by Dr. Eric Strong, a hospitalist and professor at Stanford University, he explores clinical reasoning, a critical skill for clinicians. The series is designed for viewers with little to no knowledge in the field, starting from the basics of differential diagnosis and advancing to complex topics like the use of mathematics and decision-making models in diagnostics. Dr. Strong explains that clinical reasoning encompasses both diagnostic and therapeutic aspects, is imprecise and probabilistic, and is an iterative process. The course is divided into three parts, covering foundational diagnostic reasoning, intermediate topics like cognitive theories and decision-making, and advanced quantitative reasoning, aiming to complement the 'Strong Medicine' series on symptom approaches.

Takeaways

• 👨‍⚕️ Eric Strong, a practicing hospitalist and clinical associate professor at Stanford University, introduces a new series called 'Strong Diagnosis'.
• 🧠 The series focuses on clinical reasoning, which involves hypothesizing possible diagnoses, selecting tests, and developing treatment strategies.
• 📚 It's designed for intelligent and motivated viewers who are new to the topic of clinical reasoning.
• 🔍 Clinical reasoning includes diagnostic reasoning (identifying the disease) and therapeutic reasoning (deciding on treatment).
• 🤔 The process is imprecise, often without a single 'right' answer, and can vary between clinicians due to experience, bias, and uncertainty.
• 📈 The course is structured in three parts: foundations of diagnostic reasoning, intermediate topics, and quantitative reasoning with biostats and game theory.
• 📊 Part one covers basics like differential diagnosis, diagnostic frameworks, and test selection without using math.
• 🧠 Part two delves into cognitive theories, prediction rules, decision-making models, and common diagnostic errors.
• 📊 Part three applies biostatistics and expected value analysis to clinical reasoning, including the impact of cost and digital tools.
• 🔗 'Strong Diagnosis' complements the 'Strong Medicine' series, which covers symptom approaches, diagnostic frameworks, and flowcharts.

Q & A

What is clinical reasoning?

Clinical reasoning is the collection of cognitive processes through which a clinician hypothesizes possible diagnoses, selects appropriate tests to confirm or refute those hypotheses, and develops treatment strategies. It integrates pathophysiology, biostatistics, patient values, and communication with healthcare professionals.

What are the two branches of clinical reasoning?

The two branches of clinical reasoning are diagnostic reasoning, which focuses on determining what disease a patient has, and therapeutic reasoning, which focuses on how to treat the disease in a particular patient.

Why is clinical reasoning considered imprecise?

Clinical reasoning is imprecise because situations often don’t have a single correct answer, and different clinicians may reach different conclusions based on their experiences, cognitive biases, and the weight given to the patient's values.

How is clinical reasoning probabilistic?

Clinical reasoning is probabilistic because even with perfect reasoning, clinicians can still make misdiagnoses due to uncertainty, incomplete information, and the need to make educated guesses in certain situations.

What is meant by clinical reasoning being iterative?

Clinical reasoning is iterative, meaning the reasoning process is continuously updated with new relevant data as it becomes available, allowing clinicians to refine their diagnoses and treatment plans.

What topics are covered in part one of the Strong Diagnosis series?

Part one covers the foundations of diagnostic reasoning, including diagnostic frameworks, differential diagnosis, illness scripts, problem lists, test selection, and hypothesis refinement.

What cognitive biases can affect clinical reasoning?

Cognitive biases that can affect clinical reasoning include different weight given to patient preferences and values, as well as biases introduced by previous experiences and gaps in knowledge.

What intermediate topics are covered in part two of the series?

Part two covers cognitive theories behind clinical reasoning, clinical prediction rules, the threshold model of decision-making, cognitive bias, diagnostic errors, and the assessment of clinical reasoning skills.

How does part three of the series relate to quantitative reasoning?

Part three focuses on quantitative reasoning, including biostatistics, Bayesian analysis, expected value decision-making, expected utility analysis, high-value care, and the influence of costs on clinical decisions.

How does the digital age affect clinical reasoning?

In the digital age, clinical reasoning is impacted by the use of electronic medical records (EMRs), artificial intelligence in diagnosis, and crowd-sourcing diagnostic problems through social media, all of which influence decision-making processes.