An Introduction to Clinical Reasoning (Strong Diagnosis)
Summary
TLDRIn 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
- đšââïž Eric Strong, a practicing hospitalist and clinical associate professor at Stanford University, introduces a new series called 'Strong Diagnosis'.
- đ§ The series focuses on clinical reasoning, which involves hypothesizing possible diagnoses, selecting tests, and developing treatment strategies.
- đ It's designed for intelligent and motivated viewers who are new to the topic of clinical reasoning.
- đ Clinical reasoning includes diagnostic reasoning (identifying the disease) and therapeutic reasoning (deciding on treatment).
- đ€ The process is imprecise, often without a single 'right' answer, and can vary between clinicians due to experience, bias, and uncertainty.
- đ The course is structured in three parts: foundations of diagnostic reasoning, intermediate topics, and quantitative reasoning with biostats and game theory.
- đ Part one covers basics like differential diagnosis, diagnostic frameworks, and test selection without using math.
- đ§ Part two delves into cognitive theories, prediction rules, decision-making models, and common diagnostic errors.
- đ Part three applies biostatistics and expected value analysis to clinical reasoning, including the impact of cost and digital tools.
- đ '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 donât 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.
Outlines
đšââïž Introduction to Clinical Reasoning
Dr. Eric Strong introduces the 'Strong Diagnosis' series, focusing on clinical reasoning within the context of 'Strong Medicine.' The series aims to educate viewers from the basics of differential diagnosis to advanced topics like the application of mathematics in diagnostics and decision-making. It is designed for intelligent and motivated individuals with no prior knowledge of the subject. The video explains the concept of clinical reasoning, which includes diagnostic and therapeutic reasoning, and highlights its imprecision, probabilistic nature, and iterative process. The course is structured into three parts, each with six videos, covering foundational diagnostic reasoning, intermediate topics like cognitive theories and decision-making models, and advanced quantitative reasoning with biostatistics and game theory. The series complements the 'Strong Medicine' series on symptom approaches and diagnostic frameworks.
đ Key Takeaways from Strong Diagnosis
This segment summarizes the key points of the introduction to 'Strong Diagnosis.' Clinical reasoning is defined as the cognitive process clinicians use to make decisions about possible diagnoses and treatment strategies for patients. It is divided into diagnostic reasoning, which focuses on identifying diseases, and therapeutic reasoning, which addresses treatment approaches. The segment emphasizes that clinical reasoning is imprecise, meaning that different clinicians can reach different conclusions based on their experiences and biases. It is also probabilistic, acknowledging the possibility of misdiagnosis despite perfect reasoning, and iterative, as the reasoning process is continuously updated with new data. The video concludes with a reminder to explore the 'Strong Medicine' series for a comprehensive understanding of symptom approaches and diagnostic frameworks.
Mindmap
Keywords
đĄClinical Reasoning
đĄDifferential Diagnosis
đĄPathophysiology
đĄBiostatistics
đĄEpidemiology
đĄShared Decision-Making
đĄDiagnostic Reasoning
đĄTherapeutic Reasoning
đĄIterative Process
đĄCognitive Bias
đĄQuantitative Reasoning
Highlights
Eric Strong introduces a new series on clinical reasoning called 'Strong Diagnosis'.
The series is designed for intelligent and motivated viewers with no prior knowledge of clinical reasoning.
Clinical reasoning involves hypothesizing possible diagnoses, selecting tests, and developing treatment strategies.
It includes knowledge of pathophysiology, biostatistics, and epidemiology, as well as cost considerations and patient values.
Clinical reasoning is divided into diagnostic and therapeutic reasoning.
Diagnostic reasoning focuses on identifying the patient's disease.
Therapeutic reasoning addresses how to treat the identified disease.
Clinical reasoning is imprecise, with situations often lacking a single correct answer.
Clinicians can reach different conclusions due to experiences, cognitive biases, and the need to make best guesses in uncertain situations.
Clinical reasoning is probabilistic, meaning misdiagnoses can occur even with perfect reasoning.
The process is iterative, continuously updated with new data.
The course is organized into three parts, covering foundational, intermediate, and advanced topics in clinical reasoning.
Part one focuses on the foundations of diagnostic reasoning, with no mathematical components.
Part two delves into cognitive theories, clinical prediction rules, and common diagnostic errors.
Part three applies biostatistics and game theory concepts to clinical reasoning.
The series complements the 'Strong Medicine' series on an approach to symptoms, which includes diagnostic frameworks and flowcharts.
Clinical reasoning is described as the cognitive process for decision-making regarding diagnoses and treatment strategies.
The series aims to enhance understanding of clinical reasoning skills in the digital age, including the impact of EMRs and AI on diagnosis.
Transcripts
hello everyone it's Eric strong a
practicing hospitalist
and a clinical associate professor at
Stanford University welcome to a new
series here on strong medicine which I'm
calling strong diagnosis in this series
I'll be talking about the process of
clinical reasoning consistent with
strong medicine in general this series
will assume a viewer who is intelligent
is motivated and who knows nothing about
this particular topic so I'll be taking
you from the absolute basics of what a
differential diagnosis is and will
gradually progress all the way through
some advanced topics like the use of
mathematics in making diagnoses choosing
diagnostic tests and modeling decision
making this video will serve as an
introduction to the subject of clinical
reasoning in general and an introduction
to this course specifically so let's
just start off with the most basic of
questions what is clinical reasoning
clinical reasoning is the collection of
cognitive processes by which a clinician
hypothesizes the possible diagnosis an
individual patient may have selects
appropriate tests to confirm or refute
their hypothesis and develops treatment
strategies for the diagnosis under
consideration it involves the
incorporation of the clinicians
knowledge of pathophysiology the
application of biostatistics and
epidemiology usually qualitatively
though the final videos in this series
will discuss the use of statistics
quantitatively the consideration of the
cost of both tests and treatments both
to the patient and to the healthcare
system in which one is working the
integration of the patient's values and
preferences usually under a model
referred to as shared decision-making
and lastly the communication of one's
thought processes to other healthcare
professionals there are actually two
branches of clinical reasoning and as
typical for medicine the common
terminology is confusing in common usage
the term clinical reasoning is usually
applied just to diagnostic reasoning
that is answering the question what
disease does this patient have
but there is also therapeutic reasoning
that is answering the question how
should we treat that disease in this
patient clinical reasoning both
diagnostic and therapeutic is imprecise
situations often don't have one single
right answer and outstanding clinicians
working with the same information can
reach different conclusions throughout
the series I'll talk about why this
happens but as a spoiler it's partly due
to different or previous experiences
cognitive bias different weight given to
the patient's values and preferences and
because in situations in which
uncertainty or gaps in knowledge exist
clinicians need to insert best guesses
into their analyses guesses which will
vary from person to person in addition
to clinical reasoning and being
imprecise it is also probabilistic this
means that even using perfect reasoning
clinicians can still make misdiagnosis
and clinical reasoning is iterative the
reasoning process whether it's focused
on disease probabilities or treatment
plans is continuously updated with each
new piece of relevant data
this course is organized into three
parts each consisting of six videos part
one will cover the foundations of
diagnostic reasoning these videos will
be relatively short and fully
qualitative meaning no math topics here
include this introduction diagnostic
frameworks and differential diagnosis
Samantha qualifiers and summary
statements illness scripts problem lists
and test selection and apophysis
refinement part two will cover more
intermediate topics including cognitive
theories behind the reasoning process
clinical prediction rules the threshold
model of decision-making cognitive bias
an overview of common diagnostic errors
and the assessment of clinical reasoning
skills and last part three is all about
quantitative reasoning how we apply
biostats and even concepts from game
theory to clinical reasoning the six
topics here will include a bio stats
crash course Bayesian analysis expected
value decision-making expected utility
analysis high-value care and the
influence of cost and finally clinical
reasoning in a digital age from the
effect of using an EMR on the reasoning
process to ai8 at diagnosis to crowd
sourcing diagnostic problems on social
media due to their complexity the videos
for these topics will be a bit longer
than in parts one and two strong
diagnosis this series on clinical
reasoning skills is intended to be a
complement to strong medicine series on
an approach to symptoms which itself
covers the ideologies of common symptoms
along with the appropriate workup full
of diagnostic frameworks and flowcharts
so please check out that series as well
the key takeaway points for this
introduction to strong diagnosis
clinical reasoning is the cognitive
process for which a clinician makes
decisions regarding possible diagnosis
and treatment strategies for an
individual patient it's typically
subdivided into diagnostic reasoning
also known as just clinical reasoning
and therapeutic reasoning and last
clinical reasoning is imprecise
probabilistic and iterative
[Music]
you
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