L7 - CLINICAL REASONING Flashcards
Definition of clinical reasoning
- Reasoning skills encompass ability to think critically, analyze info & make sound judgments
based on evidence & logic - In PT:
o Critical thinking
o Decision making
Different reasoning approach
Backward reasoning
Pattern recognition (forward reasoning)
Bayesian reasoning
Description of backward reasoning
- Involves starting with hypothesis about potential causes of patient’s symptoms & working
backward to gather evidence that either supports or refutes hypothesis
1. Backward reasoning
a. Clinician starts with patient’s reported symptoms or clinical findings (pain, stiffness,
weakness…) & hypothesizes potential underlying causes
b. Process involves reasoning backward from observed clinical presentation to determine
possible origins of issue
2. Hypothetical-deductive process
a. Set of potential hypotheses (clinical diagnoses or differential diagnoses) is generated
early in assessment
b. Hypotheses are tested & refined through
▪ History taking
▪ Physical examination
▪ Functional tests
▪ Imaging or other diagnostic tools if needed
3. Iterative process
a. Clinician continually revisits & adjusts hypotheses as new info is gathered during
examination
Advantages of backward reasoning
- Systematic approach: ensures that all potential causes considered, reducing risk of misdiagnosis
- Adaptable: hypotheses can be updated as new evidence emerges, allowing flexibility in treatment
planning - Efficient problem solving prioritizes testing of most probable or impactful diagnoses first
- Evidence-based: grounded in clinical findings & validated by patient’s response to treatment
Disadvantages of backward reasoning
- time
- validity
- multiple pathos
Description of pattern recognition
- Pattern recognition approach = form of clinical reasoning that relies on clinician’s ability to
identify & match patient’s presentation to known pattern of symptoms or dysfunctions based on
prior experience & knowledge
1. Rapid diagnosis
o Clinician identifies familiar cluster of symptoms or signs that match known condition
o Approach bypasses hypothesis generation & testing steps of hypothetical-deductive
method
2. Experience-driven
o Relies heavily on clinician’s expertise, prior clinical encounters & patterns recall
3. Efficient
o Particularly useful in common on straightforward conditions where established patterns
are well-documented
Advantages of pattern recognition
- Speed: reduced time required for diagnosis in straightforward cases
- Effective for common conditions: very useful in MSK PT, where patterns like rotator cuff
tendinopathy, PFPS, or low back strain are frequent - Low cognitive load: relies on intuition & recall rather than methodical analysis
Limitations of pattern recognition
- Not ideal for atypical presentations: if patient’s symptoms don’t fit known pattern, this approach
may fail - Dependent on experience: novice therapists may lack clinical knowledge required to recognize
patterns accurately - Bias risk: over-reliance on past cases can lead to premature conclusions or diagnostic errors
Description of Bayesian reasoning
= involves applying probability-based reasoning to refine diagnoses by integrating prior knowledge (pretest probability) with new clinical findings (likelihood ratios).
- More methodical & evidence-based compared to other approaches
1. Probability-based:
o Uses statistical probabilities to refine diagnoses
o Involves calculating pos-test probability of diagnosis based on presence or absence of
clinical signs
2. Dynamic updating:
o Continually revises likelihood of different diagnoses as more info is gathered
3. Evidence-driven:
o Combines clinical data with research-derived probabilities
Advantages of Bayesian reasoning
- Highly accurate: reduced diagnostic of uncertainty by combining clinical expertise with research
evidence - Systematic & logical: particularly useful in complex or ambiguous cases
- Evidence-based: encourages clinicians to use research data to inform decisions
Limitations of Bayesian reasoning
- Time-consuming: requires tome to calculate probabilities & use diagnostic test effectively
- Data dependency: relies on availability of accurate likelihood ratios & pre-test probabilities
- Complex for novices: requires solid understanding of statistics & clinical reasoning
Description of right kind of reasoning
RIGHT KIND OF REASONING
- Rare for clinician to rely on single type of reasoning
- Backward & forward reasoning: comes with experience
- Apply knowledge
- Varies examination
- Reflection & interaction
Purpose of clinical reasoning
- t to obtain diagnostic certainty but rather to reduce level of uncertainty until treatment
threshold is reached - Clinical tests & measures can never absolutely confirm or exclude presence of specific disease
- Comprehensive diagnosis should encompass what is learned from both diagnostic reasoning
regarding physical problem & narrative reasoning regarding person
Description of data collection of BPS model
a collection
- Ability of clinician to obtain full data base depends on relationship with patient
- Difference between hearing & listening. Most patients actually give you aggravating factors &
facilitating factors during S/E which in turn can give you clues on physiopathology
- Connection must be made between existing knowledge & data obtained: initial phase of
reasoning
Novice: matching patients’ symptoms to concepts
Expert: experimental knowledge within evidence-based framework
- Keeping control
- Recognizing & responding to relevant info
- Specifying symptoms
- Asking specific questions that point to pathophysiological thinking
- Placing questions in logical order, being able to replace patient information in logical order
- Checking agreement with patients
- Summarizing & body language
End goal of BPS model
- Relevant clinical facts / elements
- Predisposing factors (remote + family history)
- Correlations
- Etiologies
- Cautionary situations (flag system)
- Diagnostic hypotheses
