L13: Clinical Decision Making Flashcards

1
Q

Def of Cinical Decision Making

A
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2
Q

Importance of Decision Making

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2
Q

What does decision making cover?

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3
Q

Steps of clinical decision making process

A
  • Identify client’s (patient’s) goals
  • Identify relevant impairments & abilities.
  • Formulate plan of care.
  • Investigate the literature.
  • Generate a clinical hypothesis.
  • Select & collect the relevant outcome measures.
  • Intervene.
  • Evaluate outcome of the intervention.
  • Report the results in the appropriate venue.
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4
Q

Identify relevant impairments
& abilities

A
  • The physician identify patients’ relevant abilities & impairments by
  • Appropriate tests & measures.
  • The physician & the patient formulate the treatment goals using
  • The information from the patient’s history Discussed In step 1
  • The tests & measures Discussed In step 2
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4
Q

Identify client’s (patient’s)
goals.

A

Interview patients to identify their goals.
- Proper history taking of the current medical condition helps subsequent selection of tests & measures.

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5
Q

Formulate plan of care

A

Different types of interventions:
* Non-pharmacological.
* Pharmacological.
* Surgical.

They have to be selected properly

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6
Q

Investigate the literature

A
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7
Q

Generate a clinical hypothesis

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8
Q

Select & collect the relevant outcome measures

A
  • Select the appropriate outcome measures: To test validity of the clinical hypothesis.
  • This requires reading some of the articles for;
  • The outcome of the intervention.
  • The measures used to capture the outcome.
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8
Q

Intervene

A
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9
Q

Evaluate outcome of the intervention

A

Evaluate the outcomes of a plan of care.
- So, reexamine in a follow-up visit.

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10
Q

Report the results in the appropriate venue

A
  • Reporting outcomes of applying a certain intervention “e.g., acupuncture in obesity” is important.
  • This would take the form of
  • A case report.
  • Case presentation with colleagues.
  • A conference in the form of a platform or poster which would have a published abstract.
  • Even better is the submission of a paper.
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10
Q

Questions to be asked during the course of taking care of patients

A
  • How may I be thorough yet efficient when considering the possible causes of my patient’s problem?
  • How do I characterize the information I have gathered during the medical interview and physical examination?
  • How should I interpret new diagnostic information?
  • How do I select the appropriate diagnostic test?
  • How do I choose among several risky treatments?
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11
Q

How may I be thorough yet efficient when considering the possible causes of my patient’s problem?

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12
Q

Effective VS Efficient

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13
Q

Conflict between Being Efficient & Being Throught

A
  • Trying to be efficient often conflicts with being thorough.
  • This conflict has no single solution:
    1. Listen to expert diagnosticians.
    2. See lots of patients & learn from your mistakes.
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14
Q

How do I characterize the information I have gathered during the medical interview and physical examination?

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15
Q

Expressing Uncertainity

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16
Q

Scale for expressing uncertainty

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17
Q

A probability may apply to …..

A
  • The present state of the patient “eg., patient has coronary artery disease”
  • Or express the likelihood that an event will occur in the future “e.g., patient will experience myocardial infarction within one year”
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18
Q

How should I interpret new diagnostic information?

A
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19
Q

Expressing Reducing Uncertainity

A
  • Avoid Describing uncertainty with words is difficult.
  • The solution is to use numbers “probability” to express uncertainty.
20
Q

what is Bayes’ theorem used to?

A
  • Estimate how much a clinician’s uncertainty about a patient’s true state should have changed.
21
Steps of **Bayes' theorem**
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How do I select the appropriate diagnostic test?
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The selection of diagnostic tests depends on ......
24
Def of **Treatment-Threshold Probability**
- The level of certainty at which a clinician is willing to start treatment. - Selection of diagnostic tests depends on
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How is **Treatment-Threshold Probability** assessed?
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A clinician must take two steps to assess the treatment-threshold probability of disease: ......
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How do I choose among several risky treatments?
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Def of **Expected Value decision Making**
**"The best way to achieve a good outcome of a treatment"** - Choosing the treatment alternative whose average outcome is best.
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Def of **Target Condition**
The disease that the clinician wants to diagnose.
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Example of **Target Condition**
- A patient presents with central chest pain for one hour. - The clinician suspects acute myocardial infarction.
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Test Result can be expressed as
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what is **The upper limit of normal (ULN)**?
is usually all values up to two standard deviations above the mean.
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what is **Sensitivity**?
The frequency of a +ve test in patients with the target condition
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what is **The Cut point**?
defined as the test result that divides the spectrum of test results into a positive region & a negative region
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What is **Specificity**?
The frequency of a -ve test in patients without the target condition
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Clinical laboratories usually report: ......
- The patient's test result. - The test result that corresponds to the upper limit of normal.
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what is a perfect test?
Test with no false +ve results and no false -ve results
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Def of **Test Performance**
- Ability of a test to discriminate between patients with a disease & all other patients.
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what is a **Gold Standard test**?
The procedure that defines the true state of patient
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What is **Index test**?
The test whose performance is being measured
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2* 2 table to assess test performance
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TPR - Name - Definition - Equation - Site in 2*2 Table
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FPR - Name - Definition - Equation - Site in 2*2 Table
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FNR - Name - Definition - Equation - Site in 2*2 Table
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TNR - Name - Definition - Equation - Site in 2*2 Table
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Def of **Bayes's Theorem**
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Importance of **Bayes's Theorem**
Without knowing how new information affects (or will affect) probability, the clinician may acquire too much, too little, or wrong information
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Explanatory Exam For **Bayes's Theorem**
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# **** Def of **Prior (Pretest) Probability**
The probability of an event before acquiring new information
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Def of **Posterior (Posttest) Probability**
The probability of an event after acquiring new information
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Def of **Conditional Probability**
The probability that an event is true given that another event is true **"i.e., conditional upon the second event being true"**
46
Example of **Conditional Probability**
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**Conditional Probability** Problem Solving