L13: Clinical Decision Making Flashcards
Def of Cinical Decision Making
Importance of Decision Making
What does decision making cover?
Steps of clinical decision making process
- 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.
Identify relevant impairments
& abilities
- 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
Identify client’s (patient’s)
goals.
Interview patients to identify their goals.
- Proper history taking of the current medical condition helps subsequent selection of tests & measures.
Formulate plan of care
Different types of interventions:
* Non-pharmacological.
* Pharmacological.
* Surgical.
They have to be selected properly
Investigate the literature
Generate a clinical hypothesis
Select & collect the relevant outcome measures
- 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.
Intervene
Evaluate outcome of the intervention
Evaluate the outcomes of a plan of care.
- So, reexamine in a follow-up visit.
Report the results in the appropriate venue
- 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.
Questions to be asked during the course of taking care of patients
- 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?
How may I be thorough yet efficient when considering the possible causes of my patient’s problem?
Effective VS Efficient
Conflict between Being Efficient & Being Throught
- 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.
How do I characterize the information I have gathered during the medical interview and physical examination?
Expressing Uncertainity
Scale for expressing uncertainty
A probability may apply to …..
- 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”
How should I interpret new diagnostic information?
Expressing Reducing Uncertainity
- Avoid Describing uncertainty with words is difficult.
- The solution is to use numbers “probability” to express uncertainty.
what is Bayes’ theorem used to?
- Estimate how much a clinician’s uncertainty about a patient’s true state should have changed.
Steps of Bayes’ theorem
How do I select the appropriate diagnostic test?
The selection of diagnostic tests depends on ……
Def of Treatment-Threshold Probability
- The level of certainty at which a clinician is willing to start treatment.
- Selection of diagnostic tests depends on
How is Treatment-Threshold Probability assessed?
A clinician must take two steps to assess the treatment-threshold probability of disease: ……
How do I choose among several risky treatments?
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.
Def of Target Condition
The disease that the clinician wants to diagnose.
Example of Target Condition
- A patient presents with central chest pain for one hour.
- The clinician suspects acute myocardial infarction.
Test Result can be expressed as
what is The upper limit of normal (ULN)?
is usually all values up to two standard deviations above the mean.
what is Sensitivity?
The frequency of a +ve test in patients
with the target condition
what is The Cut point?
defined as the test result that divides the spectrum of test results into a positive region & a negative region
What is Specificity?
The frequency of a -ve test in patients
without the target condition
Clinical laboratories usually report: ……
- The patient’s test result.
- The test result that corresponds to the upper limit of normal.
what is a perfect test?
Test with no false +ve results and no false -ve results
Def of Test Performance
- Ability of a test to discriminate between patients with a disease & all other patients.
what is a Gold Standard test?
The procedure that defines the true state of patient
What is Index test?
The test whose performance is being measured
2* 2 table to assess test performance
TPR
- Name
- Definition
- Equation
- Site in 2*2 Table
FPR
- Name
- Definition
- Equation
- Site in 2*2 Table
FNR
- Name
- Definition
- Equation
- Site in 2*2 Table
TNR
- Name
- Definition
- Equation
- Site in 2*2 Table
Def of Bayes’s Theorem
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
Explanatory Exam For Bayes’s Theorem
**
Def of Prior (Pretest) Probability
The probability of an event before acquiring new information
Def of Posterior (Posttest) Probability
The probability of an event after acquiring new information
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”
Example of Conditional Probability
Conditional Probability Problem Solving
