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CI Board Prep > Fundamentals > Flashcards

Fundamentals Flashcards

1
Q

What comprises a “bit”, “nimble”, “byte” and “word”?

A

A bit is either a binary “0” or “1”.
Nimble = 4 bits
Byte = 8 bits
Word = 16 bits

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2
Q

What are the forms of control structures?

A

Sequential blocks
Conditional blocks
Iterative blocks
Recursive blocks

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3
Q

Software Quality

A

Functional suitability: gets the right result
Performance Efficiency: gets there in a reasonable time using few resources
Compatibility: Friendy towards other software
Usability: Minimizes user frustration
Reliability: does not crash the computer or light things on fire
Security: cannot be misused by bad actors or unwise users
Maintainability: can be understood/updated by the next programemer (esp oneself)
Portability: can be moved or replaced easily

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4
Q

Computational thinking

A

the mental skills and practices for designing computations that get computers to do jobs for us and explaining and interpreting the world as a complex of information processes

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5
Q

Pseudocode

A

Is not another programming language. A programmer describes roughly what they want to accomplish with each code section to complete the solution

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6
Q

Ascertainment bias

A

Thinking is shaped by prior expectation
Ex: stereotyping or gender bias

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7
Q

Availability

A

Overestimating probability of unusual events because of recent or memorable instances

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8
Q

Representativeness

A

Overestimating rare diseases by matching patients to ‘typical picture’ of that disease
“representative heuristic is insensitive to pretest probabilities”

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9
Q

Confirmation bias

A

Tendency to look for confirming evidence rather than disconfirming evidence to refute it
“cherry-picking” results from a large set of negative results

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10
Q

Diagnosis momentum

A

Things that are initially diagnostic considerations, as they are passed from clinician to clinician, become “stickier” and more certain

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11
Q

Anchoring

A

Failure to adjust probaiblity of a disease or outcome based on new information

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12
Q

Premature closure

A

Tendency to accept a diagnosis before it’s fully confirmed

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13
Q

Value-induced bias

A

Overestimate probability of an outcome based on value associated with that outcome

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14
Q

Defending against cognitive bias

A

Decrease reliance on memory (orderset for dx of rheum d/o)
Cognitive forcing strategies (CDS for clinical pathways)
Make task easier (display of complex info like trends and outliers)

Develop insight/awareness
consider alternatives
meta-cognition (“thinking about how you think”)
Specific training
Simulation
Minimize time pressures
Establish accountability
Feedback about diagnostic errors

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15
Q

Expected utlity

A

function of value and also risk aversion, personal preferences/circumstances

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16
Q

Conditional probabilities

A

probability of X given Y

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17
Q

Sequential events

A

Chance tree or graph - model a decision using the sum of conditional probabilities

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18
Q

Decision tree conventions

A

Decisions node = square
Chance node = circle (each branch assigned a probability, all branches at a node must ad to 1
Outcome node = triangle (assigned a “value” - cost, utility, QALY, relative value; if life or death are the outcomes : life = 1, death = 0)

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19
Q

Rollback analysis

A

multiplying the conditional probabilities and comparing the expected value of each branch of a decision node

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20
Q

“What-if” or sensitivity analysis

A

Use a range of values to see how model changes

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21
Q

Cost effectiveness analysis

A

The “value” of outcome nodes become units of cost instead of the valuese used in our example (life =1/ death =0)

22
Q

Quantifying patient utility

A

Adjust the value of the outcome based on the perceived utility of that outcome for that patient
-standard gamble
-time trade-off
-visual analogue

23
Q

Quality-Adjusted Life Year (QALY)

A

Often calculated using time-trade-off
For many patients, there are states of health that are worse than death, so it is possible for QALY to have a negative value
Another way of asking “how many years of your current life would you trade to live in perfect health?” - way to ascertain what utility they assign their current sate of health
Ex: suppose pt says 4 yrs of perfect health = 10 yrs of current illness, TTO = 0.4; therefore, 3 yrs in current sate = 3x 0.4 = 1.2 QALY

24
Q

Incremental Cost/Effectiveness Ratio (ICER)

A

How much do you have to spend to increase effectiveness by one unit
Compare calculated ICER to the “willingness to pay” to determine if a therapy is cost effective and worth implementing

25
Q

Sensitivity

A

likelihood of positive test given disease
aka True Positive Rate
aka Recall

26
Q

Specifity

A

likelihood of a negative test given no disease
aka True Negative Rate

27
Q

PPV

A

likelihood of disease given a positive test
aka Precision

28
Q

NPV

A

likelihood of no disease given a negative test

29
Q

Pragmatic ambiguity

A

conflicting recommendations within a guideline

30
Q

Semantic ambiguity

A

insufficient detail (ex: “specimens should be sent to the lab for further handling” - does not answer “which lab?”)

31
Q

Syntactic ambiguity

A

due to language that prevents translation into a machine-interpretable condition or syntax like not having appropriate parenthesis for interpretation of and/or statements

32
Q

Conditional ambiguity

A

Component of a condition is insufficiently detailed like “suggestive of appendicitis”

33
Q

According to social influence theory, what are the four social computing phenomena which exert influence on adoption of technology?

A

Action, authority, consensus and cooperation

34
Q

Logic model

A

commonly used to represent the next proposed change for the process redesign cycle

35
Q

Process maps

A

tools used to represent workflow analysis

36
Q

Spaghetti diagrams

A

physical maps of the movements of people in a workflow

37
Q

Gap analysis

A

determines the gaps between current state and the ideal future state

38
Q

The six IOM quality domains

A

Safe, Effective, Efficient, Timely, Patient-Centered & Equitable

39
Q

“Five Rights” of CDS

A
  1. Getting the right information
  2. To the right person
  3. In the right format
  4. Through the right channel
  5. At the right time
40
Q

6 pillars of quality

A
  1. Safety
  2. Effectiveness
  3. Efficiency
  4. Patient-centeredness
  5. Timeliness
  6. Equity
41
Q

Expected value

A

summation of the independent probabilities of events

42
Q

Expected utility

A

includes expected value but also takes into account factors like risk aversion, personal preferences, or circumstances

43
Q

Multiplication rules
P(A and B)

A

= P(A) x P(B|A)
the probability of A and B occurring is and equal to the probability of A times the probability of B, given A

44
Q

Decision tree - decision nodes (shape & representation)

A

square
represent branching points in the decision tree

45
Q

Decision tree - chance nodes (shape & representation)

A

circle
represent the probability of a specific outcome occurring

46
Q

Decision tree - outcome nodes (shape & representation)

A

triangle
assigned a value (cost, utility, QALY, relative value, etc)

47
Q

Time Trade Off (TTO) utility

A

the indifference point is the length of remaining life in perfect health divided by the length of reaming life with the evaluate state
ex: one might choose to give up 5 years of life in their current state in order to live a more healthy life vs 10 years in current state. The TTO utility would be 5 years/10years or 0.5

48
Q

Cost-Effectiveness Analysis (CEA)

A

typically expressed in terms of a ratio where the denominator is a gain in health from a measure and the numerator is the cost associated with health gain (cost/QALY)

49
Q

Incremental Cost/Effectiveness Ratio (ICER)

A

“willingness to pay” to determine if a therapy is cost effective
ICER = (Cost A - Cost B)/(Effect A - Effect B)

50
Q

Type I error

A

incorrect rejection of a true null hypothesis (i.e. a false positive) –> leads one to conclude that a supposed effect or relationship exists when in fact it doesn’t
Ex: telling an old man he’s pregnant

51
Q

Type II error

A

failure to reject a false null hypothesis (i.e. a false negative) –> leads one to conclude that a relationship does not exist when it truly does
Ex: telling a pregnant woman you’re not pregnant

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