AHIC Decision Support 3

Question 1

In predictive analytics for CDS, what is a 'feature' in the context of a machine learning model?

Accepted Answer

An input variable used to train and run the model

Answer

In machine learning, a feature is an individual measurable input variable (e.g., age, lab value, vital sign) used by the model to make predictions.

Question 2

Which evaluation measure is most appropriate when a CDS predictive model's cost of missing a true positive (e.g., sepsis) is very high?

Accepted Answer

Sensitivity (recall)

Answer

High sensitivity ensures that most true positive cases (e.g., sepsis) are identified, minimizing missed diagnoses even at the cost of more false positives.

Question 3

What does 'alert fatigue' primarily lead to in clinical settings?

Accepted Answer

Clinicians ignoring or overriding alerts indiscriminately, including important ones

Answer

Alert fatigue causes clinicians to bypass warnings automatically, increasing the risk that a clinically significant alert will be dismissed without review.

Question 4

A CDS system surfaces recommendations only after a care team member requests them rather than proactively interrupting workflow. This best describes which CDS mode?

Accepted Answer

Passive or on-demand CDS

Answer

Passive or on-demand CDS provides guidance only when the user actively requests it, reducing workflow interruptions.

Question 5

Which clinical concept is central to the ARDEN Syntax used in some CDS rule engines?

Accepted Answer

Medical Logic Modules (MLMs)

Answer

Arden Syntax organizes CDS logic into Medical Logic Modules (MLMs), self-contained units that define a trigger, logic, and action.

(AHIC) AMIA Health Informatics Certification Practice Test

(AHIC) AMIA Health Informatics Certification Practice Test

AHIC Decision Support 3