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Difficulty: Very hardResolving Paradoxes and Discrepancies

Following the introduction of an AI-driven automated diagnostic system at a major hospital network, the average triage evaluation time that human emergency room nurses spent per patient increased by 30 percent. Nevertheless, with the total number of emergency room nurses and overall patient volume remaining constant, the average waiting time for patients before receiving treatment decreased significantly across the hospital network.

Which of the following, if true, most helps to resolve the apparent discrepancy described above?

  1. The automated system independently processed and cleared routine, minor cases without nurse involvement, leaving human nurses to handle only severe cases that naturally require longer evaluations.Answer
  2. B
    Human emergency room nurses spent additional time entering medical history data into the new automated system during each patient evaluation.
  3. C
    The hospital network expanded its emergency room waiting facilities, allowing a greater number of non-emergency patients to wait simultaneously.
  4. D
    Emergency room visits during peak evening hours typically involve more complex medical conditions than visits occurring during morning hours.
  5. E
    The automated system significantly reduced the administrative processing time required for post-treatment hospital discharge paperwork.

Answer

The discrepancy is resolved by the fact that the automated system independently processed and cleared routine, minor cases without nurse involvement, leaving human nurses to handle only severe cases that naturally require longer evaluations.
The correct answer reconciles both facts through a subgroup composition shift. When the AI system automatically handles routine minor cases, these patients bypass human triage nurses entirely, significantly shortening the overall patient queue and reducing wait times. Concurrently, human nurses are left evaluating only the severe, complex cases, which naturally take longer to assess. Thus, the average evaluation time per patient for human nurses rises even as overall patient waiting times fall.

Step-by-Step Solution

1
Identify the two apparently contradictory facts in the passage.
Fact 1: Average triage time per patient spent by human nurses increased by 30%. Fact 2: Total nurses and patient volume remained constant, yet average pre-treatment patient wait times decreased significantly.
Resolving a paradox requires finding an explanation that allows both facts to be true simultaneously.
2
Analyze the mathematical and logical relationship between average time per unit and total pool composition.
If the automated system removes a large volume of fast, routine cases from the human queue, the denominator of human-evaluated patients shrinks, consisting now only of complex cases.
A shift in subgroup composition (a weighted average effect) can cause the average time spent on remaining human cases to rise while overall patient throughput speeds up.
3
Evaluate the choices to find the one that addresses both the increase in per-patient nurse time and the decrease in overall wait times.
The option stating that minor cases were handled entirely by the automated system reconciles both phenomena perfectly without contradicting any premise.
By filtering out minor cases, human queues shrink (reducing wait times), while the average time per patient for nurses increases because they only evaluate complex cases.

Key Concept

Resolving Paradoxes: Subgroup Composition Shift (Weighted Average Paradox)
Estimated Time:2m 0s
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Topics

Resolving Paradoxes and Discrepancies

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