Factor Review Questions (FRQs)

Here, you are asked to select questions that you believe to be most relevant and useful to ask in light of the Coumadin case involving Frances Abbott.

FRQs are meant to make you think about areas where you might gather useful information you don't already have. You are not meant to go through all the questions necessarily. Ask yourself if the question is relevant, regathers information you already have, or would waste your and your interviewee's time.

A scoring system has been set up for this exercise:

Any factor you click on that provides you with new information that helps you fill in the SAFER Matrix for the Coumadin case will earn you 10 points

Any factor you select that gathers information that you already have, or is not entirely relevant to the Coumadin case will earn you 0 points

Any factor that is irrelevant, or may waste your time if you pursue during your investigation of the Coumadin case will cost you 2 points

We'll let you know what a perfect score would be.

N.B. These questions have been modified from the "Systematic Systems Analysis: A Practical Approach to Patient Safety Reviews" guidebook. Please refer to pp 47 to 51 for the full list of FRQs.

Go to Patient FRQs
Go to Personnel FRQs
Go to Environment/Equipment FRQs
Go to Organization FRQs
Go to Regulatory FRQs
  • Your Score ()

Map: Warfarin Factor Review Questions (571)
Node: 16216
Score:

reset

OpenLabyrinth
OpenLabyrinth is an open source educational pathway system

Review your pathway

  • Introduction to the Andy Dufrayne case
  • Random case
  • About Video Mashups
  • Pani Nováková všetko je tak ako má byť. Teraz sa budeme sústrediť na toto tehotenstvo a ak máte ďalšie otázky tak ich prosím smerujte na pána doktora.
  • Main Menu
  • Past Medical History
  • Vad händer sedan?
  • Pick a case
  • Assess the patient
  • Take vital signs
  • Commentary
  • Jag släpar med mig Sandstedt och söker skydd
  • Factor Review Questions (FRQs)

Reminder

empty_reminder_msg

FINISH

Time is up

Debbuger window

Your Score =

Previous_value: