PM&R
BOARD REVIEWQuestion Bank + Clinical Companion

QUESTION BANK · FLASHCARDS · CLINICAL COMPANION

More than a PM&R question bank.

Practice clinical decisions, learn from every answer, retain missed concepts, and prepare for real patients with one connected platform.

Focused assessment

Choose Medical Student & PGY-1 or Resident & Board Review, then select Tutor, Timed Test, Pimp Mode, or Board Simulator. Refine the block by system, subtopic, status, difficulty, and question count.

  • Tutor grading with explanations after one committed answer
  • Timed tests with save-and-exit, notes, marks, strikeout, and question navigation
  • Board simulation in official-length 165- and 160-question sections
  • Rapid oral recall for examination and presentation practice

Prepare for actual patients

Use the PM&R Clinical Companion before clinic or rounds to review the focused history, examination maneuvers, differential diagnosis, workup, treatment options, rehabilitation planning, and a clear presentation framework.

Structured teaching

Every publishable item requires a core explanation, a separate rationale for each distractor, a key takeaway, an actionable clinical pearl, exact citations, and a documented review date.

Medication items add starting dose, route, usual target or ceiling, major safety limits, and monitoring when clinically applicable.

Active recall without the copy-and-paste work

Turn an incorrect, marked, or high-yield question into an editable card from the explanation screen. Review it in the onsite spaced-repetition queue or send it to Anki without manually rebuilding the prompt, answer, source, and tags.

Previous Tests keeps paused and completed sessions connected to their cards. Anki Lab exports UTF-8 tab-separated files filtered by session, answer date, system, incorrect or marked status, and learning level.

  • Editable Front, Back, References, and Tags fields
  • Due-card review and review history on the website
  • Today's incorrects or any custom date range
  • Session, system, status, and learning-level filters