The ARC-PA Pass Rate Report: What Triggers It — and How to Get It Accepted

Few ARC-PA requirements arrive with higher stakes on a tighter clock than the Pass Rate Report. It is triggered automatically by a number — no site visit, no warning letter, no discretion — and an inadequate response can, by itself, put a program on probation. This article gives the full anatomy: what triggers the report, everything it must analyze, the level of statistical rigor that separates accepted reports from rejected ones, and the assembly mistakes we see most often. It is part of our Accreditation Findings & Remediation pillar.

This is Commission-process content rather than Standards-text content, and it carried over the Fifth-to-Sixth Edition transition largely intact — but confirm current specifics against ARC-PA's own materials before relying on them. Last reviewed July 2026.

What is the ARC-PA Pass Rate Report?

The Pass Rate Report is a required analysis a PA program must submit to the ARC-PA when a cohort's first-time PANCE pass rate falls to 85% or below. It is not a form letter — it is a comprehensive, data-driven self-analysis spanning admissions, curriculum, assessment, remediation, and attrition, and the Commission judges it on analytical rigor, not narrative polish.

What triggers the report — and when is it due?

The trigger is mechanical: a cohort's first-time PANCE pass rate at or below 85%, based on the NCCPA data the program reports. Once triggered, the report has been due within six months of the program's Portal data submission, or by July 1 of the following year, whichever comes sooner. The practical consequence of that clock: a program that waits for the official prompt before beginning its analysis has already spent its margin. If your most recent cohort's rate is near the line, start assembling the analysis now.

What happens if the report is not accepted?

The Commission reviews the report and can accept it or require another attempt. The consequence of failing twice is explicit: if a program does not deliver an acceptable report on the second attempt, it can be placed on probation — the Commission will place programs on probation solely for that reason. That is what makes this report different from routine reporting: it is a probation trigger running on autopilot, and the quality bar is the Commission's, not the program's.

What must the report analyze?

The required analysis spans ten elements:

1. Admissions criteria — do the program's selection variables actually predict student success?
2. Individual course performance — course-level outcomes across the curriculum.
3. Course and instructor evaluations — what students reported, correlated with how they performed.
4. Instructional objectives and learning outcomes — curriculum breadth and depth against what the PANCE tests.
5. Summative evaluation results — end-of-curriculum performance as a predictor.
6. Remediation practices and results — who was remediated, how, and what happened next.
7. Attrition criteria and data — who left, when, and why.
8. Feedback from unsuccessful students — what the students who failed report about their preparation.
9. Preceptor and graduate feedback — the clinical-year and post-graduation view.
10. Employer feedback — optional, but strengthens the graduate-outcomes picture.

Each element must connect to the same analytical spine: stated benchmarks with rationale, multi-year data, and conclusions that trace visibly from the analysis to the action plan.

What level of analysis does ARC-PA expect?

Descriptive statistics are the floor, not the target. A report that presents pass rates, means, and year-over-year tables is describing the problem; the Commission is asking the program to diagnose it. The reports that get accepted go further into parametric methods — Pearson correlation, logistic regression, and stepwise regression — because those methods isolate which variables actually predict PANCE performance and which are noise. That distinction is the whole game: an action plan aimed at a variable that doesn't predict the outcome is an action plan the data does not support, and reviewers notice.

What does strong analysis look like in practice?

An anonymized example from our own consulting case studies. In one program's analysis, undergraduate GPA and science GPA each explained roughly 11% of the variance in PANCE scores — statistically significant, but weak predictors. The program's end-of-curriculum summative exam explained about 68% of the variance. And the number of course remediations explained about 45%, with each additional remediation predicting an 18-point drop in PANCE score.

Look at what that changes. The instinct after a bad PANCE year is to tighten admissions. This program's data said admissions variables were marginal — the leverage was in the summative exam as an early-warning instrument and in what remediation was actually accomplishing. The action plan that follows from regression looks completely different from the one that follows from instinct, and it is far easier to defend to the Commission.

What are the most common mistakes?

The failures we see repeatedly, from report drafts and Commission responses:

• A connectivity gap between the analysis sections and the conclusions — strengths, modifications, and areas needing improvement that don't visibly trace to the data presented.
• Benchmarks without definitions or rationale, or conclusions drawn from a single year or single source of data.
• Description masquerading as analysis — restating the numbers rather than interpreting correlations and trends.
• Starting too late for the depth required, then submitting a rushed narrative on the deadline.
• Template and submission errors — the report must go in on the current ARC-PA template, formatted as required; avoidable mechanical errors undermine an otherwise sound analysis.

Can you avoid the report entirely?

The programs that never write this report are the ones already running the analysis continuously — tracking the predictors of PANCE performance cohort by cohort, catching at-risk students through their summative and remediation data, and intervening before the pass rate moves. That is the same continuous self-assessment infrastructure the Sixth Edition expects under its program-evaluation standards, which is the deeper point: the Pass Rate Report is what the Commission demands when the ongoing analysis wasn't happening.

If your program has been asked for a Pass Rate Report — or your most recent first-time rate puts you near the threshold — this is time-critical, statistically demanding work our team has done many times, including the data analysis and drafting oversight. Talk to us about your timeline.

Frequently asked questions

What is the ARC-PA Pass Rate Report?
A required, comprehensive analysis a PA program must submit when a cohort's first-time PANCE pass rate falls to 85% or below. It spans admissions, course performance, curriculum, summative evaluation, remediation, attrition, and stakeholder feedback, and the Commission judges it on analytical rigor.

When is the Pass Rate Report due?
The report has been due within six months of the program's Portal data submission, or by July 1 of the following year, whichever comes sooner. Programs near the threshold should begin the analysis before the official clock starts — the required depth is difficult to produce on deadline.

Can a program be placed on probation over the Pass Rate Report?
Yes. If a program does not deliver an acceptable report on the second attempt, it can be placed on probation — the Commission will place programs on probation solely for that reason, independent of any site visit.

What must the Pass Rate Report include?
Ten analysis elements: admissions criteria, individual course performance, course and instructor evaluations, instructional objectives and learning outcomes, summative evaluation results, remediation practices and results, attrition criteria and data, feedback from unsuccessful students, preceptor and graduate feedback, and (optionally) employer feedback.

What statistical analysis should the report use?
Descriptive statistics are the floor. Accepted reports typically apply parametric methods — Pearson correlation, logistic regression, and stepwise regression — to isolate which variables actually predict PANCE performance, so the action plan targets real predictors rather than instinct.

Understanding why findings compound? Read the multiplier standards and ARC-PA's most common citations.