Transforming Site Visits into Continuous Program Success Strategies

There is a phrase that has quietly become outdated in GME offices across the country: "getting ready for accreditation." For a long time, it captured a real workflow. Programs would spend months pulling data, reconciling evaluation records, chasing down Milestones submissions, and scrubbing the ADS Annual Update before a Review Committee deadline or a scheduled site visit. Then, when that window passed, attention moved elsewhere.

That model no longer fits how ACGME accreditation actually works, and the infrastructure ACGME is building makes that shift impossible to ignore.

The question GME teams need to ask is not "are we ready for a site visit?" The better question is: "does our program generate clean, traceable, actionable data every month of the academic year?" Those are two different programs, and they produce two very different accreditation outcomes.

What ACGME Is Building and Why It Matters

In late 2024, ACGME announced the launch of ACGME Cloud, describing it as a platform designed to "unlock the vast potential of data within GME by providing personalized, self-service access to data, analytics, reporting, dashboard, and data exploration capabilities." (ACGME, December 2024)

That is not marketing language. It is a structural signal.

The ACGME Cloud Analytics Explorer tool provides DIOs, program directors, and institutional and program administrators with customizable exploration capabilities using data about their ACGME-accredited Sponsoring Institutions and programs, including the ability to build custom dashboards from Resident/Fellow and Faculty Survey data. ACGME

The transition from the static Data Resource Book to ACGME Cloud means these data will be exclusively available in ACGME Cloud Analytics going forward, with the stated intention of securing access, allowing for more timely publishing of the data, and optimizing resource efficiency. ACGME released additional updates to ACGME Cloud in April 2026, including a unified user experience and enhancements to ACGME Cloud Analytics. ACGMEACGME Cloud

In plain terms: the annual snapshot is being replaced by near-real-time access. The tenth edition of the Milestones National Report, now delivered through ACGME Cloud Analytics, allows program leaders to compare national-level Milestones data in their specialties and subspecialties directly to their own program data, with filtering capabilities that apply a condition across the entire dashboard. ACGME

If your program has not yet explored these dashboards, that is the first concrete action item here.

Surveys Are Not a Box You Check. They Are Accreditation Evidence.

The annual Resident/Fellow and Faculty Surveys remain one of the most consequential data sources in the accreditation system and one of the most mismanaged.

The ACGME's Resident/Fellow and Faculty Surveys are used to monitor graduate medical clinical education and provide early warning of potential non-compliance with ACGME accreditation requirements. All accredited programs, regardless of size, are required to participate each academic year. The required completion rate for both surveys is 70 percent; programs failing to meet this threshold will not receive reports. ACGME

Survey data is part of the information considered by the Review Committees for the accreditation of programs and Sponsoring Institutions, and summary data may be used to inform ACGME policy decisions at the national level. ACGME

That 70 percent threshold has direct consequences. Miss it, and your program loses access to its own aggregated data and the ability to benchmark against national and specialty peers.

Program administrators are typically the people managing roster accuracy in ADS before the window opens and driving completion rates through the survey period. That operational work determines whether the data your PD, DIO, and Review Committee rely on actually exists. Since 2004, ACGME has administered an annual survey of all residents and fellows to monitor ongoing program quality and to serve as a possible indicator of the need to assess programs between site visits. With the introduction of the Next Accreditation System in 2013, the annual survey took on even greater significance as the frequency of scheduled program site visits lengthened to every 10 years.

With site visits are now conducted annually for approximately one to two percent of programs with the status of Continued Accreditation, survey trends carry more weight between those visits than most programs appreciate. PubMed CentralACGME

The PEC Is Your Continuous Quality Engine

The Program Evaluation Committee is, on paper, a compliance structure. In practice, a well-functioning PEC is the mechanism that converts data into documented program improvement, which is exactly what accreditation reviewers look for.

ACGME mandates that residency training programs form program evaluation committees to monitor program delivery and outcomes, generate annual program evaluations, facilitate strategic planning, and implement continuous quality improvement projects. Though PECs provide essential documentation to position programs for successful accreditation decisions, few resources exist in the literature for PEC members. nih

This is the gap most programs experience. The structure is required. The intent is understood. But the operational infrastructure that supports a PEC working from real data throughout the year, rather than assembling documentation in the weeks before an APE is due, often depends on how effectively the GME administrative team manages that pipeline. Survey trends, Milestone distributions, CCC patterns, scholarly activity tracking, and case log completion rates are not separate compliance tasks. They are the dataset your PEC needs to function.

APE documentation that draws a traceable line from finding to action to outcome reflects a program doing this well. Review Committees are looking for genuine continuous improvement, and the difference between programs that demonstrate it and programs that describe it is usually visible in the documentation.

CCC Decisions Need to Be Traceable, Not Just Documented

The Clinical Competency Committee is where trainee progression decisions are made, and GME programs are increasingly expected to show their work.

What distinguishes learning analytics from other educational approaches is systematic data collection and advanced digital interpretation and visualization to inform educational systems. These data are necessary to fully understand educational contexts and guide improvements, advance proficiency among stakeholders to make ethical and accurate summative decisions, and clearly communicate methods, findings, and actionable recommendations for a range of educational stakeholders. nih

Traceability does not require sophisticated software. It requires a consistent documentation structure: which Milestone sub-competencies were reviewed for which trainees, what data the committee considered, what the outcome was, and what the follow-up plan looks like. When that becomes the standard for every CCC meeting, the program builds a paper trail that tells a coherent story about competency-based assessment. Without it, the CCC produces decisions without evidence, which is a liability in any accreditation review and a problem DIOs and accreditation specialists see more often than they should.

What "Always Survey-Ready" Looks Like in Practice

The phrase sounds like more work. In well-organized programs, it produces less stress than the alternative.

ADS rosters are maintained throughout the year, not cleaned up in a rush when the survey window opens. Survey results are reviewed when released and flagged to the PD or DIO when trends warrant attention, not filed until the next APE cycle. Milestone submissions are tracked for completion across individual faculty evaluators, not just at the aggregate level. CCC documentation captures the reasoning behind decisions, not just the outcome. APE narratives connect findings to actions to outcomes in plain language.

For program directors and DIOs, the organizational question worth asking is whether your administrative team has the context to manage data this way, not just the access. Program administrators who understand why the data matters, and not only how to submit it, build programs that are genuinely stronger. For accreditation specialists and DMEs working across multiple programs, the same principle applies at the institutional level. Consistency in how programs document and review their data is something institutional reviewers notice.

The Infrastructure Is Here. The Practice Has to Follow.

ACGME Cloud Analytics is a meaningful investment, and every program should be using it. But tools do not create a data-driven culture. People do.

The most important shift in GME accreditation right now is the expectation that programs understand their own data well enough to use it for decisions, and that they can demonstrate, at any point in the academic year, where they stand against their own improvement goals. That expectation is reflected in how Review Committees read Annual Updates, and how the accreditation system as a whole is evolving.

GME administrative professionals are positioned at the center of that work. The teams that build habits around continuous data management rather than periodic compliance events are the ones their institutions and program leaders lean on most.

If you are working through how to build a more continuous, data-informed accreditation practice, bring those questions to the FULGME community. The experience in this network is deep, and the problems you are working through have almost certainly been navigated by someone here.

References and Resources

ACGME. (December 2024). ACGME Cloud Launching in 2025. https://www.acgme.org/newsroom/2024/12/acgme-cloud-launching-in-2025/

ACGME. (September 2025). September 29, 2025 E-Communication. https://www.acgme.org/newsroom/e-communication/2025/september-29-2025/

ACGME. (October 2025). October 6, 2025 E-Communication. https://www.acgme.org/newsroom/e-communication/2025/october-6-2025/

ACGME. (January 2026). 2024-2025 Statistics on Graduate Medical Education Programs and Resident Physicians. https://www.acgme.org/newsroom/2026/1/acgme-releases-2024-2025-statistics-on-graduate-medical-education-programs-and-resident-physicians/

ACGME. Resident/Fellow and Faculty Surveys. https://www.acgme.org/data-systems-technical-support/resident-fellow-and-faculty-surveys/

ACGME. (2025). Resident/Fellow Survey Content Areas. https://www.acgme.org/globalassets/ResidentSurvey_ContentAreas.pdf

Fromme, H.B., et al. (2020). Best Practices for Building and Supporting Effective ACGME-Mandated Program Evaluation Committees. Journal of Graduate Medical Education. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732133/

Liberman, A.S., et al. (2021). Understanding and Using the ACGME Resident Surveys to Improve Your Residency Program. Journal of Graduate Medical Education. https://pmc.ncbi.nlm.nih.gov/articles/PMC8118477/

Turner, T.L., et al. (2023). Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education. Academic Medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9970252/

FULGME is a non-profit medical educational professional GME Journal and community for GME program administrators, coordinators, and institutional leaders. Views expressed in FULGME blog posts reflect the expertise and perspectives of the GME community and do not represent official ACGME positions or guidance.