Consolidated Framework for Implementation Research (CFIR)

In short

A widely used list of everything that can help or block a new practice, with example interview questions for each item. Use it to plan interviews before an AI rollout, or to find out why one is stuck.

For whoever runs the assessment: an HR or operations lead, an internal project team, or an outside consultant.

What it measures

Nothing, in the sense of a score. The framework is an organized list of the things that decide whether a new practice takes hold, in five areas:

• the new practice itself;
• the world outside the organization;
• the organization inside, including its culture and its readiness;
• the people involved;
• the process of putting the practice in place.

The framework’s website offers a planning worksheet, a table of the factors with definitions, and example open questions for each factor.

How to use it

1. Pick the factors that matter for your rollout. Do not ask about all 48.
2. Adapt the example questions to your project. The authors expect you to.
3. Interview people at several levels and in several jobs.
4. Sort the answers by factor in a simple table, and mark each as a help or a barrier.
5. Use the faster analysis method unless you need a research-grade record.

What it does not measure

• A level of readiness. You get a list of barriers and helps, not a number.
• Anything specific to AI. Questions about human oversight or dependence on data have to be added.
• What people do. It relies on what they say in interviews.

How it was tested

• The 2022 update drew on a review of 376 articles that had used the framework and a survey of 134 of their authors.
• It has been used for AI. One study in hospitals in China built its interview guide and its analysis entirely on the framework. From 40 interviews it identified 10 barriers and 8 things that helped.
• A comparison of two ways of analysing the interviews found that a faster method, working from notes and recordings in a spreadsheet, took 409.5 hours against 683 and gave results that were as useful.

Licence and access

The articles are open access under CC BY. The worksheets and templates on the website carry a copyright notice and no licence. They are free to download and use. Republishing or translating them needs confirmation from the CFIR Leadership Team.

Alternatives

Other assessments with a similar job, and when to prefer each.

• What makes this technology project hard? NASSS-CAT: complexity assessment tools for technology projects Prefer it when you want ready checklists and a form for tracking the project, built for technology. The project team, and staff in interviews · Two checklists, a 35-question form and an interview guide Free to use, ask before changing Testing: Moderate Interview guides and checklists
• Is the new way of working becoming routine? NoMAD: is a new way of working taking hold? Prefer it when you want a staff survey with scores, once the rollout has started. The staff who use the new practice · 23 questions Free to use and adapt Testing: Strong Readiness surveys

Practices that use it

• Assess readiness from several sources, not one executive’s rating A readiness check filled in by one senior person reflects that person’s view. Ask staff and managers as well, and compare the answers with what you can observe. Do next · Effort: medium (weeks, a few people) Evidence: Emerging Measurement · Explore

The details

Testing

Strong Used by many independent teams over more than a decade, and updated in 2022 after a review of 376 articles and a survey of 134 users. It has been used to study AI rollouts. It gives no score, so there is nothing to test statistically.

Looks at

Organization, Team

How the answers are collected

Interviews and document review. The framework also guides how to sort the answers.

Length

5 areas and 48 factors. You choose the factors that matter and ask about those.

Cost

Free

Licence

Not stated (tools and templates)The articles are CC BY. The tools and templates on the framework’s website are free to download, but the site states no licence. Ask the CFIR Leadership Team before you republish or translate them.

Languages

English

By

Damschroder and colleagues, updated 2022

Sources

1. Damschroder, Reardon, Opra Widerquist and Lowery (2022). The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Science. doi:10.1186/s13012-022-01245-0
2. CFIR Leadership Team (2025). CFIR Tools and Templates. cfirguide.org
3. Nevedal, Reardon, Opra Widerquist, Jackson and colleagues (2021). Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implementation Science. doi:10.1186/s13012-021-01111-5
4. Liao, Yao, Jin, Zhang and Liu (2024). Barriers and facilitators to implementing imaging-based diagnostic artificial intelligence-assisted decision-making software in hospitals in China: a qualitative study using the updated Consolidated Framework for Implementation Research. BMJ Open. doi:10.1136/bmjopen-2024-084398

Related studies on this site

• Which barriers hold back AI maturity? A survey of 108 specialists van Veen, Zhu and Ravesteyn (2026). How AI Implementation Barriers Shape AI Maturity? The Interacting Roles of Skilled Employees, Technological Infrastructure and Data Quality. CONF-IRM 2026 Proceedings, 17.
• Does readiness for change predict success? A review of 47 studies Caci, Nyantakyi, Blum, Sonpar, Schultes, Albers and Clack (2025). Organizational readiness for change: A systematic review of the healthcare literature. Implementation Research and Practice, 6.