Practice Transformation Under the University of Colorado’s Primary Care Redesign Model
Open accessAbstract
PURPOSE: We compared the transformation experience of 2 family medicine practices that implemented the Primary Care Redesign (PCR) team-based model to improve access, quality, and experience without increasing cost. The University of Colorado's A.F. Williams Family Medicine clinic (pilot practice) implemented the model in February 2015, and a smaller, community-based practice (wave 2 practice) did so 2 years later, in February 2017. METHODS: The PCR model increased the ratio of medical assistants to clinicians from about 1:2 to 2.5:1 while expanding the role of the medical assistants, through enhanced rooming procedures, in-room support (eg, scribing), postclinician wrap-up, and in-basket assistance. We assessed access, clinical quality metrics, staffing costs, and clinician and staff experience and burnout for at least 7 months before and 42 months after the intervention. RESULTS: In the pilot practice, compared with preimplementation, there were improvements in total appointments and rates of hypertension control, colorectal cancer screening, and most diabetic quality metrics. In the wave 2 practice, total appointments increased slightly when clinicians were added pre-PCR and then increased substantially after implementation; initially variable hypertension control improved rapidly after implementation. The wave 2 practice's colorectal cancer screening improved gradually, then accelerated postimplementation, while diabetic metrics initially remained stable or declined, then improved postimplementation. New patient appointments began to increase for both practices in late 2015, but grew faster in the pilot practice under PCR. Over time, all experiential domains improved for clinicians; most remained stable for staff. Clinician burnout was reduced by at least one-half in both practices except during low staffing periods, which also adversely affected staff. After a ramp-up period, the number of staff hours per visit remained stable. CONCLUSIONS: The PCR model is associated with simultaneous improvements in quality, access, and clinician experience, as well as reductions in burnout, while maintaining staffing costs.
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Strategies to reduce documentation burden, including team documentation, automatic speech recognition technologies, and 2021 E&M coding changes have been implemented with variable impact.
“Strategies to reduce documentation burden, including team documentation, 9-13 automatic speech recognition technologies, 14 and 2021 E&M coding changes 15 have been implemented with variable impact.16”
From Ambient artificial intelligence scribes: utilization and impact on documentation time (2025) · cites this paper as [13]
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- Authors
- Smith, P. C., Lyon, C., English, A. F., & Conry, C.
- Affiliations
- University of Colorado Anschutz (US)
- Venue
- The Annals of Family Medicine
- Publisher
- Annals of Family Medicine
- Published
- 2019-08-12
- Volume
- 17
- Issue
- Suppl 1
- Pages
- S24-S32
- ISSN
- 1544-1709 (ISSN-L)
- 1544-1717
- PMC
- PMC6827666
- OpenAlex
- W2968640024
- Cited by
- 28
- References
- 28
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 3 · 2022: 6 · 2021: 7 · 2020: 4 · 2019: 1 · 2018: 1
- FWCI
- 6.13
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- The Annals of Family Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Primary Care and Health Outcomes
- Health Sciences › Health Professions › General Health Professions › Nursing Roles and Practices
- Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
- Keywords
- primary care redesign, team-based care, medical assistants, scribing, health care access, hypertension control, colorectal cancer screening, clinician burnout, personnel costs, community-based primary care
- MeSH terms
- Burnout, Professional, Colorado, Humans, Medical Staff, Organizational Innovation, Primary Health Care, Quality of Health Care, Models, Organizational
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