Skip to main content

Main menu

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • Other Publications
    • abfm

User menu

Search

  • Advanced search
American Board of Family Medicine
  • Other Publications
    • abfm
American Board of Family Medicine

American Board of Family Medicine

Advanced Search

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • JABFM On Twitter
  • JABFM On YouTube
  • JABFM On Facebook
Research ArticleOriginal Research

Low-Intensity Intervention Supports Diabetes Registry Implementation: A Cluster-Randomized Trial in the Ambulatory Care Outcomes Research Network (ACORN)

Roy T. Sabo, Rebecca S. Etz, Martha M. Gonzalez, Nicole J. Johnson, Jonathan P. O'Neal, Sarah R. Reves and Jesse C. Crosson
The Journal of the American Board of Family Medicine September 2020, 33 (5) 728-735; DOI: https://doi.org/10.3122/jabfm.2020.05.190455
Roy T. Sabo
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rebecca S. Etz
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martha M. Gonzalez
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicole J. Johnson
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jonathan P. O'Neal
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sarah R. Reves
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jesse C. Crosson
the Department of Biostatistics, Virginia Commonwealth University, Richmond (RTS); Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (RTS, RSE, MMG, NJJ, JPO, SRR); TMF Health Quality Institute, Austin, TX (JCC).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

References

  1. 1.↵
    Centers for Medicare & Medicaid Services. Comprehensive Primary Care Plus. Available from: https://innovation.cms.gov/initiatives/comprehensive-primary-care-plus/index.html. Updated July 21, 2020.
  2. 2.↵
    1. Bruggen RV,
    2. Gorter K,
    3. Stolk R,
    4. Klungel O,
    5. Rutten G
    . Clinical inertia in general practice: widespread and related to the outcome of diabetes care. Fam Pract 2009;26:428–36.
    OpenUrlCrossRefPubMedWeb of Science
  3. 3.↵
    1. Norris SL,
    2. Nichols PJ,
    3. Caspersen CJ,
    4. et al
    . The effectiveness of disease and case management for people with diabetes. A systematic review. Am J Prev Med 2002;22:15–38.
    OpenUrlPubMedWeb of Science
  4. 4.↵
    1. Reach G,
    2. Pechtner V,
    3. Gentilella R,
    4. Corcos A,
    5. Ceriello A
    . Clinical inertia and its impact on treatment intensification in people with type 2 diabetes mellitus. Diabetes Metab 2017;43:501–11.
    OpenUrlPubMed
  5. 5.↵
    1. Schmittdiel J,
    2. Uratsu C,
    3. Karter A,
    4. et al
    . Why don't diabetes patients achieve recommended risk factor targets? Poor adherence versus lack of treatment intensification. J Gen Intern Med 2008;23:588–94.
    OpenUrlCrossRefPubMedWeb of Science
  6. 6.↵
    1. Bodenheimer T,
    2. Wagner E,
    3. Grumbach K
    . Improving primary care for patients with chronic illness. JAMA 2002;288:1775–9.
    OpenUrlCrossRefPubMedWeb of Science
  7. 7.↵
    1. Hibbard JH,
    2. Greene J
    . What the evidence shows about patient activation: better health outcomes and care experiences; fewer data on costs. Health Aff (Millwood) 2013;32:207–14.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Strickland P,
    2. Hudson S,
    3. Piasecki A,
    4. et al
    . Features of the Chronic Care Model (CCM) associated with behavioral counseling and diabetes care in community primary care. J Am Board Fam Med 2010;23:295–305.
    OpenUrlAbstract/FREE Full Text
  9. 9.↵
    1. McCulloch D,
    2. Price M,
    3. Hindmarsh M,
    4. Wagner E
    . A population-based approach to diabetes management in a primary care setting: early results and lessons learned. Eff Clin Pract 1998;1:12–22.
    OpenUrlPubMed
  10. 10.↵
    1. Nutting P,
    2. Dickinson W,
    3. Dickinson L,
    4. et al
    . Use of chronic care model elements is associated with higher-quality care for diabetes. Ann Fam Med 2007;5:14–20.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. Peterson K,
    2. Radosevich D,
    3. O'Connor P,
    4. et al
    . Improving diabetes care in practice: findings from the TRANSLATE trial. Diabetes Care 2008;31:2238–43.
    OpenUrlAbstract/FREE Full Text
  12. 12.↵
    1. Stroebel R,
    2. Scheitel S,
    3. Fitz J,
    4. et al
    . A randomized trial of three diabetes registry implementation strategies in a community internal medicine practice. Jt Comm J Qual Improv 2002;28:441–50.
    OpenUrlPubMed
  13. 13.↵
    1. Hoque DME,
    2. Kumari V,
    3. Hoque M,
    4. Ruseckaite R,
    5. Romero L,
    6. Evans SM
    . Impact of clinical registries on quality of patient care and clinical outcomes: a systematic review. PLoS One 2017;12:e0183667.
    OpenUrl
  14. 14.↵
    1. Balasubramanian B
    . Use of patient registries in U.S. primary care practices. Am Fam Physician 2007;75:1629.
    OpenUrlPubMedWeb of Science
  15. 15.↵
    1. Schmittdiel J,
    2. Bodenheimer T,
    3. Solomon NA,
    4. Gillies RR,
    5. Shortell SM
    . Brief report: the prevalence and use of chronic disease registries in physician organizations. A national survey. J Gen Intern Med 2005;20:855–8.
    OpenUrlCrossRefPubMedWeb of Science
  16. 16.↵
    1. Etz RS,
    2. Keith RE,
    3. Maternick AM,
    4. Stein KL,
    5. et al
    . Supporting Practices to Adopt Registry-Based Care (SPARC): protocol for a randomized controlled trial. Implement Sci 2015;10:46.
    OpenUrl
  17. 17.↵
    Virginia Commonwealth University. Virginia Ambulatory Care Outcomes Research Network. Available from: http://acornpbrn.org/.
  18. 18.↵
    Standards of medical care in diabetes—2015: summary of revisions. Diabetes Care 2015;38:S4.
    OpenUrlFREE Full Text
  19. 19.↵
    1. Bonomi A,
    2. Wagner E,
    3. Glasgow R,
    4. VonKorff M
    . Assessment of chronic illness care (ACIC): a practical instrument to measure quality improvement. Health Serv Res 2002;37:791–820.
    OpenUrlCrossRefPubMedWeb of Science
  20. 20.↵
    1. Kaissi A,
    2. Parchman M
    . Assessing chronic illness care for diabetes in primary care clinics. Jt Comm J Qual Patient Saf 2006;32:318–23.
    OpenUrlPubMed
  21. 21.↵
    1. Pilla S,
    2. Segal J,
    3. Maruthur N
    . Primary care provides the majority of outpatient care for patients with diabetes in the US: NAMCS 2009–2015. J Gen Intern Med 2019;34:1089–91.
    OpenUrl
  22. 22.↵
    1. Ricci-Cabello I,
    2. Ruiz-Perez I,
    3. Rojas-García A,
    4. Pastor G,
    5. Gonçalves D
    . Improving diabetes care in rural areas: a systematic review and meta-analysis of quality improvement interventions in OECD countries. PLoS One 2013;8:e84464.
    OpenUrlCrossRef
  23. 23.↵
    1. Keith R,
    2. Etz R,
    3. Johnson N,
    4. Gonzalez M,
    5. O'Neal J,
    6. Crosson J
    . Barriers and facilitators to implementing a diabetes registry in 14 primary care practices. Montreal, Quebec, Canada: North American Primary Care Research Group Annual Meeting; 2017.
PreviousNext
Back to top

In this issue

The Journal of the American Board of Family     Medicine: 33 (5)
The Journal of the American Board of Family Medicine
Vol. 33, Issue 5
September/October 2020
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on American Board of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Low-Intensity Intervention Supports Diabetes Registry Implementation: A Cluster-Randomized Trial in the Ambulatory Care Outcomes Research Network (ACORN)
(Your Name) has sent you a message from American Board of Family Medicine
(Your Name) thought you would like to see the American Board of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
11 + 7 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Low-Intensity Intervention Supports Diabetes Registry Implementation: A Cluster-Randomized Trial in the Ambulatory Care Outcomes Research Network (ACORN)
Roy T. Sabo, Rebecca S. Etz, Martha M. Gonzalez, Nicole J. Johnson, Jonathan P. O'Neal, Sarah R. Reves, Jesse C. Crosson
The Journal of the American Board of Family Medicine Sep 2020, 33 (5) 728-735; DOI: 10.3122/jabfm.2020.05.190455

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Low-Intensity Intervention Supports Diabetes Registry Implementation: A Cluster-Randomized Trial in the Ambulatory Care Outcomes Research Network (ACORN)
Roy T. Sabo, Rebecca S. Etz, Martha M. Gonzalez, Nicole J. Johnson, Jonathan P. O'Neal, Sarah R. Reves, Jesse C. Crosson
The Journal of the American Board of Family Medicine Sep 2020, 33 (5) 728-735; DOI: 10.3122/jabfm.2020.05.190455
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Methods
    • Results
    • Discussion
    • Acknowledgments
    • Notes
    • References
  • Figures & Data
  • Info & Metrics
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • The Changing Face of Primary Care Research and Practice-Based Research Networks (PBRNs) in Light of the COVID-19 Pandemic
  • Google Scholar

More in this TOC Section

  • Increasing Primary Care Utilization of Medication-Assisted Treatment (MAT) for Opioid Use Disorder
  • Priorities for Artificial Intelligence Applications in Primary Care: A Canadian Deliberative Dialogue with Patients, Providers, and Health System Leaders
  • Perceptions of Artificial Intelligence Use in Primary Care: A Qualitative Study with Providers and Staff of Ontario Community Health Centres
Show more Original Research

Similar Articles

Keywords

  • Chronic Disease
  • Electronic Health Records
  • Guideline Adherence
  • Mentors
  • Type 2 Diabetes
  • Organizational Innovation
  • Practice-Based Research
  • Primary Health Care
  • Registries
  • Virginia

Navigate

  • Home
  • Current Issue
  • Past Issues

Authors & Reviewers

  • Info For Authors
  • Info For Reviewers
  • Submit A Manuscript/Review

Other Services

  • Get Email Alerts
  • Classifieds
  • Reprints and Permissions

Other Resources

  • Forms
  • Contact Us
  • ABFM News

© 2023 American Board of Family Medicine

Powered by HighWire