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
    • The Editing Fellowship
    • 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
    • The Editing Fellowship
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • JABFM on Bluesky
  • JABFM On Facebook
  • JABFM On Twitter
  • JABFM On YouTube
Research ArticleOriginal Research

Development of PRAPARE Social Determinants of Health Clusters and Correlation with Diabetes and Hypertension Outcomes

Wen Wan, Vivian Li, Marshall H. Chin, David N. Faldmo, Erin Hoefling, Michelle Proser and Rosy Chang Weir
The Journal of the American Board of Family Medicine July 2022, 35 (4) 668-679; DOI: https://doi.org/10.3122/jabfm.2022.04.200462
Wen Wan
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vivian Li
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
MS
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marshall H. Chin
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
MD, MPH
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David N. Faldmo
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
PA-C, MPAS
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Erin Hoefling
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
RN
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michelle Proser
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rosy Chang Weir
From University of Chicago, Chicago, IL (WW, MHC); Association of Asian Pacific Community Health Organizations, San Francisco, CA (VL, RCW); Siouxland Community Health Center, Sioux City, IA (DF, EH); National Association of Community Health Centers, Bethesda, MD (MP).
PhD
  • 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.↵
    1. Hill-Briggs F,
    2. Adler NE,
    3. Berkowitz SA,
    4. et al
    . Social determinants of health and diabetes: a scientific review. Diabetes Care. 2021;44:258–79.
    OpenUrlFREE Full Text
  2. 2.↵
    1. Razon N,
    2. Hessler D,
    3. Bibbins-Domingo K,
    4. Gottlieb L
    . How hypertension guidelines address social determinants of health: a systematic scoping review. Med Care. 2021;59:1122–9.
    OpenUrl
  3. 3.↵
    National Association of Community Health Centers [Internet]. 2013. The Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences (PRAPARE) by National Association of Community Health Centers, Association of Asian Pacific Community Health Organizations, and Oregon Primary Care Association. Available from: http://www.nachc.org/prapare.
  4. 4.↵
    Centers for Disease Control and Prevention [Internet]. International Classification of Diseases, (ICD-10-CM/PCS) transition—background. Centers for Medicare and Medicaid Services (CMS); 2015. Available from: https://www.cdc.gov/nchs/icd/icd10cm_pcs_background.htm.
  5. 5.↵
    Logical Observation Identifiers Names and Codes [Internet]. 1996. LOINC content. Available from: https://loinc.org/content/.
  6. 6.↵
    Uniform Data System [Internet]. Uniform Data System (UDS) resources. 1996. Health Resources & Services Administration. Available from: https://bphc.hrsa.gov/datareporting/reporting/index.html.
  7. 7.↵
    National Association of Community Health Centers [Internet]. Translated versions of PRAPARE. Available from: http://www.nachc.org/research-and-data/prapare/about-the-prapare-assessment-tool/.
  8. 8.↵
    1. Moore J,
    2. Adams C,
    3. Tuck K
    [Internet]. Results from the Institute for Medicaid Innovation's 2019 Annual Medicaid Managed Care Survey; 2019. Institute for Medicaid Innovation. Available from: https://www.medicaidinnovation.org/_images/content/2019_Annual_Medicaid_MCO_Survey_Results_FINAL.pdf.
  9. 9.↵
    1. Weir RC,
    2. Proser M,
    3. Jester M,
    4. Li V,
    5. Hood-Ronick CM,
    6. Gurewich D
    . Collecting social determinants of health data in the clinical setting: findings from national PRAPARE implementation. J Health Care Poor Underserved 2020;31:1018–35.
    OpenUrlPubMed
  10. 10.↵
    1. Saloner B,
    2. Wilk AS,
    3. Levin J
    . Community health centers and access to care among underserved populations: a synthesis review. Med Care Res Rev 2020;77:3–18.
    OpenUrl
  11. 11.↵
    1. Adashi EY,
    2. Geiger HJ,
    3. Fine MD
    . Health care reform and primary care–the growing importance of the community health center. N Engl J Med 2010;362:2047–50.
    OpenUrlCrossRefPubMedWeb of Science
  12. 12.↵
    1. Braveman P,
    2. Gottlieb L
    . The social determinants of health: it's time to consider the causes of the causes. Public Health Rep 2014;129 Suppl 2:19–31.
    OpenUrlCrossRefPubMed
  13. 13.↵
    1. Shin P,
    2. Alvarez C,
    3. Sharac J,
    4. et al.
    [Internet]. A profile of community health center patients: implications for policy. Kaiser Family Foundation; 2013. Available from: https://www.kff.org/medicaid/issue-brief/a-profile-of-community-health-center-patients-implications-for-policy/.
  14. 14.↵
    1. O'Malley AS,
    2. Rich EC,
    3. Sarwar R,
    4. et al
    . How accountable care organizations use population segmentation to care for high-need, high-cost patients. Issue Brief (Commonw Fund) 2019;2019:1–17.
    OpenUrl
  15. 15.↵
    1. Johnson D,
    2. Saavedra P,
    3. Sun E,
    4. et al
    . Community health workers and Medicaid managed care in New Mexico. J Community Health 2012;37:563–71.
    OpenUrlCrossRefPubMed
  16. 16.↵
    1. Coe EH,
    2. Cordina J,
    3. Parmar S
    [Internet]. Insights from McKinsey's Consumer Social Determinants of Health Survey. McKinsey & Company; 2019. Available from: https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/insights-from-the-mckinsey-2019-consumer-social-determinants-of-health-survey.
  17. 17.↵
    AmeriHealth Caritas [Internet]. AmeriHealth Caritas' inclusion of community health-based services reduces emergency room utilization; 2019. Available from: https://www.amerihealthcaritas.com/news/2019/071819-er-utilization.aspx.
  18. 18.↵
    National Association of Community Health Centers, Association of Asian Pacific Community Health Organizations, Oregon Primary Care Association [Internet]. Measuring patient social risk to drive care transformation: the development of PRAPARE; 2021. Available from: https://wsd-nachc-sparkinfluence.s3.amazonaws.com/uploads/2021/08/factsheet-PRAPARE-Process_07.23.21.pdf.
  19. 19.↵
    1. Weaver B,
    2. Maxwell H
    . Exploratory factor analysis and reliability analysis with missing data: a simple method for SPSS users. TQMP 2014;10:143–52.
    OpenUrl
  20. 20.↵
    1. Sijtsma K
    . On the use, the misuse, and the very limited usefulness of Cronbach's alpha. Psychometrika 2009;74:107–20.
    OpenUrlCrossRefPubMedWeb of Science
  21. 21.↵
    1. Trizano-Hermosilla I,
    2. Alvarado JM
    . Best alternatives to Cronbach's alpha reliability in realistic conditions: congeneric and asymmetrical measurements. Front Psychol 2016;7:769.
    OpenUrlPubMed
  22. 22.↵
    1. Grigsby TJ
    . Development and psychometric properties of the tobacco and nicotine consequences scale (TANCS) to screen for cigarette and e-cigarette misuse in community settings. Addict Behav 2019;98:106058.
    OpenUrl
  23. 23.↵
    1. Francis JE,
    2. White L
    . Pirqual: a scale for measuring customer expectations and perceptions of quality in internet retailing. American Marketing Association Winter Educators' Conference 2002;13:263–9.
    OpenUrl
  24. 24.↵
    1. Kim S,
    2. Stoel L
    . Apparel retailers: website quality dimensions and satisfaction. J Retailing Consumer Services 2004;11:109–17.
    OpenUrl
  25. 25.↵
    UCLA [Internet]. 2021. Factor analysis, SAS annotated output. Institute for Digital Research & Education Statistical Consulting. Available from: https://stats.idre.ucla.edu/sas/output/factor-analysis/.
  26. 26.↵
    1. Hooper D,
    2. Coughlan J,
    3. Mullen M
    . Structural equation modelling: guidelines for determining model fit. J Business Research Methods 2008;53–60.
  27. 27.↵
    1. Horn JL,
    2. McArdle JJ,
    3. Mason R
    . When invariance is not invariant: a practical scientist's view of the ethereal concept of factorial invariances. Southern Psychologist 1983;179–88.
  28. 28.↵
    1. Estabrook R,
    2. Neale M
    . A comparison of factor score estimation methods in the presence of missing data: reliability and an application to nicotine dependence. Multivariate Behav Res 2013;48:1–27.
    OpenUrl
  29. 29.↵
    1. Parent MC
    . Handling item-level missing data: simpler is just as good. Counseling Psychologist 2013;41:568–600.
    OpenUrlCrossRefWeb of Science
  30. 30.↵
    1. Mazza GL,
    2. Enders CK,
    3. Ruehlman LS
    . Addressing item-level missing data: a comparison of proration and full information maximum likelihood estimation. Multivariate Behav Res 2015;50:504–19.
    OpenUrl
  31. 31.↵
    1. Browne MW,
    2. Cudeck R
    . Alternative ways of assessing model fit. Sociological Methods Research 1992;21:230–58.
    OpenUrlCrossRefWeb of Science
  32. 32.↵
    1. Baraldi AN,
    2. Enders CK
    . An introduction to modern missing data analyses. J Sch Psychol 2010;48:5–37.
    OpenUrlCrossRefPubMedWeb of Science
  33. 33.↵
    1. Gunter KE,
    2. Peek ME,
    3. Tanumihardjo JP,
    4. et al
    . Population health innovations and payment to address social needs among patients and communities with diabetes. Milbank Q. 2021;99:928–73.
    OpenUrl
  34. 34.↵
    National Association of Community Health Centers, Association of Asian Pacific Community Health Organizations, Oregon Primary Care Association [Internet]. Incorporating social determinants of health data into risk stratification models to address health inequities: the PRAPARE stakeholder-vetted risk stratification model; 2021. Available from: https://www.nachc.org/wp-content/uploads/2021/03/PRAPARE-RS-Fact-Sheet-3.30.21.pdf.
  35. 35.↵
    1. Muntner P,
    2. Hardy ST,
    3. Fine LJ,
    4. et al
    . Trends in blood pressure control among US adults with hypertension, 1999-2000 to 2017-2018. JAMA 2020;324:1190–200.
    OpenUrlPubMed
  36. 36.↵
    1. Reshetnyak E,
    2. Ntamatungiro M,
    3. Pinheiro LC,
    4. et al
    . Impact of multiple social determinants of health on incident stroke. Stroke 2020;51:2445–53.
    OpenUrl
  37. 37.↵
    1. Li V,
    2. McBurnie MA,
    3. Simon M,
    4. et al
    . Impact of social determinants of health on patients with complex diabetes who are served by national safety-net health centers. J Am Board Fam Med 2016;29:356–70.
    OpenUrlAbstract/FREE Full Text
  38. 38.↵
    1. Gottlieb LM,
    2. Wing H,
    3. Adler NE
    . A systematic review of interventions on patients' social and economic needs. Am J Prev Med 2017;53:719–29.
    OpenUrlCrossRefPubMed
  39. 39.↵
    National Association of Community Health Centers, Association of Asian Pacific Community Health Organizations, Oregon Primary Care Association [Internet]. Collecting social determinants of health data in the clinical setting: findings in high risk vs. general populations; 2021. Available from: https://wsd-nachc-sparkinfluence.s3.amazonaws.com/uploads/2021/08/factsheet-PRAPARE_high-risk_07.23.21.pdf.
  40. 40.↵
    1. Taylor LA,
    2. Tan AX,
    3. Coyle CE,
    4. et al
    . Leveraging the social determinants of health: what works? PLoS One 2016;11:e0160217.
    OpenUrlCrossRefPubMed
  41. 41.↵
    1. Ludwig J,
    2. Sanbonmatsu L,
    3. Gennetian L,
    4. et al
    . Neighborhoods, obesity, and diabetes—a randomized social experiment. N Engl J Med 2011;365:1509–19.
    OpenUrlCrossRefPubMedWeb of Science
  42. 42.↵
    1. Ogunniyi MO,
    2. Commodore-Mensah Y,
    3. Ferdinand KC
    . Race, ethnicity, hypertension, and heart disease: JACC Focus Seminar 1/9. J Am Coll Cardiol 2021;78:2460–70.
    OpenUrl
  43. 43.↵
    Association of Asian Pacific Community Health Organizations [Internet]. Enabling services data collection implementation packet; 2016. Available from: https://aapcho.org/enabling-services-data-collection-implementation-packet/?_ga=2.221344797.42374573.1639010358-925895610.1625172539.
  44. 44.↵
    1. Chang WR,
    2. Proser M
    . Highlighting the role of enabling services at community health centers: collecting data to support service expansion and enhanced funding. Association of Asian Pacific Community Health Organizations; 2010.
  45. 45.↵
    1. Chang WR,
    2. Emerson HP,
    3. Tseng W,
    4. et al
    . Use of enabling services by Asian American, Native Hawaiian, and other Pacific Islander patients at 4 community health centers. Am J Public Health 2010;100:2199–205.
    OpenUrlCrossRefPubMed
  46. 46.↵
    Health Resources & Services Administration [Internet]. 2020 patient characteristics snapshot; 2021. Available from: https://data.hrsa.gov/tools/data-reporting/data-snapshot.
PreviousNext
Back to top

In this issue

The Journal of the American Board of Family     Medicine: 35 (4)
The Journal of the American Board of Family Medicine
Vol. 35, Issue 4
July/August 2022
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
  • Back Matter (PDF)
  • 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.
Development of PRAPARE Social Determinants of Health Clusters and Correlation with Diabetes and Hypertension Outcomes
(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.
1 + 0 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Development of PRAPARE Social Determinants of Health Clusters and Correlation with Diabetes and Hypertension Outcomes
Wen Wan, Vivian Li, Marshall H. Chin, David N. Faldmo, Erin Hoefling, Michelle Proser, Rosy Chang Weir
The Journal of the American Board of Family Medicine Jul 2022, 35 (4) 668-679; DOI: 10.3122/jabfm.2022.04.200462

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Development of PRAPARE Social Determinants of Health Clusters and Correlation with Diabetes and Hypertension Outcomes
Wen Wan, Vivian Li, Marshall H. Chin, David N. Faldmo, Erin Hoefling, Michelle Proser, Rosy Chang Weir
The Journal of the American Board of Family Medicine Jul 2022, 35 (4) 668-679; DOI: 10.3122/jabfm.2022.04.200462
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

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

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Family Medicine Researchers Explore the Social Determinants of Health, COVID-19 Issues, and Cancer Survivor Care
  • Google Scholar

More in this TOC Section

  • Evaluating Pragmatism of Lung Cancer Screening Randomized Trials with the PRECIS-2 Tool
  • Perceptions and Preferences for Defining Biosimilar Products in Prescription Drug Promotion
  • Successful Implementation of Integrated Behavioral Health
Show more Original Research

Similar Articles

Keywords

  • Community Health Centers
  • Cross-Sectional Studies
  • Diabetes Mellitus
  • HbA1c
  • Hypertension
  • Logistic Models
  • Risk Factors
  • Social Determinants of Health
  • Vulnerable Populations

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

© 2025 American Board of Family Medicine

Powered by HighWire