Covid-19 Research

Original Article

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The Veterans Affairs Lipid Optimization Reimagined - Quality Improvement Program Rationale and Methods

Medicine Group    Start Submission

Abigail A Santos*, Jennifer DelGrande, Abigail Fink, Juhi Seth, Courtney Bonnema, Rachel Ward, Helen M Wellman, Nedim Yel, Mason Coleman Lopez, Dakotah Feil, Sharon Sharnprapai, Kristin Colson, Eddie Pan, Tharen Leesch, David Pena, Michelle Congdon, Michele Bolles, Luc Djousse and John Michael Gaziano

Volume6-Issue7
Dates: Received: 2025-07-19 | Accepted: 2025-07-25 | Published: 2025-07-27
Pages: 929-937

Abstract

Background: Atherosclerotic cardiovascular disease (ASCVD) is a major contributor to morbidity and mortality in United States (US) Veterans and to healthcare costs in the United States Veterans Affairs (VA) Healthcare System. Optimizing Low-Density Lipoprotein Cholesterol (LDL-C) can improve Veteran health, reduce incidence of cardiovascular events and death, and lower healthcare costs.

Methods: The VA Lipid Optimization Reimagined - Quality Improvement (VALOR-QI) program is an innovative three-year multi-site quality improvement program leveraging various lipid optimization strategies tailored to unique barriers and needs at 50 VA Medical Centers. Program oversight is provided by the Boston VA Coordinating Center and the American Heart Association (AHA), and local teams include a site lead or Clinical Champion (CC), a Healthcare Coach (HC), and a Health Care Provider Network (HCPN) of clinicians treating Veterans with ASCVD. Outcome data are collected through the VA electronic health record database and QI data are collected through the VA Research Electronic Data Capture (REDCap) system. Primary and secondary outcomes include the percentage of Veterans with optimized LDL-C (<70 mg/dL), absolute and percent change in LDL-C, use of lipid lowering therapies, medication adherence, cardiovascular risk score, and healthcare utilization and costs. Lipid optimization outcomes will be stratified by key Veteran demographics including geographic region, age, sex assigned at birth, race, and ethnicity.

Results: N/A- Program still in progress

Conclusions: We will assess whether a novel quality improvement program can optimize lipids in Veterans with ASCVD at high risk for cardiovascular events, with subsequent improvement of Veterans’ health and reduction of costs for US Veterans and the VA Healthcare System. Findings from this program can inform clinical processes and guidelines for the VA Healthcare System and other healthcare systems alike.

FullText HTML FullText PDF DOI: 10.37871/jbres2147


Certificate of Publication




Copyright

© 2025 Santos AA, et al, Distributed under Creative Commons CC-BY 4.0

How to cite this article

Santos AA, DelGrande J, Fink A, Seth J, Bonnema C, Ward R, Wellman HM, Yel N, Lopez MC, Feil D, Sharnprapai S, Colson K, Pan E, Leesch T, Peña D, Congdon M, Bolles M, Djoussé L, Gaziano JM. The Veterans Affairs Lipid Optimization Reimagined - Quality Improvement Program: Rationale and Methods. J Biomed Res Environ Sci. 2025 Jul 27; 6(7): 929-937. doi: 10.37871/jbres2147, Article ID: JBRES2147, Available at: https://www.jelsciences.com/articles/jbres2147.pdf


Subject area(s)

References


  1. Assari S. Veterans and risk of heart disease in the United States: a cohort with 20 years of follow up. Int J Prev Med. 2014 Jun;5(6):703-9. PMID: 25013689; PMCID: PMC4085922.
  2. Eibner C, Krull H, Brown KM, Cefalu M, Mulcahy AW, Pollard M, Shetty K, Adamson DM, Amaral EF, Armour P, Beleche T, Bogdan O, Hastings J, Kapinos K, Kress A, Mendelsohn J, Ross R, Rutter CM, Weinick RM, Woods D, Hosek SD, Farmer CM. Current and Projected Characteristics and Unique Health Care Needs of the Patient Population Served by the Department of Veterans Affairs. Rand Health Q. 2016 May 9;5(4):13. PMID: 28083423; PMCID: PMC5158228.
  3. Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC Jr, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019 Jun 18;139(25):e1082-e1143. doi: 10.1161/CIR.0000000000000625. Epub 2018 Nov 10. Erratum in: Circulation. 2019 Jun 18;139(25):e1182-e1186. doi: 10.1161/CIR.0000000000000698. Erratum in: Circulation. 2023 Aug 15;148(7):e5. doi: 10.1161/CIR.0000000000001172. PMID: 30586774; PMCID: PMC7403606.
  4. Sandesara PB, Virani SS, Fazio S, Shapiro MD. The Forgotten Lipids: Triglycerides, Remnant Cholesterol, and Atherosclerotic Cardiovascular Disease Risk. Endocr Rev. 2019 Apr 1;40(2):537-557. doi: 10.1210/er.2018-00184. PMID: 30312399; PMCID: PMC6416708.
  5. Virani SS, Akeroyd JM, Smith SC Jr, Al-Mallah M, Maddox TM, Morris PB, Petersen LA, Ballantyne CM, Grundy SM, Stone NJ. Very High-Risk ASCVD and Eligibility for Nonstatin Therapies Based on the 2018 AHA/ACC Cholesterol Guidelines. J Am Coll Cardiol. 2019 Aug 6;74(5):712-714. doi: 10.1016/j.jacc.2019.05.051. PMID: 31370962.
  6. Virani SS, Akeroyd JM, Nambi V, Heidenreich PA, Morris PB, Nasir K, Michos ED, Bittner VA, Petersen LA, Ballantyne CM. Estimation of Eligibility for Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitors and Associated Costs Based on the FOURIER Trial (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk): Insights From the Department of Veterans Affairs. Circulation. 2017 Jun 20;135(25):2572-2574. doi: 10.1161/CIRCULATIONAHA.117.028503. Epub 2017 May 2. PMID: 28465286.
  7. Al Rifai M, Blumenthal RS, Stone NJ, Schofield RS, Orringer CE, Michos ED, Heidenreich PA, Braun L, Birtcher KK, Smith SC, Nambi V, Grundy S, Virani SS. Department of Veterans Affairs (VA) and U.S. Department of Defense (DoD) guidelines for management of dyslipidemia and cardiovascular disease risk reduction: Putting evidence in context. Prog Cardiovasc Dis. 2021 Sep-Oct;68:2-6. doi: 10.1016/j.pcad.2021.08.001. Epub 2021 Aug 8. PMID: 34371083.
  8. O'Malley PG, Arnold MJ, Kelley C, Spacek L, Buelt A, Natarajan S, Donahue MP, Vagichev E, Ballard-Hernandez J, Logan A, Thomas L, Ritter J, Neubauer BE, Downs JR. Management of Dyslipidemia for Cardiovascular Disease Risk Reduction: Synopsis of the 2020 Updated U.S. Department of Veterans Affairs and U.S. Department of Defense Clinical Practice Guideline. Ann Intern Med. 2020 Nov 17;173(10):822-829. doi: 10.7326/M20-4648. Epub 2020 Sep 22. PMID: 32956597.
  9. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377-81. doi: 10.1016/j.jbi.2008.08.010. Epub 2008 Sep 30. PMID: 18929686; PMCID: PMC2700030.
  10. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN; REDCap Consortium. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019 Jul;95:103208. doi: 10.1016/j.jbi.2019.103208. Epub 2019 May 9. PMID: 31078660; PMCID: PMC7254481.
  11. Obeid JS, McGraw CA, Minor BL, Conde JG, Pawluk R, Lin M, Wang J, Banks SR, Hemphill SA, Taylor R, Harris PA. Procurement of shared data instruments for Research Electronic Data Capture (REDCap). J Biomed Inform. 2013 Apr;46(2):259-65. doi: 10.1016/j.jbi.2012.10.006. Epub 2012 Nov 10. PMID: 23149159; PMCID: PMC3600393.
  12. https://dvagov.sharepoint.com/sites/OITBISL/SitePages/BISL%20Bulletin/Data-Quality-in-the-CDW.aspx


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