Journal of General Internal Medicine

, Volume 21, Issue 10, pp 1050–1056

Simultaneous control of intermediate diabetes outcomes among veterans affairs primary care patients

  • George L. Jackson
  • David Edelman
  • Morris Weinberger
Original Articles


BACKGROUND: Guidelines recommend tight control of hemoglobin Alc (HbAlc), low-density lipoprotein cholesterol (LDL-C), and blood pressure (BP) for patients with diabetes. The degree to which these intermediate outcomes are simultaneously controlled has not been extensively described.

OBJECTIVE: Describe the degree of simultaneous control of HbAlc, LDL-C, and BP among Veterans Affairs (VA) diabetes patients defined by both VA and American Diabetes Association (ADA) guidelines.

DESIGN: Cross-sectional cohort.

PATIENTS: Eighty-thousand two hundred and seven VA diabetes patients receiving care between October 1999 and September 2000.

MEASURMENTS: We defined simultaneous control of outcomes using 1997 VA Guidelines (in place in 2000) (HbAlc<9.0%; LDL-C<130 mg/dL; systolic BP<140mmHg; and diastolic BP<90mmHg) and 2004 ADA guidelines (HbAlc<7.0%; LDL-C<100 mg/dL; systolic BP<130 mmHg; and diastolic BP<80 mmHg). A patient is considered to have simultaneous control of the intermediate outcomes for a given definition if the average of measurements for each outcome was below the defined threshold during the study period.

RESULTS: Using VA guidelines, 31% of patients had simultaneous control. Control levels of individual outcomes were: HbAlc (82%), LDL-C (77%), and BP (48%). Using ADA guidelines, 4% had simultaneous control. Control levels of individual outcomes were: HbAlc (36%), LDL-C (41%), and BP (23%). Associations between individual risk factors were weak. There was a modest association between LDL-C control and control of HbAlc (odds ratio [OR] 1.51; 95% confidence interval [CI] 1.44, 1.58). The association between LDL-C and BP control was clinically small (1.26: 1.21, 1.31), and there was an extremely small association between BP and HbAlc control (0.95; 0.92, 0.99). Logistic regression modeling indicates greater body mass index, African American or Hispanic race-ethnicity, and female gender were negatively associated with simultaneous control.

CONCLUSION: While the proportion of patients who achieved minimal levels of control of HbAlc and LDL-C was high, these data indicate a low level of simultaneous control of HbAlc, LDL-C, and BP among patients with diabetes.

Key words

blood pressure diabetes mellitus hemoglobin A-glycosylated lipoproteins-LDL cholesterol United States Department of Veterans Affairs 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Khaw K-T, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin Alc with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Ann Intern Med. 2004;141:413–20.PubMedGoogle Scholar
  2. 2.
    Selvin E, Marinoppulos S, Berkenblit G, et al. Meta-analysis. Glycosylated hemoglobin and cardiovascular disease in diabetes mellitus. Ann Intern Med. 2004;141:421–31.PubMedGoogle Scholar
  3. 3.
    Stratton IM, Adler AI, Neil HAW, et al. Association of glycemia with macrovascular and microvascular conditions of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321:405–12.PubMedCrossRefGoogle Scholar
  4. 4.
    Vijan S, Hayward RA. Pharmacologic lipid-lowering therapy in type 2 diabetes mellitus: background paper for the American College of Physicians. Ann Intern Med. 2004;140:650–8.PubMedGoogle Scholar
  5. 5.
    Adler AI, Stratton IM, Neil HAW, et al. Association of systolic blood pressure with macrovascular and microvascular complication of type 2 diabetes (UKPDS 36): prospective observational study. BMJ. 2000;321:412–9.PubMedCrossRefGoogle Scholar
  6. 6.
    Snow V, Weiss KB, Mottur-Pilson C, for the Clinical Efficacy Assessment Subcommittee of the American College of Physicians. The evidence base for tight blood pressure control in the management of type 2 diabetes. Ann Intern Med. 2003;138:587–92.PubMedGoogle Scholar
  7. 7.
    Bruno G, Cavallo-Perin P, Bargero G, Borra M, D’Errico N, Pagano G. Glycaemic control and cardiovascular risk factors in type 2 diabetes: a population-based study. Diabetes Med. 1998;15:304–7.CrossRefGoogle Scholar
  8. 8.
    Harris MI. Health care and health status and outcomes for patients with type 2 diabetes. Diabetes Care. 2000;23:754–8.PubMedCrossRefGoogle Scholar
  9. 9.
    Saaddine JB, Engelgau MM, Beckles GL, Gregg EW, Thompson TJ, Narayan KMV. A diabetes report card for the United States: quality of care in the 1990s. Ann Intern Med. 2002;136:565–74.PubMedGoogle Scholar
  10. 10.
    Saydah SH, Fradkin J, Cowie CC. Poor control of risk factors for vascular disease among adults with previously diagnosed diabetes. JAMA. 2004;291:335–42.PubMedCrossRefGoogle Scholar
  11. 11.
    Smith NL, Savage PJ, Heckbert SR, et al. Glucose, blood pressure, and lipid control in older people with and without diabetes mellitus: the Cardiovascular Health Study. J Am Geriatr Soc. 2002;50:416–23.PubMedCrossRefGoogle Scholar
  12. 12.
    Heisler M, Smith DM, Hayward RA, Krein SL, Kerr EA. Racial disparities in diabetes care processes, outcomes, and treatment intensity. Med Care. 2003;41:1221–32.PubMedCrossRefGoogle Scholar
  13. 13.
    Kerr EA, Gerzoff RB, Krein SL, et al. Diabetes care quality in the Veterans Affairs health care system and commercial managed care: the TRIAD Study. Ann Intern Med. 2004;141:272–81.PubMedGoogle Scholar
  14. 14.
    Smith NL, Chen L, Au DH, McDonell M, Fihn SD. Cardiovascular risk factor control among veterans with diabetes. Diabetes Care. 2004;27:B33–8.PubMedCrossRefGoogle Scholar
  15. 15.
    Beaton SJ, Nag SS, Gunter MJ, Gleeson JM, Saigan SS, Alexander CM. Adequacy of glycemic, lipid, and blood pressure management for patients with diabetes in a managed care setting. Diabetes Care. 2004;27:694–8.PubMedCrossRefGoogle Scholar
  16. 16.
    Bouma M, Dekker JH, van Eijk JThM, Schellevis FG, Kriegsman DMW, Heine RJ. Metabolic control and morbidity of type 2 diabetic patients in a general practice network. Fam Pract. 1999;16:402–6.PubMedCrossRefGoogle Scholar
  17. 17.
    Kell SH, Drass J, Bausell B, Thomas KA, Osborn MA, Gohdes D. Measures of disease control in Medicare beneficiaries with diabetes mellitus. J Am Geriatr Soc. 1999;47:417–22.PubMedGoogle Scholar
  18. 18.
    Kim C, Williamson DF, Mangione CM, et al. Managed care organization and the quality of diabetes care. Diabetes Care. 2004;27:1529–34.PubMedCrossRefGoogle Scholar
  19. 19.
    McFarlane SI, Jacober SJ, Winer N, et al. Control of cardiovascular risk factors in patients with diabetes and hypertension at urban academic medical centers. Diabetes Care. 2002;25:718–23.PubMedCrossRefGoogle Scholar
  20. 20.
    Porterfield DS, Kinsinger L. Quality of care for uninsured patients with diabetes in a rural area. Diabetes Care. 2002;25:319–23.PubMedCrossRefGoogle Scholar
  21. 21.
    Putzer GJ, Ramirez AM, Sneed K, Brownlee HJ, Roetzheim RG, Campbell RJ. Prevalence of patients with type 2 diabetes mellitus reaching the American Diabetes Association’s target guidelines in a university primary care setting. South Med J. 2004;97:145–8.PubMedCrossRefGoogle Scholar
  22. 22.
    Wandell PE, Gafvels C. Metabolic controland quality of data in medical records for subjects with type 2 diabetes in Swedish primary care: improvement between 1995 and 2001. Scand J Prim Health Care. 2002;20:230–5.PubMedCrossRefGoogle Scholar
  23. 23.
    Narayan KMV, Benjamin E, Gregg EW, Norris SL, Engelgau MM. Diabetes translation research: where are we and where do we want to be. Ann Intern Med. 2004;140:958–63.PubMedGoogle Scholar
  24. 24.
    Renders CM, Calk GD, Griffin SJ, et al. Interventions to improve the management of diabetes in primary care, outpatient, and community settings, a systematic review. Diabetes Care. 2001;24:1821–33.PubMedCrossRefGoogle Scholar
  25. 25.
    Healthcare Analysis and Information Group, Quality Enhancement Research Initiative-Diabetes Mellitus. VA Diabetes Registry and Dataset [fact sheet], VA Ann Arbor QUERI-DM Research Coordinating Center, Ann Arbor, MI, November 22, 2002.Google Scholar
  26. 26.
    Hawley G: VIReC Briefing. HAIG Diabetes Projects [presentation available on the World Wide Web]. June 20, 2001. Available at: Accessed March 10, 2005.Google Scholar
  27. 27.
    Maynard C, Chapko MK. Data resources in the Department of Veterans Affairs. Diabetes Care. 2004;27:B22–6.PubMedCrossRefGoogle Scholar
  28. 28.
    Cowper DC, Kubal JD, Maynard C, Hynes DM. A primer and comparative review of major U.S. mortality databases. Ann Epidemiol. 2002;12:462–8.PubMedCrossRefGoogle Scholar
  29. 29.
    Agency for Healthcare Research and Quality. Clinical Classification Software (CCS), 2003, Software and User’s Guide; February, 2003. Available at: Accessed March 10, 2005.Google Scholar
  30. 30.
    Rosen AK, Trivedi P, Amuan M, Montez M. The Johns Hopkins Adjusted Clinical Groups (ACGs) Case-Mix System: a risk-adjustment methodology currently available at the VA Austin Automation Center. VIReC Insights, 2003;4:1–10. Available at: Accessed March 10, 2005.Google Scholar
  31. 31.
    Jackson GL, Yano EM, Edelman D, et al. Veterans affairs primary care organizational characteristics associated with better diabetes control. Am J Manage Care. 2005;11:225–50.Google Scholar
  32. 32.
    Leinung MC, Gianoukakis AG, Lee DW, Jeronis SL, Desemone J. Comparison of diabetes care provided by and endocrinology clinic and a primary-care clinic. Endocrine Pract. 2000;6:361–6.Google Scholar
  33. 33.
    Clark MJ Jr,Sterrett JJ, Carson DS. Diabetes guidelines. A summary comparison of the recommendations of the American Diabetes Association, Veterans Health Administration, and American Association of Clinical Endocrinologists. Clin Ther. 2000;22:899–910.PubMedCrossRefGoogle Scholar
  34. 34.
    American Diabetes Association. Clinical practice recommendations 2004. Diabetes Care. 2004;27:S1–150.CrossRefGoogle Scholar
  35. 35.
    SAS Institute Inc. SAS [computer program] Version 9.1. Cary, NC: SAS Institute Inc.: 2003.Google Scholar
  36. 36.
    Williams RL. A note on robust variance estimation for cluster-correlated data. Biometrics. 2000;56:645–6.PubMedCrossRefGoogle Scholar
  37. 37.
    StataCorp. Intercooled Stata [computer program] Version 8.2. College Station, TX: SAS Institute Inc.; 2004.Google Scholar
  38. 38.
    Asch SM, McGlynn EA, Hogan MM, et al. Comparison of quality of care for patients in the Veterans Health Administration and patients in a national sample. Ann Intern Med. 2004;141:938–45.PubMedGoogle Scholar
  39. 39.
    Clark NM. Management of chronic disease by patients. Ann Rev Public Health. 2003;24:289–313.CrossRefGoogle Scholar
  40. 40.
    Alexander SC, Sleath B, Golin CE, Kalinowski CT. Provider-patient communication and treatment adherence. In: Bosworth HB, Oddone EZ, Weinberger M, eds. Patient Treatment Adherence: Concepts, Interventions, and Measurement. Mahwah, NJ: Lawrence Erlbaum Associates; 2005:329–72.Google Scholar
  41. 41.
    Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension. 2003;42:1206–52.PubMedCrossRefGoogle Scholar
  42. 42.
    Cook CB, Ziemer DC, El-Kebbi IM, et al. Diabetes in urban African-Americans. XVI. Overcoming clinical inertia improves glycemic control in patients with type 2 diabetes. Diabetes Care. 1999;22:1494–500.PubMedCrossRefGoogle Scholar
  43. 43.
    Phillips LS, Branch WT, Cook CB, et al. Clinical inertia. Ann Intern Med. 2001;135:825–34.PubMedGoogle Scholar
  44. 44.
    Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ. 2005;31:564–71.PubMedCrossRefGoogle Scholar
  45. 45.
    Johnson CL, Rifkind BM, Sempos CT, et al. Declining serum total cholesterol levels, The National Health and Nutrition Examination Surveys. JAMA. 1993;269:3002–8.PubMedCrossRefGoogle Scholar
  46. 46.
    Joffres MR, Hamet P, MacLean DR, L’italien GJ, Fodor G. Distribution of blood pressure and hypertension in Canada and the United States. Am J Hypertens. 2001;14:1099–105.PubMedCrossRefGoogle Scholar
  47. 47.
    Dagogo-Jack S. Ethnic disparities in type 2 diabetes: pathophysiology and implications for prevention and management. J Natl Med Assoc. 2003;95:774, 779–89.PubMedGoogle Scholar
  48. 48.
    Acton KJ, Preston S, Rith-Najarian S. Clinical hypertension in Native Americans: a comparison of 1987 and 1992 rates from ambulatory care data. Public Health Rep. 1996;111:33–6.PubMedGoogle Scholar
  49. 49.
    Welty TK, Lee ET, Yeh J, et al. Cardiovascular disease risk factors among American Indians: the Strong Heart Study. Am J Epidemiol. 1995;142:269–87.PubMedGoogle Scholar
  50. 50.
    National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation. 2002;106:3143–421.Google Scholar
  51. 51.
    Perlin JB, Kolodner RM, Roswell RH. The Veterans Health Administration: quality, value, accountability, and information as transforming strategies for patient-centered care. Am J Manage Care. 2004;10:828–36.Google Scholar
  52. 52.
    Wagner EH, Austin BT, Von Korff M. Organizing care for patients with chronic illness. Milbank Q. 1996;74:511–44.PubMedCrossRefGoogle Scholar
  53. 53.
    Bosworth HB, Oddone EZ. A model of psychosocial and cultural antecedents of blood pressure control. J Natl Med Assoc. 2002;94:236–48.PubMedGoogle Scholar

Copyright information

© Society of General Internal Medicine 2006

Authors and Affiliations

  • George L. Jackson
    • 1
    • 2
  • David Edelman
    • 1
    • 2
  • Morris Weinberger
    • 1
    • 3
  1. 1.Durham Veterans Affairs Medical CenterHSR&D Service (152)Durham
  2. 2.Division of General Internal MedicineDuke UniversityDurhamUSA
  3. 3.Department of Health Policy and AdministrationUniversity of North Carolina at Chapel HillChapel HillUSA

Personalised recommendations