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Impact of Computerized Decision Support on Blood Pressure Management and Control: A Randomized Controlled Trial

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Abstract

BACKGROUND

We conducted a cluster randomized controlled trial to examine the effectiveness of computerized decision support (CDS) designed to improve hypertension care and outcomes in a racially diverse sample of primary care patients.

METHODS

We randomized 2,027 adult patients receiving hypertension care in 14 primary care practices to either 18 months of their physicians receiving CDS for each hypertensive patient or to usual care without computerized support for the control group. We assessed prescribing of guideline-recommended drug therapy and levels of blood pressure control for patients in each group and examined if the effects of the intervention differed by patients’ race/ethnicity using interaction terms.

MEASUREMENTS AND MAIN RESULTS

Rates of blood pressure control were 42% at baseline and 46% at the outcome visit with no significant differences between groups. After adjustment for patients’ demographic and clinical characteristics, number of prior visits, and levels of baseline blood pressure control, there were no differences between intervention groups in the odds of outcome blood pressure control. The use of CDS to providers significantly improved Joint National Committee (JNC) guideline adherent medication prescribing compared to usual care (7% versus 5%, P < 0.001); the effects of the intervention remained after multivariable adjustment (odds ratio [OR] 1.39 [CI, 1.13–1.72]) and the effects of the intervention did not differ by patients’ race and ethnicity.

CONCLUSIONS

CDS improved appropriate medication prescribing with no improvement in disparities in care and overall blood pressure control. Future work focusing on improvement of these interventions and the study of other practical interventions to reduce disparities in hypertension-related outcomes is needed.

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References

  1. Anonymous. The sixth report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Arch Intern Med. 1997;157:2413–46.

    Article  Google Scholar 

  2. Berlowitz DR, Ash AS, Hickey EC, et al. Inadequate management of blood pressure in a hypertensive population. N Engl J Med. 1998;339:1957–63.

    Article  PubMed  CAS  Google Scholar 

  3. Hyman DJ, Pavlik VN. Self-reported hypertension treatment practices among primary care physicians: blood pressure thresholds, drug choices, and the role of guidelines and evidence-based medicine. Arch Intern Med. 2000;160:2281–6.

    Article  PubMed  CAS  Google Scholar 

  4. Oliveria SA, Lapuerta P, McCarthy BD, L’Italien GJ, Berlowitz DR, Asch SM. Physician-related barriers to the effective management of uncontrolled hypertension. Arch Intern Med. 2002;162:413–20.

    Article  PubMed  Google Scholar 

  5. Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988–2000. JAMA. 2003;290:199–206.

    Article  PubMed  Google Scholar 

  6. Chobanian AV, Bakris GL, Black HR, et al. The seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289:2560–72.

    Article  PubMed  CAS  Google Scholar 

  7. Sundquist J, Winkleby MA, Pudaric S. Cardiovascular disease risk factors among older black, Mexican-American, and white women and men: an analysis of NHANES III, 1988–1994. Third National Health and Nutrition Examination Survey. J Am Geriatr Soc. 2001;49:109–16.

    Article  PubMed  CAS  Google Scholar 

  8. Hyman DJ, Pavlik VN. Characteristics of patients with uncontrolled hypertension in the United States. N Engl J Med. 2001;345:479–86.

    Article  PubMed  CAS  Google Scholar 

  9. Materson BJ. Lessons on the interaction of race and anti-hypertensive drugs from the VA cooperative study group on anti-hypertensive agents. Am J Hypertension. 1995;8:91s–3s.

    Article  CAS  Google Scholar 

  10. Richardson AD, Piepho RW. Effect of race on hypertension and anti-hypertensive therapy. Int J Clin Pharmacol Ther. 2000;38:75–9.

    PubMed  CAS  Google Scholar 

  11. He J, Klag MJ, Caballero B, Appel LJ, Charleston J, Whelton PK. Plasma insulin levels and incidence of hypertension in African Americans and Whites. Arch Intern Med. 1999;159:498–503.

    Article  PubMed  CAS  Google Scholar 

  12. Wong MD, Shapiro MF, Boscardin WJ, Ettner SL. Contribution of major diseases to disparities in mortality. N Engl J Med. 2002;347:1585–92.

    Article  PubMed  Google Scholar 

  13. Hyman DJ, Pavlik VN. Uncontrolled hypertension as a risk for coronary artery disease: patient characteristics and the role of physician intervention. Diabetes Care. 2003;26:355–9.

    Article  Google Scholar 

  14. Hicks LS, Fairchild DG, Horng MS, Orav EJ, Bates DW, Ayanian JZ. Determinants of JNC VI guideline adherence, intensity of drug therapy, and blood pressure control by race and ethnicity. Hypertension. 2004;44:429–34.

    Article  PubMed  CAS  Google Scholar 

  15. Cooper LA, Hill MN, Powe N. Designing and evaluating interventions to eliminate racial and ethnic disparities in health care. J Gen Intern Med. 2002;17:477–86.

    Article  PubMed  Google Scholar 

  16. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington: National Academy Press; 2003.

    Google Scholar 

  17. Groman R, Ginsburg J, for the American College of Physicians. Racial and ethnic disparities in health care: a position paper of the American College of Physicians. Ann Intern Med. 2004;141:226–32.

    PubMed  Google Scholar 

  18. Sequist TD, Gandhi TK, Karson AS, et al. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. J Am Med Inform Assoc. 2005;12:431–7.

    Article  PubMed  Google Scholar 

  19. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. A systematic review. JAMA. 2005;293:1223–38.

    Article  PubMed  CAS  Google Scholar 

  20. Tierney WM, Overhage JM, Murray MD, et al. Effects of computerized guidelines for managing heart disease in primary care. J Gen Intern Med. 2003;18:967–76.

    Article  PubMed  Google Scholar 

  21. Nilasena DS, Lincoln MJ. A computer-generated reminder system improves physician compliance with diabetes preventive care guidelines. Proc Annu Symp Comput Appl Med Care. 1995;640–5.

  22. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 1998;280:1339–46.

    Article  PubMed  CAS  Google Scholar 

  23. Shea S, DuMouchel W, Bahamonde L. A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. J Am Med Inform Assoc. 1996;3:399–409.

    PubMed  CAS  Google Scholar 

  24. Tunis SR, Stryer DB, Clancy CM. Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003;290:1624–32.

    Article  PubMed  CAS  Google Scholar 

  25. Smith SC Jr, Blair SN, Bonow RO, et al. AHA/ACC scientific statement: AHA/ACC guidelines for preventing heart attack and death in patients with atherosclerotic cardiovascular disease: 2001 update: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation. 2001;104:1577–79.

    Article  PubMed  Google Scholar 

  26. Quality compass 2003. Washington, DC: National Committee for Quality Assurance, 2003 (computer disk).

  27. Frane J. SUDAAN: Professional Software for Survey Data Analysis. Research Triangle Park, NC: Research Triangle Institute; 1989.

    Google Scholar 

  28. Forrest CB, Whelan EM. Primary care safety-net delivery sites in the United States: a comparison of community health centers, hospital outpatient departments, and physicians’ offices. JAMA. 2000;284:2077–83.

    Article  PubMed  CAS  Google Scholar 

  29. Hicks LS, Shaykevich S, Bates DW, Ayanian JZ. Determinants of racial/ethnic differences in blood pressure management among hypertensive patients. BMC Cardiovasc Disord. 2005;5:16.

    Article  PubMed  Google Scholar 

  30. Gerber JC, Stewart DL. Prevention and control of hypertension and diabetes in an underserved population through community outreach and disease management: a plan of action. J Assoc Acad Minor Physicians. 1998;9:48–52.

    CAS  Google Scholar 

  31. Kottke TE, Stroebel RJ, Hoffman RS. JNC 7—it’s more than high blood pressure. JAMA. 2003;289:2573–5.

    Article  PubMed  Google Scholar 

  32. Luck J, Peabody JW, Dresselhaus TR, Lee M, Glassman P. How well does chart abstraction measure quality? A prospective comparison of standardized patients with the medical record. Am J Med. 2000;108:642–9.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors would like to thank Deborah H. Williams for programming assistance. This study was supported by a grant from the Agency of Healthcare Research and Quality (#3U18 HS11046). Dr. Hicks was supported by the Robert Wood Johnson Foundation’s Harold Amos Medical Faculty Development Program.

Conflict of Interest

None disclosed.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to LeRoi S. Hicks MD, MPH.

Appendix

Appendix

Algorithm for Hypertension Reminders

Rule 1 Algorithm (CAD and HTN)

Rule 2 Algorithm (DM and HTN)

Rule 3 Algorithm (CHF and HTN)

Rule 4 Algorithm (Renal Failure/HTN)

Rule 5 (Black Race/ HTN)

Rule 6 (Elderly/ HTN)

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Hicks, L.S., Sequist, T.D., Ayanian, J.Z. et al. Impact of Computerized Decision Support on Blood Pressure Management and Control: A Randomized Controlled Trial. J GEN INTERN MED 23, 429–441 (2008). https://doi.org/10.1007/s11606-007-0403-1

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