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Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease

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Abstract

OBJECTIVE: Suboptimal treatment of hyperlipidemia in patients with coronary artery disease (CAD) is well documented. We report the impact of a computer-assisted physician-directed intervention to improve secondary prevention of hyperlipidemia.

DESIGN AND SETTING: Two hundred thirty-five patients under the care of 14 primary care physicians in an academically affiliated practice with an electronic health record were enrolled in this proof-of-concept physician-blinded randomized, controlled trial. Each patient with CAD or risk equivalent above National Cholesterol Education Program-recommended low-density lipoprotein (LDL) treatment goal for greater than 6 months was randomized, stratified by physician and baseline LDL. Physicians received a single e-mail per intervention patient. E-mails were visit independent, provided decision support, and facilitated “one-click” order writing.

MEASUREMENTS: The primary outcomes were changes in hyperlipidemia prescriptions, time to prescription change, and changes in LDL levels. The time spent using the system was assessed among intervention patients.

RESULTS: A greater proportion of intervention patients had prescription changes at 1 month (15.3% vs 2%, P=.001) and 1 year (24.6% vs 17.1%, P=.14). The median interval to first medication adjustment occurred earlier among intervention patients (0 vs 7.1 months, P=.005). Among patients with baseline LDLs >130 mg/dL, the first postintervention LDLs were substantially lower in the intervention group (119.0 vs 138.0 mg/dL, P=.04). Physician processing time was under 60 seconds per e-mail.

CONCLUSION: A visit-independent disease management tool resulted in significant improvement in secondary prevention of hyperlipidemia at 1-month postintervention and showed a trend toward improvement at 1 year.

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References

  1. Committee on Quality of Health Care in America, Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century Health Care Services. Washington, DC: National Academy Press; 2001.

    Google Scholar 

  2. Braunwald E. Shattuck lecture—cardiovascular medicine at the turn of the millennium: triumphs, concerns, and opportunities. N Engl J Med. 1997;337:1360–9.

    Article  PubMed  CAS  Google Scholar 

  3. McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348:2635–45.

    Article  PubMed  Google Scholar 

  4. Grant RW, Cagliero E, Murphy-Sheehy P, Singer DE, Nathan DM, Meigs JB. Comparison of hyperglycemia, hypertension, and hypercholesterolemia management in patients with type 2 diabetes. Am J Med. 2002;112:603–9.

    Article  PubMed  CAS  Google Scholar 

  5. Grant RW, Cagliero E, Dubey A, et al. Clinical inertia in the management of type 2 diabetes metabolic risk factors. Diabetic Med. 2004;21:150–5.

    Article  PubMed  CAS  Google Scholar 

  6. Kottke TE, Brekke ML, Solberg LI. Making time for preventative services. Mayo Clin Proc. 1993;68:785–91.

    PubMed  CAS  Google Scholar 

  7. Hibble A, Kanka D, Pencheon D, Pooles E. Guidelines in general practice: the new tower of Babel? BMJ. 1998;317:862–3.

    PubMed  CAS  Google Scholar 

  8. Pearson TA, McBride PE, Miller NH, Smith SC Jr. 27th Bethesda conference: matching the intensity of risk factor management with the hazard for coronary disease events. Task Force 8. Organization of preventive cardiology service. J Am Coll Cardiol. 1996;27:1039–47.

    Article  PubMed  CAS  Google Scholar 

  9. Johnston ME, Langton KB, Haynes B, Mathieu A. Effects of computer-based clinical decision support systems on clinician performance and patient outcome. Ann Intern Med. 1994;120:135–42.

    PubMed  CAS  Google Scholar 

  10. Classen D. Clinical decision support systems to improve clinical practice and quality of care. JAMA. 1998;280:1360–1.

    Article  PubMed  CAS  Google Scholar 

  11. Smith S, Murphy M, Huschka T, et al. Impact of a diabetes electronic management system on the care of patients seen in a subspecialty diabetes clinic. Diabetes Care. 1998;21:972–6.

    Article  PubMed  CAS  Google Scholar 

  12. McDonald C. Use of a computer to detect and respond to clinical events: its effect on clinician behavior. Ann Int Med. 1976;84:162–7.

    CAS  Google Scholar 

  13. McDonald CJ, Hui SL, Smith DM, et al. Reminders to physicians from an introspective computer medical record: a two-year randomized trial. Ann Intern Med. 1984;100:130–8.

    PubMed  CAS  Google Scholar 

  14. 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 

  15. Maviglia SM, Teich JM, Fiskio J, Bates DW. Using an electronic medical record to identify opportunities to improve compliance with cholesterol guidelines. J Gen Intern Med. 2001;16:531–7.

    Article  PubMed  CAS  Google Scholar 

  16. Stamos TD, Shaltoni H, Girard SA, Parrillo JE, Calvin JE. Effectiveness of chart prompts to improve physician compliance with the National Cholesterol Education Program guidelines. Am J Cardiol. 2001;88:1420–3. A8.

    Article  PubMed  CAS  Google Scholar 

  17. Murray MD, Harris LE, Overhage JM, et al. Failure of computerized treatment suggestions to improve health outcomes of outpatients with uncomplicated hypertension: results of a randomized controlled trial. Pharmacotherapy. 2004;24:324–37.

    Article  PubMed  Google Scholar 

  18. Grimshaw JM, Russell IT. Effect of clinical guidelines on medical practice: a systematic review of rigorous evaluations. Lancet. 1993;342:1317–22.

    Article  PubMed  CAS  Google Scholar 

  19. Hunt D, Haynes R, Hanna S, 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 

  20. McDonald CJ, Hui SL, Smith DM, et al. Reminders to physicians from an introspective computer medical record. A two-year randomized trial. Ann Intern Med. 1984;100:130–8.

    PubMed  CAS  Google Scholar 

  21. Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med. 2001;345:965–70.

    Article  PubMed  CAS  Google Scholar 

  22. Overhage JM, Tierney WM, Zhou XH, McDonald CJ. A randomized trial of “corollary orders” to prevent errors of omission. J Am Med Inform Assoc. 1997;4:364–75.

    PubMed  CAS  Google Scholar 

  23. McDonald C. Use of a computer to detect and respond to clinical events: its effect on clinician behavior. Ann Intern Med. 1976;84:162–7.

    CAS  Google Scholar 

  24. Litzelman DK, Dittus RS, Miller ME, Tierney WM. Requiring physicians to respond to computerized reminders improves their compliance with preventive care protocols. J Gen Intern Med. 1993;8:311–7.

    Article  PubMed  CAS  Google Scholar 

  25. Tierney WM, Hui SL, McDonald CJ. Delayed feedback of physician performance versus immediate reminders to perform preventive care. Effects on physician compliance. Med Care. 1986;24:659–66.

    Article  PubMed  CAS  Google Scholar 

  26. McDonald CJ. Computer reminders, the quality of care and the nonperfectability of man. N Engl J Med. 1976;295:1351–5.

    Article  PubMed  CAS  Google Scholar 

  27. Schellhase KG, Koepsell TD, Norris TE. Providers’ reactions to an automated health maintenance reminder system incorporated into the patient’s electronic medical record. J Am Board Fam Pract. 2003;16:312–7.

    Article  PubMed  Google Scholar 

  28. Barnett GO. The application of computer based medical record systems in ambulatory practice. N Engl J Med. 1984;310:1643–50.

    Article  PubMed  CAS  Google Scholar 

  29. Rabbani U, Morgan M, Barnett O. A COSTAR interface using WWW technology. Proc AMIA Symp. 1998;703–7.

  30. NCEP Expert Panel. Executive summary of the 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). JAMA. 2001;285:2486–97.

    Article  Google Scholar 

  31. Roper WL, Baker EL, Dyal WW, Nicola RM. Strengthening the public health system. Public Health Rep. 1992;107:609–15.

    PubMed  CAS  Google Scholar 

  32. Bakken S. An informatics infrastructure is essential for evidence-based practice. J Am Med Inform Assoc. 2001;8:199–201.

    PubMed  CAS  Google Scholar 

  33. Information for health: a strategy for building the national health information infrastructure report and recommendations. National Committee on Vital and Health Statistics. Available at aspe.hhs.gov/sp/nhii/Documents/nhiilayo.pdf. Accessed on December 20, 2004.

  34. Transforming health care: the President’s health information technology plan. Available at aspe.hhs.gov/sp/nhii/news/WhiteHouseITPlan.pdf. Accessed on December 20, 2004.

  35. Research in Action, Issue 6. Medical Informatics for Better and Safer Health Care Agency for Healthcare Research and Quality. Available at www.ahrq.gov/data/informatics/informatria.pdf. Accessed on December 20, 2004.

  36. Demakis JG, Beauchamp C, Cull WL, et al. Improving residents’ compliance with standards of ambulatory care: results from the VA cooperative study on computerized reminders. JAMA. 2000;284:1411–6.

    Article  PubMed  CAS  Google Scholar 

  37. Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG. The unreliability of individual physician “report cards” for assessing the costs and quality of care of a chronic disease. JAMA. 1999;281:2098–105.

    Article  PubMed  CAS  Google Scholar 

  38. Balas EA, Boren SA, Brown GD, Ewigman BG, Mitchell JA, Perkoff GT. Effect of physician profiling on utilization. Meta-analysis of randomized clinical trials. J Gen Intern Med. 1996;11:584–90.

    Article  PubMed  CAS  Google Scholar 

  39. Cabana MD, Rand CS, Powe NR, et al. Why don’t physicians follow clinical practice guidelines?. A framework for improvement. JAMA. 1999;282:1458–65.

    Article  PubMed  CAS  Google Scholar 

  40. Tunis SR, Hayward R, Wilson MC, et al. Internists’ attitudes about clinical practice guidelines. Ann Intern Med. 1994;120:956–63.

    PubMed  CAS  Google Scholar 

  41. Patterson ES, Nguyen AD, Halloran JP, Asch SM. Human factors barriers to the effective use of ten HIV clinical reminders. J Am Med Inform Assoc. 2004;11:50–9.

    Article  PubMed  Google Scholar 

  42. Blumenthal D, Causino N, Chang Y, et al. The duration of ambulatory visits to physicians. J Fam Pract. 1999;48:264–71.

    PubMed  CAS  Google Scholar 

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Correspondence to William T. Lester MD, MS.

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The authors were supported by a Partners IS Innovation Award.

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Lester, W.T., Grant, R.W., Barnett, G.O. et al. Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease. J GEN INTERN MED 21, 22–29 (2006). https://doi.org/10.1111/j.1525-1497.2005.00268.x

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  • DOI: https://doi.org/10.1111/j.1525-1497.2005.00268.x

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