ABSTRACT
BACKGROUND
Many individuals at higher risk for cardiovascular disease (CVD) do not receive recommended treatments. Prior interventions using personalized risk information to promote prevention did not test clinic-wide effectiveness.
OBJECTIVE AND DESIGN
To perform a 9-month cluster-randomized trial, comparing a strategy of electronic health record-based identification of patients with increased CVD risk and individualized mailed outreach to usual care.
PARTICIPANTS
Patients of participating physicians with a Framingham Risk Score of at least 5 %, low-density lipoprotein (LDL)-cholesterol level above guideline threshold for drug treatment, and not prescribed a lipid-lowering medication were included in the intention-to-treat analysis.
INTERVENTION
Patients of physicians randomized to the intervention group were mailed individualized CVD risk messages that described benefits of using a statin (and controlling hypertension or quitting smoking when relevant).
MAIN MEASURES
The primary outcome was occurrence of a LDL-cholesterol level, repeated in routine practice, that was at least 30 mg/dl lower than prior. A secondary outcome was lipid-lowering drug prescribing. Clinicaltrials.gov identifier: NCT01286311.
KEY RESULTS
Fourteen physicians with 218 patients were randomized to intervention, and 15 physicians with 217 patients to control. The mean patient age was 60.7 years and 77% were male. There was no difference in the primary outcome (11.0 % vs. 11.1 %, OR 0.99, 95 % CI 0.56–1.74, P = 0.96), but intervention group patients were twice as likely to receive a prescription for lipid-lowering medication (11.9 %, vs. 6.0 %, OR 2.13, 95 % CI 1.05–4.32, p = 0.038). In post hoc analysis with extended follow-up to 18 months, the primary outcome occurred more often in the intervention group (22.5 % vs. 16.1 %, OR 1.59, 95 % CI 1.05–2.41, P = 0.029).
CONCLUSIONS
In this effectiveness trial, individualized mailed CVD risk messages increased the frequency of new lipid-lowering drug prescriptions, but we observed no difference in proportions lowering LDL-cholesterol after 9 months. With longer follow-up, the intervention’s effect on LDL-cholesterol levels was apparent.
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References
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;285:2486–2497.
Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation. 2004;110:227–239.
Mosca L, Benjamin EJ, Berra K, et al. Effectiveness-based guidelines for the prevention of cardiovascular disease in women–2011 update: a guideline from the American Heart Association. Circulation. 2011;123:1243–1262.
Redberg RF, Benjamin EJ, Bittner V, et al. AHA/ACCF [corrected] 2009 performance measures for primary prevention of cardiovascular disease in adults: a report of the American College of Cardiology Foundation/American Heart Association task force on performance measures (writing committee to develop performance measures for primary prevention of cardiovascular disease): developed in collaboration with the American Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; and Preventive Cardiovascular Nurses Association: endorsed by the American College of Preventive Medicine, American College of Sports Medicine, and Society for Women’s Health Research. Circulation. 2009;120:1296–1336.
Persell SD, Zei C, Cameron KA, Zielinski M, Lloyd-Jones DM. Potential use of 10-year and lifetime coronary risk information for preventive cardiology prescribing decisions: a primary care physician survey. Arch Intern Med. 2010;170:470–477.
Mosca L, Linfante AH, Benjamin EJ, et al. National study of physician awareness and adherence to cardiovascular disease prevention guidelines. Circulation. 2005;111:499–510.
Sheridan SL, Crespo E. Does the routine use of global coronary heart disease risk scores translate into clinical benefits or harms? A systematic review of the literature. BMC Health Serv Res. 2008;8:60.
Sheridan SL, Viera AJ, Krantz MJ, et al. The effect of giving global coronary risk information to adults: a systematic review. Arch Intern Med. 2010;170:230–239.
Hall LM, Jung RT, Leese GP. Controlled trial of effect of documented cardiovascular risk scores on prescribing. BMJ. 2003;326:251–252.
Grover SA, Lowensteyn I, Joseph L, et al. Patient knowledge of coronary risk profile improves the effectiveness of dyslipidemia therapy: the CHECK-UP study: a randomized controlled trial. Arch Intern Med. 2007;167:2296–2303.
Edelman D, Oddone EZ, Liebowitz RS, et al. A multidimensional integrative medicine intervention to improve cardiovascular risk. J Gen Intern Med. 2006;21:728–734.
Sheridan SL, Shadle J, Simpson RJ Jr, Pignone MP. The impact of a decision aid about heart disease prevention on patients’ discussions with their doctor and their plans for prevention: a pilot randomized trial. BMC Health Serv Res. 2006;6:121.
Sheridan SL, Draeger LB, Pignone MP, et al. A randomized trial of an intervention to improve use and adherence to effective coronary heart disease prevention strategies. BMC Health Serv Res. 2011;11:331.
van Wyk JT, van Wijk MA. Assessment of the possibility to classify patients according to cholesterol guideline screening criteria using routinely recorded electronic patient record data. Stud Health Technol Inform. 2002;93:39–46.
Persell SD, Dunne AP, Lloyd-Jones DM, Baker DW. Electronic health record-based cardiac risk assessment and identification of unmet preventive needs. Med Care. 2009;47:418–424.
Roland M, Torgerson DJ. What are pragmatic trials? BMJ. 1998;316:285.
National Cholesterol Education Program. Risk assessment tool for estimating 10-year risk of developing hard CHD (myocardial infarction and coronary death). Available at http://hin.nhlbi.nih.gov/atpiii/calculator.asp?usertype=prof. Accessed October 18, 2012.
Persell SD, Kaiser D, Dolan NC, et al. Changes in performance after implementation of a multifaceted electronic-health-record-based quality improvement system. Med Care. 2011;49:117–125.
Montaño D, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. San Francisco: Wiley; 2008:67–96.
D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham heart study. Circulation. 2008;117:743–753.
Wood DA, Kotseva K, Connolly S, et al. Nurse-coordinated multidisciplinary, family-based cardiovascular disease prevention programme (EUROACTION) for patients with coronary heart disease and asymptomatic individuals at high risk of cardiovascular disease: a paired, cluster-randomised controlled trial. Lancet. 2008;371:1999–2012.
Wister A, Loewen N, Kennedy-Symonds H, McGowan B, McCoy B, Singer J. One-year follow-up of a therapeutic lifestyle intervention targeting cardiovascular disease risk. CMAJ. 2007;177:859–865.
Randomised controlled trial evaluating cardiovascular screening and intervention in general practice: principal results of British family heart study. Family Heart Study Group. BMJ. 1994;308:313–320.
Benner JS, Erhardt L, Flammer M, et al. A novel programme to evaluate and communicate 10-year risk of CHD reduces predicted risk and improves patients’ modifiable risk factor profile. Int J Clin Pract. 2008;62:1484–1498.
Mann DM, Ponieman D, Montori VM, Arciniega J, McGinn T. The Statin choice decision aid in primary care: a randomized trial. Patient Educ Couns. 2010;80:138–140.
van Wyk JT, van Wijk MA, Sturkenboom MC, Mosseveld M, Moorman PW, van der Lei J. Electronic alerts versus on-demand decision support to improve dyslipidemia treatment: a cluster randomized controlled trial. Circulation. 2008;117:371–378.
Acknowledgements
Author contribution: Dr. Persell had full access to the study data and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Persell, Lloyd-Jones, Baker
Acquisition of data: Persell, Cooper, Friesema
Analysis and interpretation of data: Persell, Cooper
Drafting of the manuscript: Persell
Critical revision of the manuscript for important intellectual content: Lloyd-Jones, Friesema, Cooper, Baker
Statistical analysis: Persell
Obtained funding: Persell
Study supervision: Persell, Baker
Funding/Support: K08 HS015647, Agency for Healthcare Research and Quality.
Role of the funder: the funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
This work was presented at the Society of General Internal Medicine Annual Meeting in Orlando Florida, May 9, 2012.
Conflict of Interest
The authors declare that they do not have a conflict of interest.
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Grant support: K08 HS015647, Agency for Healthcare Research and Quality Trial registration: Clinicaltrials.gov identifier: NCT01286311.
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Persell, S.D., Lloyd-Jones, D.M., Friesema, E.M. et al. Electronic Health Record-Based Patient Identification and Individualized Mailed Outreach for Primary Cardiovascular Disease Prevention: A Cluster Randomized Trial. J GEN INTERN MED 28, 554–560 (2013). https://doi.org/10.1007/s11606-012-2268-1
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DOI: https://doi.org/10.1007/s11606-012-2268-1