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Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care Wesley O’Neal HIMA 5060 Fall 2012

Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

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Page 1: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Wesley O’NealHIMA 5060Fall 2012

Page 2: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Cardiovascular Disease • Cardiovascular disease (CVD) accounts for 1 in every 3 deaths

in the United States (Roger et al., 2012)• CVD is projected to increase by 10% over the next 20 years

(Heidenreich et al., 2011)• CVD accounts for 20% of healthcare dollars spent and a 3-fold

increase in these expenditures is expected (Trogdon, Finkelstein, Nwaise, Tangka, & Orenstein, 2007)

Page 3: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Clinical Decision Support Systems (CDSS)• Clinical Decision Support Systems (CDSS) are defined as clinical

consult systems that use population statistics or encode expert knowledge to assist healthcare professionals in the diagnosis and treatment of disease (Shortliffe & Cimino, 2006)

• CDSSs have been reported to improve the quality of care delivered and health outcomes (Kawamoto, Houlihan, Balas, & Lobach, 2005)

Page 4: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

CDSS and CVD• Numerous guidelines exist for the treatment of CVD • Many practitioners are not appropriately reaching quality

measures (Brady, Oliver, & Pittard, 2001)• CDSSs could possibly improve patient care and reduce the

heavy financial burden of CVD • This paper explored the data that has been reported

concerning the use of CDSSs and their impact on CVD-related care

Page 5: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Congestive Heart Failure • Mudge et al. showed that CDSSs reduced mortality in CHF

patients (Mudge et al., 2010). • Toth-Pal et al. showed that general physicians are able to

manage CHF patients with a CDSS (Toth-Pal, Wardh, Strender, & Nilsson, 2008).

• Riggio et al. found that ACEIs were more likely to be prescribed upon discharge after MI with a CDSS that was simultaneously linked with the EMR (Riggio et al., 2009).

• Eckstein et al. showed that paramedics in the field were capable of diagnosing CHF and treating it when symptoms were linked to a CDSS (Eckstein & Suyehara, 2002).

Page 6: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Hypertension• Bosworth et al. showed that physicians that used CDSSs to

treat hypertensive patients were more likely to abide by the national guidelines but not improve blood pressure numbers (Bosworth et al., 2009)

• Hicks et al. found similar results (Hicks et al., 2008)• Both of these studies show that CDSSs are not actually able to

improve the blood pressure of hypertensive patients but improve guideline adherence

Page 7: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Dyslipidemia • Gilutz et al. showed that CDSSs were able to improve the

cholesterol values of patients with known coronary artery disease (CAD)

• Increased secondary prevention and possible reduction in MI needs to be researched further

Page 8: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Myocardial Infarction• Riggio et al. found that adherence to evidence-based

guidelines was improved with increases in prescriptions for ACEIs (Riggio et al., 2009)

• These drugs have been shown to reduce mortality

Page 9: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Areas of Uncertainty • Only a few of the studies in this report were randomized

controlled trials• It does appear that CDSSs can improve the care of patients with

CVD but studies with a higher level of design will be needed • The studies discussed did not investigate the cost of

implementing CDSSs• These studies did not look at long-term outcomes • There was no uniformity in CDSSs used between studies

Page 10: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

Conclusion• CDSSs have a benefit in the management of patients with CHF

and are also able to reduce mortality in these patients• CDSSs are not able to actually improve the treatment of

hypertensive patients but may increase adherence to evidence-based guidelines

• CDSSs are able to improve the management of patients with dyslipidemia

• CDSSs improve the prescription practices of patients that are discharged from the hospital after MI

Page 11: Clinical Decision Support Systems and their Impact on Cardiovascular Disease Patient Care

References• Bosworth, H. B., Olsen, M. K., Dudley, T., Orr, M., Goldstein, M. K., Datta, S. K., . . . Oddone, E. Z. (2009). Patient education and

provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J. 157(3): 450-456.• Brady, A. J., Oliver, M. A., & Pittard, J. B. (2001). Secondary prevention in 24, 431 patients with coronary heart disease: survey in

primary care. BMJ. 322(7300): 1463.• Eckstein, M., & Suyehara, D. (2002). Ability of paramedics to treat patients with congestive heart failure via standing field

treatment protocols. Am J Emerg Med. 20(1): 23-25.• Gilutz, H., Novack, L., Shvartzman, P., Zelingher, J., Bonneh, D. Y., Henkin, Y., . . . Porath, A. (2009). Computerized community

cholesterol control (4C): meeting the challenge of secondary prevention. Isr Med Assoc J. 11(1): 23-29.• Heidenreich, P. A., Trogdon, J. G., Khavjou, O. A., Butler, J., Dracup, K., Ezekowitz, M. D., . . . Woo, Y. J. (2011). Forecasting the

future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 123(8): 933-944.

• Hicks, L. S., Sequist, T. D., Ayanian, J. Z., Shaykevich, S., Fairchild, D. G., Orav, E. J., & Bates, D. W. (2008). Impact of computerized decision support on blood pressure management and control: a randomized controlled trial. J Gen Intern Med. 23(4): 429-441.

• Kawamoto, K., Houlihan, C. A., Balas, E. A., & Lobach, D. F. (2005). Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 330(7494): 765.

• Mudge, A., Denaro, C., Scott, I., Bennett, C., Hickey, A., & Jones, M. A. (2010). The paradox of readmission: effect of a quality improvement program in hospitalized patients with heart failure. J Hosp Med. 5(3): 148-153.

• Riggio, J. M., Sorokin, R., Moxey, E. D., Mather, P., Gould, S., & Kane, G. C. (2009). Effectiveness of a clinical-decision-support system in improving compliance with cardiac-care quality measures and supporting resident training. Acad Med. 84(12): 1719-1726.

• Roger, V. L., Go, A. S., Lloyd-Jones, D. M., Benjamin, E. J., Berry, J. D., Borden, W. B., . . . Turner, M. B. (2012). Heart disease and stroke statistics--2012 update: a report from the American Heart Association. Circulation. 125(1): e2-e220.

• Shortliffe, E. H., & Cimino, J. J. (2006). Biomedical informatics : computer applications in health care and biomedicine (3rd ed.). New York, NY: Springer.

• Toth-Pal, E., Wardh, I., Strender, L. E., & Nilsson, G. (2008). A guideline-based computerised decision support system (CDSS) to influence general practitioners management of chronic heart failure. Inform Prim Care. 16(1): 29-39.

• Trogdon, J. G., Finkelstein, E. A., Nwaise, I. A., Tangka, F. K., & Orenstein, D. (2007). The economic burden of chronic cardiovascular disease for major insurers. Health Promot Pract. 8(3): 234-242.