Wesley O'Neal

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

2. 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)

3. 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)

4. 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

5. 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).

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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.