IMPLICATIONS OF TRUE AND PERCEIVED TREATMENT BURDEN ON CARDIOVASCULAR MEDICATION USE

Purpose: To examine how much variations in patient treatment burden would influence optimal use of antihypertensive medications and how much over- and under-treatment can result from clinicians misunderstanding their patients' treatment burden.

Method: We developed a Markov Decision Process (MDP) model to estimate the difference in expected QALYs (over a 10-year planning horizon) if clinicians used the true patient burden to guide blood pressure treatment, compared to the expected QALYs if the clinician's perceived patient burden diverged from the true patient burden. The MDP model makes decisions that maximize expected QALYs for each patient using the clinician's perceived treatment burden, thus estimating the best care that the clinician could provide if the only limitation is their uncertainty about patient (true) treatment burden. The models were calibrated using CVD risk factors derived from NHANES as well as other published data. Untreated event rates were estimated using the Framingham score. Sensitivity analyses was performed to examine: (1) the definition of mistreatment, (2) the discount factor used, (3) the mortality scaling factor, (4) variability around the perceived and true burden, and (5) patient adherence.

Result: Fairly small differences in true patient burden from blood pressure treatment alter the number of blood pressure medications that should be recommended and alters treatment's potential benefit dramatically. We also found that a clinician misunderstanding the patient's burden could lead to almost 30% of patients being treated inappropriately. Most dramatically, if a clinician's underestimation of the patient's true burden makes that patient less likely to take a medication, this would amount to losses of up to 85.3 QALYs per 1000 people.

Conclusion: Treatment burden varies between patients based on side effects, costs, and patient opinion. Current clinical practice fails to gather information that explicitly understands this variation, and clinical practice guidelines fail to account for it. We found that clinical decisions that fail to account for patient treatment burden can mistreat a very large proportion of the public. Successful treatment selection is closely dependent on a clinicians' ability to accurately gauge a patient's treatment burden.