The American Journal of Managed Care January 2006
Varying Pharmacy Benefits With Clinical Status: The Case of Cholesterol-lowering Therapy
Objective: To determine whether a pharmacy benefit that varies copayments for cholesterol-lowering (CL) therapy according to expected therapeutic benefit would improve compliance and reduce use of other services.
Methods: Using claims data from 88 health plans, we studied 62 274 patients aged 20 years and older who initiated CL therapy between 1997 and 2001. We examined the association between copayments and compliance in the year after initiation of therapy, and the association between compliance and subsequent hospital and emergency department (ED) use for up to 4 years after initiation.
Results: The fraction of fully compliant patients fell by 6 to 10 percentage points when copayments increased from $10 to $20, depending on patient risk (P < .05). Full compliance was associated with 357 fewer hospitalizations annually per 1000 high-risk patients (P < .01) and 168 fewer ED visits (P < .01) compared with patients not in full compliance. For patients at low risk, full compliance was associated with 42 fewer hospitalizations (P = .02) and 21 fewer ED visits (P = .22). Using these results, we simulated a policy that eliminated copayments for high- and medium-risk patients but raised them (from $10 to $22) for low-risk patients. Based on a national sample of 6.3 million adults on CL therapy, this policy would avert 79 837 hospitalizations and 31 411 ED admissions annually.
Conclusion: Although many obstacles exist, varying copayments for CL therapy by therapeutic need would reduce hospitalizations and ED useâ€”with total savings of more than $1 billion annually.
(Am J Manag Care. 2006;12:21-28)
Prescription drugs have been shown to be very cost-effective treatments for chronic illness; they forestall complications, reduce attendant medical utilization, and make patients more productive.1,2 But with recent increases in pharmacy spending, benefit managers have adopted policies designed to reduce use of pharmaceuticals. Usually, these policies involve increasing patient copayments for brand medications, sometime to as much as $50 for a 1-month supply. Although several studies have shown that these measures substantially reduce health plan payments and overall drug spending,3-5 they may adversely affect the health of plan enrollees.
A more promising approach links the patient copayment to therapeutic benefit. First advocated by Fendrick et al,6 such plans offer reduced copayments for patients who are most likely to benefit from a drug or class of drugs, as determined by using the best available clinical evidence. Patients for whom the therapeutic benefit is modest–or the evidence is mixed–face higher copayments. By linking copayments with individual clinical need, plans can encourage cost-effective care without unpopular utilization controls such as prior authorization.
Cholesterol-lowering (CL) drugs, the most commonly prescribed class of medications in the United States, are well suited for a benefit-based-copayment (BBC) scheme. First, patients prescribed these medications often have difficulty adhering.7-11 Second, clinical studies (the Long-Term Intervention with Pravastatin in Ischemic Disease study, the Cholesterol and Recurrent Events study, the Scandinavian Simvastatin Survival Study, the West of Scotland Coronary Prevention Study [WOSCOPS], the Air Force/Texas Coronary Atherosclerosis Prevention Study, the Heart Protection Study) have demonstrated the efficacy of CL drugs in preventing coronary heart disease (CHD). In addition, CL drugs have well-established dose-response curves such that a patient using a suboptimal dose will benefit less from therapy than a patient who fully complies. Finally, there is sufficient clinical evidence to determine the patient-specific medical benefits. Although CL drugs are beneficial for patients with average cholesterol levels, they are more effective in reducing cardiac events and mortality for those at high CHD risk.12
In this paper, we modeled a BBC for CL therapy wherein copayments are allowed to vary by clinical status. We found that eliminating copayments for patients with high CHD risk–and raising them for low-risk patients to offset the higher cost to plans–would reduce hospitalizations and emergency department (ED) visits overall among the privately insured and Medicare insured populations on CL therapy.
First, we examined the relationship between copayments and compliance. Second, we examined how compliance is associated with subsequent use of expensive services (ie, hospitalizations, EDs). The salient details are discussed below; a technical appendix providing more information is available from the authors.
We assembled a dataset of pharmacy and medical claims from 1997 to 2002 from 88 health plans and 25 employers. We restricted our attention to the 62 774 adults (age =20 years) who initiated CL therapy. Initiation of therapy was defined as the absence of any pharmacy claim in the same therapeutic class in the prior 6 months. To be eligible for our sample, a patient had to be continuously enrolled for at least 1 year before and after initiating therapy. For each prescription, we observed the fill date, type and dose of CL drug, total days supplied, patient out-of-pocket expense, and payments made by all third-party payers. We constructed the average daily price for each individual by dividing the total out-of-pocket expenses for CL agents by the total days supplied. All prices were inflated to 2004 dollars using the medical services consumer price index.
We measured compliance using the medication possession ratio (MPR). We computed the total days supplied of CL medications purchased over the subsequent 12 months (or 12 prescriptions) to compute the percentage of compliant days for each individual in the sample. Standard practice is to assign patients to compliance classes based on the MPR or proportion of days covered.7,8,10,11,13-15 Using the MPR, we classified patients into 10 categories (1 = MPR less than 10%, 2 = MPR between 10% and 19%, and so on). Days spent in the hospital were assumed to be compliant days.
Copayments and Compliance. We estimated an ordered logit model to account for our polychotomous measure of compliance (1 through 10) and its natural ordering. Explanatory variables included age, sex, marital status, median household income in the patient's zip code, number of 30-day equivalent prescriptions for non-CL therapy, health conditions, and the patient's average out-of-pocket expense (ie, copayment) for a 30-day supply of CL therapy. The model included interactions between the average copayment and risk factors for major coronary events (eg, age, sex, diabetes, heart disease). In this way, the model allowed the effects of copayments to vary with each patient's clinical status. The model also included a set of binary indicators for the health plan and year. We used the estimates from the model to predict the impact on compliance when copayments are doubled. For ease of reporting, we grouped patients into 3 compliance categories: fully compliant (MPR = 80%); partially compliant (MPR between 20% and 79%), and noncompliant (MPR < 20%).
Compliance and Service Use. We also estimated the impact of compliance in prior years on the number of hospitalizations and ED visits and the number of cardiovascular-related hospitalizations and ED admissions. WOSCOPS indicated that the greatest benefits of reduced morbidity were achieved in patients who took more than 75% of their medications.16 Wei et al also found that compliance above 80% reduced the recurrence of myocardial infarction in a 6-year follow-up study.17 Thus, we regressed annual utilization at time (t) on a binary indicator for full compliance (MPR = 80%) over the previous years (t -n), where n = 1 to 4. We used full compliance averaged over multiple years rather than just the prior year to capture the cumulative effects of compliance. Models using the previous year's full compliance yielded similar results. The model included the demographic variables and binary indicators for health plan and year as described above, as well as individual random effects to capture unobserved heterogeneity across patients.
We classified patients into 3 CHD risk groups using information available in medical claims. All patients were assigned a risk score based on age, sex, and comorbid conditions, and then were grouped by tercile into groups at high, medium, or low risk for CHD. Risk associated with age and sex was assigned based on the Framingham point system; patients with existing diabetes, myocardial infarction, ischemic heart disease, angina, atherosclerosis, or vascular disease were automatically assigned to the high-risk group. Sensitivity analysis using several other risk classification schemes–including a modified Framingham point system using smoking, blood pressure, and cholesterol levels from national data–yielded similar results.
We used estimates from both the compliance and service-use models to estimate the impact of 2 alternative BBC designs relative to a base case of a $10 copayment for all patients (the modal copayment). We derived the predictions by first estimating compliance using our copayment and compliance model, and then predicting hospitalizations and ED visits with the compliance and service-use models. The first scenario was chosen to keep total pharmacy payments unchanged. Patients at high and medium risk had no copayments while copayments for low-risk individuals were increased from $10 to $22. In the second scenario, medium-and high-risk patients received the medication for free, while low-risk patients still paid $10. The estimates were computed assuming 6.3 million privately insured or Medicare-insured adults on CL therapy in the United States, as calculated using the 1999-2000 National Health and Nutrition Examination Survey. Medicare patients were included in anticipation of the forthcoming Part D drug benefit; dual eligibles with Medicaid coverage were not included because they pay little or nothing for prescription drugs.
Table 1 shows the characteristics of the sample by CHD risk. By construction, individuals at higher CHD risk were older and sicker; those with a prior history of diabetes or heart disease automatically were assigned to the highest risk group. High-and medium-risk patients paid $9 on average for a 30-day supply of their CL medications, compared with $14 for low-risk patients. In part, this difference reflected lower prices paid by elderly beneficiaries coupled with greater use of mail-order pharmacies. High-risk patients also were the most compliant, filling prescriptions for 281 days per year (77% of total days) compared with 245 days (67%) for those at low risk of CHD. Higher risk also was associated with more hospitalizations and ED visits. In sum, higher risk patients had more comorbidity and were more compliant–perhaps due to lower copayments–but they also used more services.
Figure 1 depicts the relationship between copayments and compliance at the plan level. Each data point shows the average copayment and average compliance for a given year in plans with at least 50 beneficiaries receiving CL therapy (n = 99 plan-years). There is a large, inverse relationship between copayments and compliance. For each $10 rise in copayments, average compliance in a plan-year falls by 5 percentage points (P < .01).
Figure 2 shows the predicted effects of doubling copayments based on our ordered logit model, which adjusts the copayment response for individual characteristics. About 60% of patients at high and medium risk for CHD fully complied (MPR > 80%) with CL therapy when faced with a $10 copayment, compared with 52% of patients at low risk for CHD. Compliance fell in all risk groups when copayments doubled from $10 to $20 (P < .05 for all risk groups). After controlling for individual characteristics, there was no strong differential by risk group in the size of the response; full compliance dropped by 6 to 10 percentage points.