Clinical Outcomes Associated With Rates of Sulfonylurea Use Among Physicians | Page 2
Published Online: July 08, 2013
Katalin Bognar, PhD; Kelly Fee Bell, PharmD, MS Phr; Darius Lakdawalla, PhD; Anshu Shrestha, PhD; Julia Thornton Snider, PhD; Nina Thomas, MPH; and Dana Goldman, PhD
For each patient cohort (incident, prevalent, second-line, or long-run), we used physician identifiers from the pharmacy claims to link physicians prescribing T2DM medicines to each patient and compile an associated cohort of physicians. Once a patient received T2DM prescriptions from a provider, the patient was considered that provider’s patient for the next 6 months. A patient receiving prescriptions from multiple providers was considered the patient of each. For each physician in each month, we calculated complication rates, average patient characteristics (age, sex, ECI), and average T2DM drug usage (fraction of patients using each class) among the physician’s T2DM patients.
After tabulating drug use and complication rates for the patient cohort, we created for each month in the study period a case-mix-adjusted measure of physician performance. Specifically, we calculated the fraction of a physician’s patients experiencing any of the study complications in a given month. We then used a linear regression model to predict the monthly rate of any T2DMrelated complication as a function of average age, gender, and ECI among patients in the practice in a given month, as well as a monthly time trend. This model provided a measure of physicians’ performance as relative success at avoiding T2DM-related complications, after adjusting for their patients’ age, sex, and comorbidities.
After deriving this measure of physician performance, we sought to determine whether it was related to T2DM prescription patterns. To do this, we compared each physician’s actual performance to the “risk-adjusted” performance predicted by patient characteristics alone (Figure 2). Those doctors with lower complication rates than predicted based on patient characteristics were considered “high performers,” whereas those with higher complication rates than predicted were considered “low performers.” We ranked physicians in each month based on their performance that month, and then sorted doctor-months into 10 ordered and equally sized groups (deciles). After establishing the 10-group ranking of physician performance, we analyzed whether the prescribing patterns in the month prior of highest performing doctors were different than those of the lowest performing doctors for each of the drug classes.
Finally, to quantify the impact of physicians’ prescribing decisions, we expanded the previous regression model of physicians’ T2DM complication rates on practice characteristics to include rates of use for each of the T2DM drug classes in the month prior. We used this model to predict the change in T2DM complications when switching from “low performer” (bottom decile) prescribing patterns to
those of “high performers” (top decile). We performed sensitivity analyses on the prevalent, second-line, and longrun samples.
We identified an incident T2DM cohort of 7905 patients. Demographic descriptions are provided in Table 1. A majority of patients were men (n = 4418; 55.90%), and the most frequent age category was 46-55 years (n = 3155, 39.91%). The average age was 50.1 years.
Rates of T2DM drug use are summarized in Table 2. The biguanide (metformin) was used during 80,244 patientmonths (37.46% of the total patientmonths). Sulfonylureas were the second most commonly used (21,429 patientmonths; 10.00%). TZDs were the thirdmost commonly used (8835; 4.12%). Every other drug class was filled less than 3% of the total patient-months. All insulin classes combined (bolus, basal,premixed) totaled 9709 patient-months(4.53%). Because metformin is widely accepted as the first-line T2DM medication,4 these data suggest that sulfonylureas are the most commonly prescribed second-line agent in this cohort.
We compared baseline ECIs among all patients newly initiating each class of diabetes medication (Table 3). Patients newly initiating the biguanide had an average ECI of 2.38 in the year prior to initiation, the lowest score of any T2DM drug class. Sulfonylureas were prescribed to patients who had the second-fewest comorbidities at initiation (average ECI: 2.75). Patients who received amylinomimetics had the most comorbidities, on average (4.00).
Rates of complications are summarized in Table 4. Cardiovascular complications were the most common, in 6378 patient-months (2.98% of the total patient-months), and neuropathy complications the least common, in 804 patient-months (0.38% of the total patientmonths). Overall, 15,492 patient-months (7.23% of the total patient-months) involved any diabetes-related complication.
Among the incident cohort, we identified10,457 distinct prescribing physicians. The average number of distinct prescribing physicians per incident T2DM patient was 1.7 (range, 1-9), whereas the average number of distinct incident T2DM patients (covered by Humana insurance) per prescribing physician was 1.3 (range, 1-18).
Figure 3 relates prescribing patterns to patient outcomes. Low-performing physicians (ie, those exhibiting higher complication rates for a given patient case-mix) were more likely than highperforming peers to prescribe metformin, sulfonylureas, and insulin. By contrast, high-performing physicians were more likely than peers to prescribe DPP-4 inhibitors, TZDs, GLP-1 agonists,or other classes of diabetes medications. The strongest correlation of drug use to performance was for DPP-4 inhibitors (R2 = 0.1662), with increasing use of this drug class positively associated with fewer T2DM complications. Sulfonylureas (R2 = 0.0857) and insulin (R2 = 0.0166) were more commonly prescribed by low performers. The insulin relationship appeared nonlinear, with high prescription rates among both high and low performers, and lower rates among average performers.
After expanding the regression model to incorporate prescriptions of T2DM drug classes, we were able to predict the number of complications that would be avoided by moving from the prescribing patterns of bottom-decile to top-decile performers. In a population of 100,000 incident T2DM patients, such a change in prescribing patterns would amount to 924 avoided complications per year (95% CI, 597-1251).
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