(148) INFLUENCE OF INDUSTRY PAYMENTS ON PRESCRIPTION BEHAVIOR PATTERN OF TESTOSTERONE MEDICATIONS AMONG PHYSICIANS IN THE UNITED STATES: NATIONAL CLAIM DATABASE ANALYSIS

Abstract Introduction Testosterone medications is commonly used to treat adult-onset hypogonadism worldwide including the United States. Physicians pattern of medication's prescription may be influenced by specific factors including pharmaceutical industry and financial relationships. Objective To determine the impact of physicians’ financial relationships with the pharmaceutical industry on prescribing marketed Testosterone medications ie, prescription behavior pattern. Methods We identified prescribers from the 2021 Medicare Part D Prescribers – by Provider and Drug dataset and the CMS General Open Payment Data Prescriber public use file. This file contains prescriber identifying information (name and practice address) and claim counts for all pharmaceuticals prescribed to beneficiaries with Medicare Part D coverage. We sorted the prescribers based on three categories, (All Providers, “Urologists”, and “Non-Urologists”). We included all prescription drugs labeled “testosterone”. We recorded the total number of prescriptions of “testosterone” drugs for each prescribing provider. We recorded the total number of financial payments each prescriber received for the generic-named “testosterone” drugs. Both the number of payments and the total value of payments were included. Results We identified 387,452 prescribers (273,978 urologists and 113,474 non-urologists) in Open Payment Data and Medicare Part D databases. Providers who received payment had a statistically significant higher number of prescriptions of testosterone medications compared to providers who did not receive a payment when prescribed testosterone medications. In 2021, the average number of prescriptions was 1.495 among all providers who received payment vs. 1.22 among all providers who did not receive payment (p < 0.001). The average number of prescriptions was 1.499 among all “urologists” who received payment vs. 1.218 among all “urologists” who did not receive payment (p < 0.001). The average number of prescriptions was 1.480 among all “non-urologists” who received payment vs. 1.226 among all “non-urologists” who did not receive payment (p < 0.001) (Table 1). Conclusions There is a consistent association between receipt of industry payment and prescribing marketed Testosterone medications particularly among urologists providers. This database analysis does indicate that prescription pattern for testosterone is primarily influenced by industry payments particularly among urologists providers. Disclosure No.