Influence of peer networks on physician adoption of new drugs

• Published in: PloS one Vol. 13; no. 10; p. e0204826
• Main Authors: Donohue, Julie M., Guclu, Hasan, Gellad, Walid F., Chang, Chung-Chou H., Huskamp, Haiden A., Choudhry, Niteesh K., Zhang, Ruoxin, Lo-Ciganic, Wei-Hsuan, Junker, Stefanie P., Anderson, Timothy, Richards-Shubik, Seth
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.10.2018; Public Library of Science (PLoS)
• Subjects: Amides - therapeutic use; Analysis; Anticoagulants; Antidiabetics; Antihypertensives; Computer and Information Sciences; Dabigatran - therapeutic use; Diabetes mellitus; Drug Prescriptions - statistics & numerical data; Drug Utilization - trends; Drugs; Female; Fumarates - therapeutic use; Government programs; Health care; Health care policy; Humans; Male; Medicaid; Medical personnel; Medical technology; Medicare; Medicine and Health Sciences; Networks; Patients; Peer Group; Peer pressure; Pennsylvania; People and Places; Physical Sciences; Physicians; Practice; Practice Patterns, Physicians; Prescription drugs; Prescriptions (Drugs); Research and Analysis Methods; Sitagliptin Phosphate - therapeutic use; Social network analysis; Social networks; Social Sciences; Training; United States; United States; Pennsylvania; Istanbul Turkey; San Francisco California; Turkey; United States > US; Massachusetts; Pittsburgh Pennsylvania; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0204826

Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians' own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications. We constructed 4 types of peer networks based on shared Medicare and Medicaid patients, medical group affiliation, hospital affiliation, and medical school/residency training. Instrumental variables analysis was used to estimate the causal effect of peer adoption (fraction of peers in each network adopting the new drug) on physician adoption (prescribing at least the median number prescriptions within 15 months of the new drug's introduction). We illustrate how physician network position can inform targeting of interventions to physicians by computing a social multiplier. Dabigatran was adopted by 25.2%, sitagliptin by 24.5% and aliskiren by 8.3% of physicians. A 10-percentage point increase in peer adoption in the patient-sharing network led to a 5.90% (SE = 1.50%, p<0.001) increase in physician adoption of dabigatran, 8.32% (SE = 1.51%, p<0.001) increase in sitagliptin, and 7.84% increase in aliskiren adoption (SE = 2.93%, p<0.001). Peer effects through shared hospital affiliation were positive but not significant, and medical group and training network effects were not reliably estimated. Physicians in the top decile of patient-sharing network peers were estimated to have nearly 2-fold stronger influence on their peers' adoption compared to physicians in the top decile of prescribing volume. Limitations include lack of detailed clinical information and pharmaceutical promotion, variables which may influence physician adoption but which are unlikely to bias our peer effect estimates. Peer adoption, especially by those with whom physicians share patients, strongly influenced physician adoption of new drugs. Our study shows the potential for using information on physician peer networks to improve technology diffusion.