Qi Guan1, Wayne Khuu2, Sheryl Spithoff3, Tara Kiran4, Meldon Kahan5, Mina Tadrous6, Diana Martins2, Pamela Leece7, Tara Gomes8. 1. Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St., Toronto, Ontario, M5S 3M2, Canada. 2. The Institute for Clinical Evaluative Sciences, Veterans Hill Trail, 2075 Bayview Ave., Toronto, Ontario, M4N 3M5, Canada. 3. Women's College Hospital, 76 Grenville St., Toronto, Ontario, M5S 1B2, Canada. 4. Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond St., Toronto, Ontario, M5B 1W8, Canada; The Institute for Clinical Evaluative Sciences, Veterans Hill Trail, 2075 Bayview Ave., Toronto, Ontario, M4N 3M5, Canada; Department of Family and Community Medicine, University of Toronto, 500 University Ave., Toronto, Ontario, M5G 1V7, Canada. 5. Department of Family and Community Medicine, University of Toronto, 500 University Ave., Toronto, Ontario, M5G 1V7, Canada. 6. Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond St., Toronto, Ontario, M5B 1W8, Canada; The Institute for Clinical Evaluative Sciences, Veterans Hill Trail, 2075 Bayview Ave., Toronto, Ontario, M4N 3M5, Canada; Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St., Toronto, Ontario, M5S 3M2, Canada. 7. Public Health Ontario, Suite 300, 480 University Ave., Toronto, Ontario, M5G 1V2, Canada; Women's College Hospital, 76 Grenville St., Toronto, Ontario, M5S 1B2, Canada; Department of Family and Community Medicine, University of Toronto, 500 University Ave., Toronto, Ontario, M5G 1V7, Canada. 8. Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond St., Toronto, Ontario, M5B 1W8, Canada; The Institute for Clinical Evaluative Sciences, Veterans Hill Trail, 2075 Bayview Ave., Toronto, Ontario, M4N 3M5, Canada; Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St., Toronto, Ontario, M5S 3M2, Canada; The Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College St., Toronto, Ontario, M5T 3M6, Canada. Electronic address: gomest@smh.ca.
Abstract
BACKGROUND: Despite concerns surrounding high patient volumes in methadone clinics, little is known about the practice patterns of opioid maintenance therapy (OMT) providers in Ontario. We examined the distribution of these services and how physician characteristics differ based on prescribing volume. METHODS: We conducted a cross-sectional study among prescribers of methadone or buprenorphine to Ontario public drug beneficiaries in 2014 by stratifying physicians into low- (lower 50%), moderate- (51-89%) and high-volume (top 10%) prescribers. We summarized the distribution of OMT prescription days dispensed and urine drug screens (UDS) ordered using Lorenz curves and examined physician characteristics using descriptive statistics. RESULTS: We identified 893 OMT prescribers in 2014. Physicians were mostly male (67.5%; N=603), and middle-aged (median was 50). High-volume methadone providers (N=57) prescribed approximately 56% (N=4,115,322) of the total days of methadone (Gini coefficient=0.76, 95% CI 0.74-0.79) while high-volume buprenorphine providers (N=64) prescribed 61% (N=589,463) of the total days of buprenorphine (Gini coefficient=0.78, 95% CI 0.75-0.80). On average, each high-volume methadone prescriber treated 435 OMT patients and billed 43 UDS per patient, while each high-volume buprenorphine prescriber treated 64 OMT patients and billed 22 UDS per patient. Daily OMT patient volume was on average 74 for high-volume methadone prescribers and 6 for high-volume buprenorphine prescribers. CONCLUSIONS: OMT services are highly concentrated among a small portion of OMT providers who carry high daily patient volumes. Future research should examine the quality of primary care received by their patients to better elucidate the possible consequences of this highly unequal distribution of services.
BACKGROUND: Despite concerns surrounding high patient volumes in methadone clinics, little is known about the practice patterns of opioid maintenance therapy (OMT) providers in Ontario. We examined the distribution of these services and how physician characteristics differ based on prescribing volume. METHODS: We conducted a cross-sectional study among prescribers of methadone or buprenorphine to Ontario public drug beneficiaries in 2014 by stratifying physicians into low- (lower 50%), moderate- (51-89%) and high-volume (top 10%) prescribers. We summarized the distribution of OMT prescription days dispensed and urine drug screens (UDS) ordered using Lorenz curves and examined physician characteristics using descriptive statistics. RESULTS: We identified 893 OMT prescribers in 2014. Physicians were mostly male (67.5%; N=603), and middle-aged (median was 50). High-volume methadone providers (N=57) prescribed approximately 56% (N=4,115,322) of the total days of methadone (Gini coefficient=0.76, 95% CI 0.74-0.79) while high-volume buprenorphine providers (N=64) prescribed 61% (N=589,463) of the total days of buprenorphine (Gini coefficient=0.78, 95% CI 0.75-0.80). On average, each high-volume methadone prescriber treated 435 OMTpatients and billed 43 UDS per patient, while each high-volume buprenorphine prescriber treated 64 OMTpatients and billed 22 UDS per patient. Daily OMTpatient volume was on average 74 for high-volume methadone prescribers and 6 for high-volume buprenorphine prescribers. CONCLUSIONS:OMT services are highly concentrated among a small portion of OMT providers who carry high daily patient volumes. Future research should examine the quality of primary care received by their patients to better elucidate the possible consequences of this highly unequal distribution of services.
Authors: Nicola R Jones; Suzanne Nielsen; Michael Farrell; Robert Ali; Anthony Gill; Sarah Larney; Louisa Degenhardt Journal: Drug Alcohol Depend Date: 2020-12-19 Impact factor: 4.492
Authors: Morgane Guillou-Landreat; Philippe Levassor; Marylène Guerlais; Veronique Sebille; Caroline Victorri-Vigneau Journal: Int J Environ Res Public Health Date: 2021-05-27 Impact factor: 3.390