UNLABELLED: Opioid adverse events are widespread, and deaths have been directly attributed to opioids prescribed by medical professionals. Little information exists on the amount of opioids various medical specialties prescribe and the opioid fatality rate that would be expected if prescription opioid-related deaths were independent of medical specialty. OBJECTIVE: To compute the incidence of prescription opioid fatalities by medical specialty in Utah and to calculate the attributable risk (AR) of opioid fatality by medical specialty. DESIGN: Prevalence database study design linking the Utah Controlled Substance Database (CSD) for prescribing data with the Utah Medical Examiner data to identify prescription opioid fatalities. AR were calculated for each medical specialty and year. RESULTS: Opioid prescriptions are common with 23,302,892 recorded in the CSD for 2002-2010, 0.64% of which were associated with a fatality. We attached specialty to 90.2% of opioid prescriptions. Family medicine and internal medicine physicians wrote the largest proportion of prescriptions (24.1% and 10.8%) and were associated with the greatest number of prescription opioid fatalities. The number of active prescriptions at time of death decreased each year. The AR of fatality by provider specialty varied each year with some specialties, such as pain medicine and anesthesiology, consistently associated with more fatalities per 1,000 opioid prescriptions than internal medicine physicians the same year. CONCLUSIONS: Primary care providers were the most frequent prescribers and the most often associated with opioid fatalities and should be targeted for education about safe prescribing along with specialties that prescribe less frequently but are associated with a positive AR for opioid fatality. Wiley Periodicals, Inc.
UNLABELLED: Opioid adverse events are widespread, and deaths have been directly attributed to opioids prescribed by medical professionals. Little information exists on the amount of opioids various medical specialties prescribe and the opioid fatality rate that would be expected if prescription opioid-related deaths were independent of medical specialty. OBJECTIVE: To compute the incidence of prescription opioid fatalities by medical specialty in Utah and to calculate the attributable risk (AR) of opioid fatality by medical specialty. DESIGN: Prevalence database study design linking the Utah Controlled Substance Database (CSD) for prescribing data with the Utah Medical Examiner data to identify prescription opioid fatalities. AR were calculated for each medical specialty and year. RESULTS: Opioid prescriptions are common with 23,302,892 recorded in the CSD for 2002-2010, 0.64% of which were associated with a fatality. We attached specialty to 90.2% of opioid prescriptions. Family medicine and internal medicine physicians wrote the largest proportion of prescriptions (24.1% and 10.8%) and were associated with the greatest number of prescription opioid fatalities. The number of active prescriptions at time of death decreased each year. The AR of fatality by provider specialty varied each year with some specialties, such as pain medicine and anesthesiology, consistently associated with more fatalities per 1,000 opioid prescriptions than internal medicine physicians the same year. CONCLUSIONS: Primary care providers were the most frequent prescribers and the most often associated with opioid fatalities and should be targeted for education about safe prescribing along with specialties that prescribe less frequently but are associated with a positive AR for opioid fatality. Wiley Periodicals, Inc.
Authors: Pooja Lagisetty; Amy Bohnert; Jenna Goesling; Hsou Mei Hu; Breanna Travis; Kiran Lagisetty; Chad M Brummett; Michael J Englesbe; Jennifer Waljee Journal: Ann Surg Date: 2019-03-01 Impact factor: 12.969
Authors: Michael P Klueh; Hsou M Hu; Ryan A Howard; Joceline V Vu; Calista M Harbaugh; Pooja A Lagisetty; Chad M Brummett; Michael J Englesbe; Jennifer F Waljee; Jay S Lee Journal: J Gen Intern Med Date: 2018-06-11 Impact factor: 5.128
Authors: Christopher D Saffore; Sarette T Tilton; Stephanie Y Crawford; Michael A Fischer; Todd A Lee; A Simon Pickard; Lisa K Sharp Journal: Br J Gen Pract Date: 2020-07-30 Impact factor: 5.386
Authors: Pooja Lagisetty; Amy Bohnert; Jenna Goesling; Hsou Mei Hu; Breanna Travis; Kiran Lagisetty; Chad M Brummett; Michael J Englesbe; Jennifer Waljee Journal: Ann Surg Date: 2020-08 Impact factor: 12.969
Authors: Daniel B Larach; Jennifer F Waljee; Hsou-Mei Hu; Jay S Lee; Romesh Nalliah; Michael J Englesbe; Chad M Brummett Journal: Ann Surg Date: 2020-02 Impact factor: 13.787