Scott G Weiner1, Christopher A Griggs2, Breanne K Langlois3, Patricia M Mitchell3, Kerrie P Nelson4, Franklin D Friedman1, James A Feldman3. 1. Department of Emergency Medicine, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts. 2. Department of Emergency Medicine, Carolinas Medical Center, Charlotte, North Carolina. 3. Department of Emergency Medicine, Boston Medical Center, Boston, Massachusetts. 4. Boston University School of Public Health, Boston, Massachusetts.
Abstract
BACKGROUND: There is a need to accurately identify patients at risk for drug abuse before giving a prescription for a scheduled medication. OBJECTIVE: Our aim was to describe a subset of emergency department (ED) patients that had eight or more schedule II-V prescriptions filled from eight or more providers in 1 year, known as "doctor-shopping" (DS) behavior, to compare demographic features of DS and non-DS patients, and to determine clinical factors associated with DS. METHODS: We conducted a prospective, observational study of emergency providers' (EPs) assessment of patients with back pain, dental pain, or headache. EPs recorded patient demographics, clinical characteristics, and numbers of schedule II-V prescriptions, subset opioid prescriptions, providers, and pharmacies utilized in a 12-month period, as reported on the state prescription drug-monitoring program. χ(2) and t-tests were used to compare DS with non-DS patients on demographics; a multivariate logistic regression was performed to determine clinical factors associated with DS. RESULTS: Five hundred and forty-four patient visits were recorded; 12.3% (n = 67) had DS behavior. DS and non-DS patients were similar in sex but differed in age, race, chief complaint, and weekday vs. weekend arrival. DS patients utilized a median of 12.0 (interquartile range [IQR] 9.0-18.0) providers compared with a median of 1.0 (IQR 0-2.0) providers in the non-DS group. Reporting allergies to non-narcotic medications (odds ratio [OR] = 3.1; 95% confidence interval [CI] 1.4-6.9; p = 0.01), requesting medications by name (OR = 2.7; 95% CI 1.5-4.9; p < 0.01), and hospital site (OR = 2.0; 95% CI 1.1-3.6; p = 0.03) were significantly associated with DS. CONCLUSIONS: There are multiple clinical characteristics associated with DS in this patient population.
BACKGROUND: There is a need to accurately identify patients at risk for drug abuse before giving a prescription for a scheduled medication. OBJECTIVE: Our aim was to describe a subset of emergency department (ED) patients that had eight or more schedule II-V prescriptions filled from eight or more providers in 1 year, known as "doctor-shopping" (DS) behavior, to compare demographic features of DS and non-DSpatients, and to determine clinical factors associated with DS. METHODS: We conducted a prospective, observational study of emergency providers' (EPs) assessment of patients with back pain, dental pain, or headache. EPs recorded patient demographics, clinical characteristics, and numbers of schedule II-V prescriptions, subset opioid prescriptions, providers, and pharmacies utilized in a 12-month period, as reported on the state prescription drug-monitoring program. χ(2) and t-tests were used to compare DS with non-DSpatients on demographics; a multivariate logistic regression was performed to determine clinical factors associated with DS. RESULTS: Five hundred and forty-four patient visits were recorded; 12.3% (n = 67) had DS behavior. DS and non-DSpatients were similar in sex but differed in age, race, chief complaint, and weekday vs. weekend arrival. DSpatients utilized a median of 12.0 (interquartile range [IQR] 9.0-18.0) providers compared with a median of 1.0 (IQR 0-2.0) providers in the non-DS group. Reporting allergies to non-narcotic medications (odds ratio [OR] = 3.1; 95% confidence interval [CI] 1.4-6.9; p = 0.01), requesting medications by name (OR = 2.7; 95% CI 1.5-4.9; p < 0.01), and hospital site (OR = 2.0; 95% CI 1.1-3.6; p = 0.03) were significantly associated with DS. CONCLUSIONS: There are multiple clinical characteristics associated with DS in this patient population.
Authors: Joseph J Palamar; Jenni A Shearston; Eric W Dawson; Pedro Mateu-Gelabert; Danielle C Ompad Journal: Drug Alcohol Depend Date: 2015-11-21 Impact factor: 4.492
Authors: Christopher Okunseri; Raymond A Dionne; Sharon M Gordon; Elaye Okunseri; Aniko Szabo Journal: Drug Alcohol Depend Date: 2015-09-28 Impact factor: 4.492
Authors: Benjamin C Sun; Nicoleta Lupulescu-Mann; Christina J Charlesworth; Hyunjee Kim; Daniel M Hartung; Richard A Deyo; K John McConnell Journal: Ann Emerg Med Date: 2017-11-24 Impact factor: 5.721
Authors: Kathryn Hawk; Gail D'Onofrio; David A Fiellin; Marek C Chawarski; Patrick G O'Connor; Patricia H Owens; Michael V Pantalon; Steven L Bernstein Journal: Acad Emerg Med Date: 2017-12-26 Impact factor: 3.451
Authors: Benjamin C Sun; Nicoleta Lupulescu-Mann; Christina J Charlesworth; Hyunjee Kim; Daniel M Hartung; Richard A Deyo; K John McConnell Journal: Acad Emerg Med Date: 2017-07-26 Impact factor: 3.451
Authors: Brian J Piper; Clare E Desrosiers; John W Lipovsky; Matthew A Rodney; Robert P Baker; Kenneth L McCall; Stephanie D Nichols; Sarah L Martin Journal: J Stud Alcohol Drugs Date: 2016-07 Impact factor: 2.582
Authors: Jacob Gorbaty; Susan M Odum; Meghan K Wally; Rachel B Seymour; Nady Hamid; Joseph R Hsu; Michael Beuhler; Michael J Bosse; Michael Gibbs; Christopher Griggs; Steven Jarrett; Daniel Leas; Tamar Roomian; Michael Runyon; Animita Saha; Bradley Watling; Stephen Wyatt; Ziqing Yu Journal: Arthrosc Sports Med Rehabil Date: 2021-02-03