Early Detection of Prescription Drug Abuse Using Doctor Shopping Monitoring From Claims Databases: Illustration From the Experience of the French Addictovigilance Network - Soeiro, Thomas; Lacroix, Clémence; Pradel, Vincent; Lapeyre-Mestre, Maryse; Micallef, Joëlle (Frontiers in Psychiatry, 2021)
Opioid analgesics and maintenance treatments, benzodiazepines and z-drugs, and other sedatives and stimulants are increasingly being abused to induce psychoactive effects or alter the effects of other drugs, eventually leading to dependence. Awareness of prescription drug abuse has been increasing in the last two decades, and organizations such as the International Narcotics Control Board has predicted that worldwide prescription drug abuse may exceed the use of illicit drugs. Assessment of prescription drug abuse tackles an issue by nature hidden, which therefore requires a specific monitoring. The current best practice is to use multiple detection systems to assess prescription drug abuse by various populations in a timely, sensitive, and specific manner. In the early 2000s, we designed a method to detect and quantify doctor shopping for prescription drugs from the French National Health Data System, which is one of the world’s largest claims database, and a first-class data source for pharmacoepidemiological studies. Doctor shopping is a well-known behavior that involves overlapping prescriptions from multiple prescribers for the same drug, to obtain higher doses than those prescribed by each prescriber on an individual basis. In addition, doctor shopping may play an important role to supply the black market. The paper aims to review how doctor shopping monitoring can improve the early detection of prescription drug abuse within a multidimensional monitoring. The paper provides an in-depth overview of two decades of development and validation, for several pharmacological classes (e.g. opioids, benzodiazepines, antidepressants, and methylphenidate). The process accounted for relevant determinants of prescription drug abuse, such as pharmacological data (e.g. formulations and doses), chronological and geographical data (e.g. impact of measures and comparison between regions), and epidemiological and outcome data (e.g. profiles of patients and trajectories of care).