Estimates of geographic variation among states and counties in the prevalence of opioid prescribing are developed using data from a large (135M) representative national sample of opioid prescriptions dispensed during 2008 by 37,000 retail pharmacies. Statistical analyses are used to estimate the extent to which county variation is explained by characteristics of resident populations, their healthcare utilization, proxy measures of morbidity, availability of healthcare resources, and prescription monitoring laws. Geographic variation in prevalence of prescribed opioids is large, greater than variation observed for other healthcare services. Counties having the highest prescribing rates for opioids were disproportionately located in Appalachia and in Southern and Western states. The number of available physicians was by far the strongest predictor of amounts prescribed, but only one-third of county variation is explained by the combination of all measured factors. Wide variation in prescribing opioids reflects weak consensus regarding the appropriate use of opioids for treating pain, especially chronic non-cancer pain. Patients’ demands for treatment have increased, more potent opioids have become available, an epidemic of abuse has emerged, and calls for increased government regulation are growing. Greater guidance, education and training in opioid prescribing are needed for clinicians to support appropriate prescribing practices. Perspective Wide geographic variation that does not reflect differences in the prevalence of injuries, surgeries, or conditions requiring analgesics raises questions about opioid prescribing practices. Low prescription rates may indicate under-treatment, while high rates may indicate overprescribing and insufficient attention to risks of misuse.

BackgroundAbuse of prescription opioid analgesics is a serious threat to public health, resulting in rising numbers of overdose deaths and admissions to emergency departments and treatment facilities. Absent adequate patient information systems, “doctor shopping” patients can obtain multiple opioid prescriptions for nonmedical use from different unknowing physicians. Our study estimates the prevalence of doctor shopping in the US and the amounts and types of opioids involved.Methods and FindingsThe sample included records for 146.1 million opioid prescriptions dispensed during 2008 by 76% of US retail pharmacies. Prescriptions were linked to unique patients and weighted to estimate all prescriptions and patients in the nation. Finite mixture models were used to estimate different latent patient populations having different patterns of using prescribers. On average, patients in the extreme outlying population (0.7% of purchasers), presumed to be doctor shoppers, obtained 32 opioid prescriptions from 10 different prescribers. They bought 1.9% of all opioid prescriptions, constituting 4% of weighed amounts dispensed.ConclusionsOur data did not provide information to make a clinical diagnosis of individuals. Very few of these patients can be classified with certainty as diverting drugs for nonmedical purposes. However, even patients with legitimate medical need for opioids who use large numbers of prescribers may signal dangerously uncoordinated care. To close the information gap that makes doctor shopping and uncoordinated care possible, states have created prescription drug monitoring programs to collect records of scheduled drugs dispensed, but the majority of physicians do not access this information. To facilitate use by busy practitioners, most monitoring programs should improve access and response time, scan prescription data to flag suspicious purchasing patterns and alert physicians and pharmacists. Physicians could also prevent doctor shopping by adopting procedures to screen new patients for their risk of abuse and to monitor patients' adherence to prescribed treatments.

Objective This study estimated the prevalence of stimulant treatment among both adults and children at national, state, and county levels during 2008 and explored explanations for wide variations in treatment prevalence. Methods Records of 24.1 million stimulant prescriptions dispensed to insured and uninsured patients were obtained from approximately 76% of U.S. retail pharmacies. Data were weighted to estimate treatment prevalence on March 15, 2008, for all U.S. states and counties. Regression models were used to estimate the associations among the counties’ treatment rates and the characteristics of the counties and their resident populations. Results An estimated 2.5% of children ≤17 years of age (3.5% of males and 1.5% of females) and .6% of persons >17 years of age were being treated with stimulants in March 2008. Treatment prevalence among states varied widely, and variation among counties was even wider. Two-thirds of the variation among counties in treatment prevalence was associated with supply of physicians, socioeconomic composition of the population, and, among children, funding for special education. Rates of children and adults in treatment were highly correlated. Conclusions Wide variations in treatment prevalence signal disparities between established clinical practice guidelines and actual practice, especially for primary care, where most patients prescribed stimulants are managed. Better education and training for physicians may improve identification and treatment, thereby reducing disparities in care for attention-deficit hyperactivity disorder and other disabling conditions.

Purpose This study estimates the prevalence in US counties of opioid patients who use large numbers of prescribers, the amounts of opioids they obtain, and the extent to which their prevalence is predicted by ecological attributes of counties, including general medical exposure to opioids. Methods Finite mixture models were used to estimate the size of an outlier subpopulation of patients with suspiciously large numbers of prescribers (probable doctor shoppers), using a sample of 146 million opioid prescriptions dispensed during 2008. Ordinary least squares regression models of county-level shopper rates included independent variables measuring ecological attributes of counties, including rates of patients prescribed opioids, socioeconomic characteristics of the resident population, supply of physicians, and measures of healthcare service utilization. Results The prevalence of shoppers varied widely by county, with rates ranging between 0.6 and 2.5 per 1000 residents. Shopper prevalence was strongly correlated with opioid prescribing for the general population, accounting for 30% of observed county variation in shopper prevalence, after adjusting for physician supply, emergency department visits, in-patient hospital days, poverty rates, percent of county residents living in urban areas, and racial/ethnic composition of resident populations. Approximately 30% of shoppers obtained prescriptions in multiple states. Conclusions The correlation between prevalence of doctor shoppers and opioid patients in a county could indicate either that easy access to legitimate medical treatment raises the risk of abuse or that drug abusers take advantage of greater opportunities in places where access is easy. Approaches to preventing excessive use of different prescribers are discussed.

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