Non-medical use of prescription opioid medications is a serious and rapidly growing addiction problem in the US. Maine witnessed a 22% increase in opioid prescriptions written from 2005-2010, and the Maine Medical Examiner reported an exponential increase in drug overdose deaths (from 34 in 1998 to 179 in 2010), most from prescription drug misuse. Therefore it is critical to identify target areas where rapid implementation of strategies for prescription misuse prevention and addiction treatment should be focused, given limited resources in a rural state during this economically challenging time. Our objective is to describe the geographic distribution of prescription opioid medications to visualize the diffusion of these prescriptions into Maine communities, utilizing geographic information systems (GIS) to assess spatial features powerfully and precisely and to find 'hot spots'of overall availability of prescription opioid medications.
Aim 1 : Create a deidentified database from Maine Office of Substance Abuse (OSA) Prescription Monitoring Program (PMP) 2005-2010 data to describe the volume and distribution of opioid prescriptions, linking continuous prescriptions to an individual over time and identifying locations of new and concurrent prescriptions.
Aim 2 : Describe demographic and geographic characteristics of opioid prescription recipients and of opioid prescribers, including zip code, details of each opioid prescription (formulation, dosage, duration), age and simultaneous prescriptions of other controlled substances.
Aim 3 : Assess spatial and temporal associations between opiates, the recipients (in aggregate) and the underlying population socio-demographic characteristics. Using GIS for spatial analysis, we will identify clustering, directional trends and dispersion of effect in geographic space. Our retrospective analysis will analyze de-identified data consisting of more than 12 million prescriptions for controlled substances dispensed in Maine from 2005 - 2010, with demographic and geographic information on prescriber, pharmacy and recipient for each prescription. This data from the Maine PMP is provided by pharmacies. Our measures will include descriptive analysis of demographic and geographic factors associated with receipt of prescriptions for opioid medications, generated at the patient level and for prescribers of these medications. Rates and associations of location by zip code, patient age, specifics of each opioid prescription and of other controlled substances, rates of new prescriptions to patients, and new prescriber behavior will be analyzed using univariate and bivariate analysis. Using US Census data and robust methods now available with GIS mapping and analysis software, spatial trends in the data will be mapped to identify locations with high levels of receipt of narcotic prescriptions and concomittant high risk socio-demographic factors for prescription drug abuse. Geographic analysis of the prescription drug supply is a novel approach to allow visualization of this data, providing accurate summary information about the availability of prescription opioid medications fueling the prescription drug abuse epidemic, and allowing focus on high risk areas for treatment interventions.
Prescription drug abuse is increasing exponentially in many rural areas, including all of Maine, and is known to be more likely in areas with high poverty, low educational attainment rates, and high rates of prescription drug supply. Our objective is to describe the demographic and geographic factors associated with receipt of prescriptions for opioid medications, and to map the distribution of these prescriptions and their providers over time, using Maine Prescription Monitoring data from 2005 - 2010. Geographic analysis of the prescription drug supply is a novel approach to allow visualization of this trend, providing accurate data about the overall availability of the prescription opioid medications fueling the prescription drug abuse epidemic, and can identify high risk areas for concentrated treatment intervention.