By Leo Beletsky and Andrea Sorensen
Much attention has been devoted in recent years to the alarming increase in morbidity and mortality related to opioid overdose. Between 2004 and 2007 there was a nearly fourfold increase in the use of prescription opioids in the US, and in at least five states this is now the leading cause of unintentional injury death. Data such as the number of emergency room visits and deaths attributable to opioid overdose have raised awareness among states and the federal government that there is much work needed in preventing and addressing this epidemic.
A growing body of research and reports addressing this issue have focused on, for example, the severity of this problem in particular states, the trends of a particular opiate such as methadone, or the societal cost of drug addiction more broadly. Lacking from this literature is an assessment of the overall costs that result from the increased overdose morbidity and mortality. Thus, we intend to perform a cost-of-illness analysis by assessing the costs associated with emergency room visits, lost productivity due to hospitalization, and costs to society resulting from premature deaths. Data permitting, we will focus on the annual cost in 2008—the most recent year for which healthcare cost data are available.
We are currently working to collect data and information from a wide variety of sources in order to provide a national cost estimate and range. Our costs will include healthcare costs/medical expenses; the economic impact from days of work lost due to hospitalization; and the costs associated with lives lost and premature death. Thus, we will take into account both direct (medical) and indirect (lost productivity and lost lives) to estimate this annual cost burden.
We are relying on DAWN statistics for Emergency room visit data, which provides a breakdown of the annual number of ER visits attributable to opioid/opiate abuse. DAWN also provides data for the cost of an average hospital stay for accidental poisoning and substance abuse stays, as well as the average length of stay by condition. This will allow us to calculate the cost per episode that we can use to determine the entire direct health care cost component. The average length of hospital stay data will also be used to determine lost productivity due to hospitalization.
Prevalence of premature death will be determined using the National Vital Statistics System data. We will calculate the premature death costs based on previously established methods used in similar cost analysis research: we will rely on the value of statistical life (VSL) determined by Aldy and Viscusi (2003)—a value that has been used widely in other similar cost studies. In addition, we will calculate projected lost earnings based on the number of deaths attributable to opioid overdose in each age group, using life expectancy data and estimated earnings data (for each age group). International Classification of Diseases (ICD) 10th Revision, T-40.0—T40.6 are of interest for this analysis. The overall category ICD -10 T40 includes Poisoning by narcotics and psychodysleptics (hallucinogens). We have yet to locate this mortality data. While there are many summary reports published by the CDC, finding specific breakdowns of mortality causes has proven challenging to pinpoint. It looks as though the Healthcare Cost and Utilization Project (HCUP) offers databases available for purchase that might contain this information (http://www.hcup-us.ahrq.gov/tech_assist/centdist.jsp).
Questions that have emerged during our initial stage of gathering data and defining costs include selecting proper ICD categories and determining the accuracy of deaths attributable to prescription opioid overdose, as earlier research has found that death certificates might fail to specify this as the reason of death, thus underestimating the actual number.
Our goal is for this cost analysis to inform policymaking and funding decisions. Our findings can help state and Federal government agencies and other funders quantify the costs of opioid overdose morbidity and loss of life. Cost estimation is important for setting priorities in prevention programming, surveillance, and research particularly at a time of particularly scarce public health resources. Quantifying this piece can also provide an important component in future benefit-cost preventative treatment studies.