Opioid. Economic and Social Cost of the Opioid Crisis

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Opioid
Abstract
Opioids consist of drugs used to relieve pain. Some of these drugs include hydrocodone, codeine, and morphine, among others. During the manufacturing of the drugs, pharmacists and physicists use heroin in minimal doses to enhance the productivity of the entire prescription. Opioids play a vital role in the health sector since surgeons recommend their use during surgeries. Although opioids have an essential role in enhancing healthcare practices, studies suggest that they are widely misused since they contain heroin. The objective of this paper is to outline the economic crisis and social cost of opioids in the United States. Studies illustrate that increased misuse of opioids contributes to death and sabotages the economic and social lives of the victims’ families. Therefore, testing the rate and impact of opioid overdose in society will help prevent the continued misuse of the drugs, thus preventing further loses and deaths.
Keywords: Opioids, drugs, misuse, crisis, overdose, and death.
Economic and Social Cost of the Opioid Crisis
Opioid crises and misuse have posed significant threats to the healthcare costs of the United States. Current trends reveal that people die of overdoses each year, the majority of which involve opioid drugs. Although all individuals are vulnerable to the effects of the opioid epidemic, the vulnerable populations, such as those from economically deprived backgrounds, can suffer far-reaching consequences. Medical practitioners prescribe drugs daily to patients in different parts of the world as one of the ways of enhancing the overall health levels of the entire population. The ongoing opioid epidemic has been spurring for several decades resulting from the misuse of prescribed and illegal drugs. Codeine, morphine, oxycodone, and fentanyl are the various forms of opioids, which have far-reaching consequences across the United States.
The United States reached the peak of the opioid crisis in 2015 after drug overdose became one of the leading causes of death in the country. Statistics indicate that the country recorded a total of thirty-three deaths as a result of opioids. For that reason, President Donald Trump pronounced the crisis as a national health emergency. According to Brill and Ganz, the opioid epidemic has been one of the major concerns based on increased awareness among the members of the public (23). According to research findings, every stakeholder ought to find effective strategies for addressing the pandemic. Notably, the top government officials have to formulate an effective plan of addressing the issues of misuse of opioids to decrease the number of drug-related deaths.
The prescription of drugs is one of the leading factors in the opioid crisis. However, economic and social upheaval are equally relevant factors, which have fueled the crises. According to Dasgupta et al., the use of heroin, fentanyl analogs, and opioid analgesics has influenced the trajectory of the crises (182). The authors postulate that the roots of the opioid crisis are deeper more than the existing popular narratives. The revelations of undertreated chronic pain and normative practice influenced a change in the United States medicine (Parramore 2). Besides, pharmaceutical innovations have propagated oral dissolving strips, transdermal patches, and nasal sprays. Research findings indicate that heightened opioid prescription for chronic pain has been a vector of the crises in the United States.
The opioid crisis has caused high economic costs across the United States. The devastating consequences of the predicament have influenced public health and social and economic welfare. Over the years, local and state governments have shouldered the burden of the opioid epidemic and other related costs to families and individuals. According to Florence et al., the United States government is at ground zero, especially if people suffering from opioid epidemic incur high costs on treatment (12). The high prevalence of opioid crisis cases has influenced high burdens on children’s welfare systems, the criminal justice system, and special education. Research findings add to the body of literature on the opioid epidemic. Arguably, misuse of opioids minimized overall tax revenue by about $11 billion and almost $ 2 billion in sales tax revenue (Scavette 1). Furthermore, total Medicaid costs associated with the use of opioids have tripled from 1999 to 2019, reaching $3 billion.
LOG Model
A simple analysis was conducted to investigate the trend in the twelve states with manufacturing and tmanufacturing jobs concentration in other states. The model run was;
Log (overdoses) = beta0 + beta1*t + beta2*t*manufacturing
Log (overdoses) = 5.463148 – 1.143877t + 0.1118731t*manufacturing
Coefficients of t and tmanufacturing were negative and positive, respectively. The factors were also significant in predicting the trend as they had p-values of 0.0001<0.05 level of significance. The fitted model had an R-Squared value of 0.0555. Therefore, the coefficients explained 5.55% of the variation in the model. Overall, the model was significantly fit with ANOVA results showing a p-value of 0.0001 less than 0.05.
OLS Model
Subsequently, an OLS model of opioid deaths was constructed with multiple factors and year dummies to estimate and analyze the effect of those factors on opioid deaths in the “manufacturing” states post-recession (on or after 2008). The model constructed was as follows.
OLS (opioid deaths) = 9.725692 + 0.362886recession + 0.4631478recmanu + 0.0000379mdhhincomreal + 1.5e-06stategdpmlreal – 0.0081938pctinsured + 0.0146824pcthsg + 0.0557396unemploymentrate – 0.1241221lfpr + … –0.1261302d17
Variables listed in the model’s output table had negative and positive coefficients with some insignificant. Those with negative coefficients were pctinsured, lfpr, d8, d9, d10, d11, d12, d13, d14, d15, d16 and d17. D18 was omitted due to singularities. Conversely, those with positive coefficients were recession, recmanu, mdhhincomereal, stategdpmlreal, pcthsg, unemploymentrate, d1, d2, d3, d4, d5, d6, and d7. Variables with negative coefficients meant that a single unit increase in them would have resulted in a decrease in opioid deaths. Contrary, those with positive coefficient values would have increased opioid deaths if a unit were added to them. The significant predictors of opioid deaths were recmanu, mdhhincomereal, stategdpmlreal, lfpr, d6, d9, d10, d11, d12, d13, and d14.
The above model showed that opioid deaths had a sharp rise post-recession in non-manufacturing states (36% rise on average). However, for manufacturing nations, the growth was more significant (36% + 46.6% larger). Also shown wa...