Modeling the evolution of the US opioid crisis for national policy development.

The opioid crisis is a major public health challenge in the United States, killing about 70,000 people in 2020 alone. Long delays and feedbacks between policy actions and their effects on drug-use behavior create dynamic complexity, complicating policy decision-making. In 2017, the National Academies of Sciences, Engineering, and Medicine called for a quantitative systems model to help understand and address this complexity and guide policy decisions. Here, we present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), a dynamic simulation model developed in response to that charge. SOURCE tracks the US population aged ≥12 y through the stages of prescription and illicit opioid (e.g., heroin, illicit fentanyl) misuse and use disorder, addiction treatment, remission, and overdose death. Using data spanning from 1999 to 2020, we highlight how risks of drug use initiation and overdose have evolved in response to essential endogenous feedback mechanisms, including: 1) social influence on drug use initiation and escalation among people who use opioids; 2) risk perception and response based on overdose mortality, influencing potential new initiates; and 3) capacity limits on treatment engagement; as well as other drivers, such as 4) supply-side changes in prescription opioid and heroin availability; and 5) the competing influences of illicit fentanyl and overdose death prevention efforts. Our estimates yield a more nuanced understanding of the historical trajectory of the crisis, providing a basis for projecting future scenarios and informing policy planning.

EMS utilization predictors in a Mobile Integrated Health (MIH) program.

BACKGROUND: The provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patients who do not need urgent care. The goals of this study were (1) to identify factors associated with EMS utilization (911) and (2) their effects on total EMS calls and transports in an MIH program. METHODS: The study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016 and September 2018. The study employed descriptive statistics and Poisson regressions to estimate the effects of covariates on total EMS calls and transports. RESULTS: The typical enrollee is a 60-year-old single Black male living with two other individuals. He has a PCP, takes 12 medications and is compliant with his treatment. The likelihood of calling and/or being transported by EMS was higher for males, patients at high risk for falls, patients with asthma/COPD, psychiatric or behavioral illnesses, and longer travel times to a PCP. Each prescribed medication increased the risk for EMS calls or transports by 4%. The program achieved clear reductions in 911 calls and transports and savings of more than 140,000 USD in the first month. CONCLUSIONS: This study shows that age, marital status, high fall risk scores, the number of medications, psychiatric/behavioral illness, asthma/COPD, CHF, CVA/stroke and medication compliance may be good predictors of EMS use in an MIH setting. MIH programs can help control utilization of EMS care and reduce both EMS calls and transports.

The relation between health insurance and health care disparities among adults with disabilities.

OBJECTIVES: We examined disparities among US adults with disabilities and the degree to which health insurance attenuates disparities by race, ethnicity, and socioeconomic status (SES). METHODS: We pooled data from the 2001-2007 Medical Expenditure Panel Survey on individuals with disabilities aged 18 to 64 years. We modeled measures of access and use as functions of predisposing, enabling, need, and contextual factors. We then included health insurance and examined the extent to which it reduced observed differences by race, ethnicity, and SES. RESULTS: We found evidence of disparities in access and use among adults with disabilities. Adjusting for health insurance reduced these disparities most consistently for emergency department use. Uninsured individuals experienced substantially poorer access across most measures, including reporting a usual source of care and experiencing delays in or being unable to obtain care. CONCLUSIONS: Although health insurance is an important enabling resource among adults with disabilities, its effect on reducing differences by race, ethnicity, and SES on health care access and use was limited. Research exploring the effects of factors such as patient-provider interactions is warranted.

Disparities in access to health care among middle-aged and older adults with disabilities.

Disability is increasing among middle-aged adults and, reversing earlier trends, increasing among older adults as well. Disability is experienced disproportionately by Black and lower socioeconomic status (SES) individuals. We used Medical Expenditure Panel Survey data to examine health care disparities in access to health care for middle-aged (31 to 64 years of age) and older (65+ years of age) adults with disabilities by race and ethnicity, education, and income (n=13,174). Using logistic regression, we examined three measures of potential (e.g., usual source of care), and three measures of realized (e.g., counseling related to smoking) access. Middle-aged and older minority individuals with disabilities had lower relative risks of having usual sources of care and higher relative risks of having suboptimal usual sources of care (e.g., a place rather than a person) than White adults with disabilities. There were SES effects observed for middle-aged adults with disabilities across most measures that were, for certain measures, more pronounced than SES effects among older adults with disabilities. These findings are important, since health resources (e.g., a usual source of care) may mediate relations among disability, morbidity, and mortality. Policy actions that may mitigate the disparities we observed include financial incentives to support access to an optimal usual source of care and mechanisms to foster behavioral interventions related to smoking and exercise. Ensuring that these actions address the specific concerns of individuals with disabilities, such as physical accessibility and provider cultural competency, is essential.

Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis.

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers' capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.

Data Needs in Opioid Systems Modeling: Challenges and Future Directions.

INTRODUCTION: The opioid crisis is a pervasive public health threat in the U.S. Simulation modeling approaches that integrate a systems perspective are used to understand the complexity of this crisis and analyze what policy interventions can best address it. However, limitations in currently available data sources can hamper the quantification of these models. METHODS: To understand and discuss data needs and challenges for opioid systems modeling, a meeting of federal partners, modeling teams, and data experts was held at the U.S. Food and Drug Administration in April 2019. This paper synthesizes the meeting discussions and interprets them in the context of ongoing simulation modeling work. RESULTS: The current landscape of national-level quantitative data sources of potential use in opioid systems modeling is identified, and significant issues within data sources are discussed. Major recommendations on how to improve data sources are to: maintain close collaboration among modeling teams, enhance data collection to better fit modeling needs, focus on bridging the most crucial information gaps, engage in direct and regular interaction between modelers and data experts, and gain a clearer definition of policymakers' research questions and policy goals. CONCLUSIONS: This article provides an important step in identifying and discussing data challenges in opioid research generally and opioid systems modeling specifically. It also identifies opportunities for systems modelers and government agencies to improve opioid systems models.

Effective Market Exclusivity of New Molecular Entities for Rare and Non-rare Diseases.

BACKGROUND: Growth in development, approvals, and revenue of drugs treating rare diseases (orphan drugs) has been increasing over the last four decades, which has drawn substantial attention to these products. Much of this growth has been attributed to the incentives created by the Orphan Drug Act, which includes a seven-year exclusivity period for the approval of rare disease indications. OBJECTIVE: This study aims to compare the effective market exclusivity period of small molecule new molecular entities (NMEs) for rare (orphan) and non-rare (non-orphan) diseases approved by the U.S. Food and Drug Administration (FDA) from 2001-2012. While the overall length of a drug's effective market exclusivity period has been explored previously, there is little empirical research evaluating the differences in its duration between drugs for rare and non-rare diseases. METHODS: Data sources utilized in this analysis included the NME Drug and New Biologic Approvals Reports, Orange Book, Orphan Drug Product Designation Database, Drugs@FDA and IQVIA's National Sales Perspective. We computed the effective market exclusivity period for each NME as the time from NME approval until approval of the first generic competitor. We then regressed the effective market exclusivity period for each NME, on orphan disease status, and other NME market factors using a Cox proportional hazards model. Subsequently, we calculated regression-adjusted median effective market exclusivity periods for both orphan and non-orphan NMEs to estimate effective exclusivity extensions from orphan status. RESULTS: We find that only individual NMEs approved for the treatment of both orphan and non-orphan indications lower the hazard of generic entry (hazard ratio 0.464, p = 0.030) in comparison with non-orphan NMEs with a single indication. The associated additional median survival time for these NMEs is 1.9 years. CONCLUSIONS: NMEs' orphan status per se is not associated with a reduction in the hazard of generic entry and longer effective market exclusivity periods in comparison with non-orphan NMEs. Only NMEs that were approved for the treatment of both orphan and non-orphan diseases experience lower hazard of generic entry and longer exclusivity periods compared with non-orphan drugs with a single indication.

The impact of the abuse-deterrent reformulation of extended-release OxyContin on prescription pain reliever misuse and heroin initiation.

The introduction of abuse-deterrent OxyContin in 2010 was intended to reduce its misuse by making it more tamper resistant. However, some studies have suggested that this reformulation might have had unintended consequences, such as increases in heroin-related deaths. We used the 2005-2014 cross-sectional U.S. National Survey on Drug Use and Health to explore the impact of this reformulation on intermediate outcomes that precede heroin-related deaths for individuals with a history of OxyContin misuse. Our study sample consisted of adults who misused any prescription pain reliever prior to the reformulation of OxyContin (n = 81,400). Those who misused OxyContin prior to the reformulation were considered the exposed group and those who misused other prescription pain relievers prior to the reformulation were considered the unexposed group. We employed multivariate logistic regression under a difference-in-differences framework to examine the effect of the reformulation on five dichotomous outcomes: prescription pain reliever misuse; prescription pain reliever use disorder; heroin use; heroin use disorder; and heroin initiation. We found a net reduction in the odds of prescription pain reliever misuse (OR:0.791, p < 0.001) and heroin initiation (OR:0.422, p = 0.011) after the reformulation for the exposed group relative to the unexposed group. We found no statistically significant effects of the reformulation on prescription pain reliever use disorder (OR: 0.934, p = 0.524), heroin use (OR: 1.014p = 0.941), and heroin use disorder (OR: 1.063, p = 0.804). Thus, the reformulation of OxyContin appears to have reduced prescription pain reliever misuse without contributing to relatively greater new heroin use among those who misused OxyContin prior to the reformulation.

Impacts of a Medicaid Wraparound Model Demonstration Program on Youth Specialty Mental Health Services Use.

Effective coordination of mental health care is critical in Medicaid wraparound model programs for youth. This study examined participation over time in mental health services for youth diverted or transitioned from residential care to a Medicaid wraparound demonstration program. Youth in wraparound had more sustained use of mental health outpatient clinic services than did propensity score matched youth who were not in wraparound. However, the rate of outpatient clinic follow-up after inpatient discharge was no greater in wraparound. Routine assessment of wraparound programs' impacts on receipt of mental health care may inform the development of Medicaid wraparound program performance standards.

Effects of gender, disability, and age in the receipt of preventive services.

PURPOSE OF THE STUDY: We extend research to examine relations between gender, disability, and age in the receipt of preventive services. DESIGN AND METHODS: We pool Medical Expenditure Panel Survey data for years 2001-2007. Using logit models, we examine the relations between gender, disability, and age and the receipt of preventive services. RESULTS: For most services, both women and men with disabilities had higher probabilities of receiving preventive services relative to those without disabilities. There was a pattern of more significant differences for men relative to women. Predicted probabilities for receipt of services were significantly higher among older adults relative to younger adults. A usual source of care was a significant predictor across services. For example, we estimate that adults aged 18-64 with a place as a usual source of care received 59% of recommended services, whereas those with a person as a source of care received 63% of services relative to 47% for those without a usual source of care. Among older adults, the predicted percentage of preventive services received for no usual source of care was 52% and that for a place or a person as a usual source of care were 71% and 76%, respectively. Across gender, disability, and age, receipt of a range of clinical preventive services is suboptimal. IMPLICATIONS: Policy actions that may mitigate the differences we observed include mechanisms to support access to a usual source of care, financial incentives to enhance the receipt of preventive services, and implementation of community-based prevention services with attention to their linkage to clinical care.