Inovalon’s latest analysis draws on an immense dataset from the MORE² Registry that includes nationally representative populations of individuals insured by commercial, Medicare Advantage, and Managed Medicaid plans. The company’s May report shows that only 19.8 percent of Medicare Advantage patients received recommended treatments for Opioid Use Disorder compared to over 30 percent of commercial patients. Further data reveals that women are 1.3 times more likely than men to continue using opioids post-hospitalization, yet men are more likely to receive guideline-recommended treatment.
West Virginia and Kentucky have the highest Opioid Use Disorder (OUD) diagnosis rates, while Colorado and South Dakota are among the lowest. A steep drop-off in treatment rates among older patients following OUD related hospitalization is also among the key findings, with just 11.8 percent of those aged 65 and above receiving recommended therapy. Overall, trends show a moderate uptick in opioid abuse diagnoses in the commercial population and increasing hospitalization rates, so what are the next priorities in research for this highly contentious area? We asked Inovalon's VP of Research Science, Christie Teigland, to find out.
What challenges or innovations were involved in analyzing such a large and diverse dataset, especially across payer types like commercial, Medicaid, and Medicare Advantage?
The Inovalon research team, which consists of economists, biostatisticians, research scientists, epidemiologists, pharmacists, and health outcomes researchers, has worked with our large national all-payer datasets for more than a decade. Since we tend to see major differences across different insurance coverages, we always recommend stratifying any research results by payer type. This usually gives us and our partners more insight into issues like gaps in care, access, and quality issues, and differences in resource use and cost, among other factors we investigate.
That said, claims data are inherently messy, and there are always surprises. Because of this, we need to be vigilant in reviewing the data. For example, this includes finding extreme outliers before running an entire analysis, as well as carefully reviewing programming codes and results to ensure they make sense. We also have many processes in place and advanced analytical tools for assuring our results are accurate and comparable.
What systemic factors do you believe are driving disparities between Medicare and commercial patients?
When interpreting the data, the age difference between the two populations is certainly driving disparities. Most Medicare beneficiaries are over the age of 65, though there is a growing population of Medicare enrollees who are younger but eligible for Medicare due to disability, which can also be a factor in poor outcomes.
In this study, the Medicare segment we evaluated includes those enrolled in private Medicare Advantage (MA) plans. Recent research demonstrated that MA enrolls patients who have a higher number of chronic conditions, are much more socially disadvantaged, and more likely to be disabled compared to traditional Medicare Fee-for-Service. Because of these differences, the MA population looks more like the Medicaid population than the commercial population. Additionally, social risk factors, such as low income, low education, low language proficiency, and living alone, are all associated with higher rates of mental illness and the use of more medications, including pain medications that can lead to opioid use disorder.
How might the report inform gender-specific approaches to care or clinical follow-up?
The data show that females are about 10 percent less likely to have an opioid related hospitalization, and eight percent less likely to receive a recommended treatment within 30 days after discharge. However, females are 34 percent more likely to continue using prescription opioids after an opioid-related hospital stay.
Further research is needed to better understand why continued opioid use appears to be higher among females with OUD, including factors contributing to ongoing prescriptions following OUD related hospitalizations. At the same time, it’s important to explore why fewer women are receiving FDA-recommended treatments, which are critical for preventing overdoses and improving overall health outcomes. Improved follow-up care for female patients after an opioid use-related hospitalization is essential to ensure they receive optimal and equitable treatment.
How should local health departments interpret the findings, and what role can real-world evidence play in informing state-level policy or intervention strategies?
There have been some advancements at the federal level around OUD treatment. This includes removing the requirement that prescriptions for therapies like naltrexone and methadone be written by certified specialists, as well as removing limits on the number of patients these specialists can treat. Still, our research found that fewer than one in three patients with a diagnosis of OUD and a related hospitalization receive the FDA recommended treatment.
With this in mind, state and local health departments should explore ways that they may increase access to these critical treatments and educate their local communities on OUD and treatment access. For example, they might consider opening up more methadone treatment centers, which provide medication-assisted treatment for people with OUD using methadone, a long-acting full opioid agonist. In a follow-up analysis, we found very low utilization of non-residential opioid treatment facilities (less than nine percent of OUD patients). Further analysis is needed to understand why reported use of these facilities is so low. For example, these treatment centers have been somewhat controversial within local communities due to lingering stigma, misconceptions, and community concerns. By educating communities around the benefits of these services and investing in the infrastructure, this could contribute to reduced opioid dependence, overdoses, and deaths.
Ongoing vigilance is crucial when prescribing opioids to patients with OUD to ensure they are both necessary and the last resort to treat pain management. Behavioral interventions can offer highly effective alternatives, making it critical that trained professionals are both available and accessible to provide these alternative therapies.
Treating the mental illnesses that frequently accompany OUD is also essential to reducing incidence of OUD. In our data, we found that about 50 percent of OUD patients were being treated for co-occurring psychiatric conditions. Our previous research has shown that adherence to antipsychotics, antidepressants, and antianxiety medications is very low, which can further contribute to patients developing OUD and interfere with their ability to make health care decisions. This is especially true among the underserved populations, making the accessibility of resources that address social risk essential to improving health outcomes, including those related to continued opioid abuse.
What can be done to better support senior patients?
As our data reveal, seniors age 65 and older with OUD – especially women – are the least likely to receive FDA recommended treatments following an opioid-related hospitalization. Better care coordination among patients’ care teams and following up after their discharge from the hospital are essential to improving outcomes in this population.
However, this age group is more complicate, as they tend to have more chronic conditions that may cause pain than other age groups and may have a real need for pain relieving treatment. Because of this, the age group was most likely to continue use of opioids like oxycodone, methadone, morphine, fentanyl, and hydrocodone after hospitalization.
A geriatrician I used to work with always said, “Prescribing drugs is easy, but actually addressing the root cause of the problem is hard.” Providers must carefully weigh the benefits versus the costs of continuing to prescribe opioids for their senior patients, and consider how alternative treatments might be more beneficial for their health outcomes.
How are you integrating SDOH into predictive modeling or intervention planning for opioid use disorder?
We have done considerable research and published several manuscripts evaluating the impact of social drivers of health (SDOH) on patients’ access to treatment, their likelihood of hospitalization, and adherence to prescribed medications, specifically for patients with severe mental illness, cancers, and advanced Parkinson’s disease. These informative studies could help guide similar research in the OUD population.
Are you exploring AI or predictive analytics to intervene earlier in the care continuum?
Most definitely. In fact, we co-authored a study published in Hepatology Communications last year exploring which factors impact the likelihood of at-risk patients getting early surveillance for hepatocellular cancer (liver cancer), which found that patients with racial and socioeconomically disadvantaged backgrounds were less likely to receive surveillance and curative treatments, resulting in higher healthcare costs and poorer outcomes.
The studies also used multivariable modelling to predict future outcomes such as who is most likely to be admitted to the hospital or emergency room, and who is least likely to have access to advanced treatments such as the novel new CAR-T therapies – or even new device aided therapies. There is so much potential to really drill down into the root causes of disparities in care in order to design effective interventions.
Our team is just breaking the ice on using AI. We‘re working on some exciting pilot applications and are optimistic about how AI can move us forward faster. However, we are equally cautious, as AI is an extremely powerful tool that we must use responsibly and work to fully understand its capabilities and limitations, especially as the research we do has real impacts on people’s lives and health outcomes.
What are your hopes and aims for this report and how do you anticipate its impact on policy and results?
The CDC reported that overdose deaths in the US decreased 26.9 percent in 2024 compared to 2023. This inspired our team to dig deeper into what happens before overdose deaths occur, including rates of OUD diagnosis, OUD related hospitalizations, and receipt of recommended treatment after hospital discharge.
Our goal was to generate real-world information to better inform providers, health plans, and policy makers, and our research provides new insights into the downstream issues that need to be addressed to continue the decline we’re seeing in opioid-related deaths in the coming years. We must ensure that patients have access to the right care providers and the right treatments to help avoid negative health outcomes, including death. Our goal was to uncover which populations were at the highest risk, and to learn in which subgroups we see the largest inequities in access to care and treatment so payers, providers, and local and federal agencies can focus their resources, however limited, on the areas of greatest need for their communities to improve their population’s overall health.