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PINC AI™ Data Reveals Significant Health Disparities Among Patients Diagnosed with Opioid Use Disorder

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Key takeaways:

  • Opioid use disorder (OUD) remains a public health concern due to the devastating impacts it has on individuals, families, society and the healthcare system.
  • PINC AI™ Applied Sciences (PAS) data shows patients diagnosed with OUD were younger, and more likely to be male and Native American or White.
  • Patients with OUD diagnosis were more likely to live below the poverty line than those without OUD (e.g., 66.9 percent versus 40.8 percent of ED outpatients and 47.5 percent versus 21.4 percent of inpatients were on Medicaid or uninsured)

New data from PINC AI™ Applied Sciences (PAS) reveals that opioid use disorder (OUD) disproportionately affects patient populations of certain races, as well as those living in poverty.

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The analysis shows that patients with an OUD diagnosis were younger than their non-OUD counterparts (ED outpatients: 42 versus 47 years of age; inpatients: 50 versus 59 years of age).

Compared to peers without OUD, patients with OUD were also more likely to be male (56.2 percent versus 42.2 percent among ED outpatients; 48.6 percent vs 42.3 percent among inpatients) and Native American (1.7 percent versus 1.4 percent among ED outpatients; 1.6 percent versus 1.2 percent among inpatients) or White (76.8 percent versus 64.6 percent among ED outpatients; 77.4 percent versus 72.3 percent among inpatients).

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In addition to age and race, the data shows several statistics related to socioeconomic status, including higher rates of Medicaid insurance, uninsured and homelessness for OUD patients in both the ED and inpatient settings.

Implications for Health Systems

Many low-income and minority earners have less access to medical care – issues exacerbated by the potential legal issues associated with addiction. This means that many of these patients forego or wait longer periods of time to obtain treatment, which can lead to exacerbated conditions and more intensive healthcare needs – all of which adds to the total expense of provided care.

Studies also show that 87 percent of people with OUD do not receive evidence-based treatment, and there are significant demographic disparities in pain management and development and management of OUD.

With higher rates of OUD, Native Americans often receive care in settings that lack funding and resources to combat OUD, which can have a severe negative impact on long-term outcomes. According to a recent study published in the BMJ Journals, researchers found that opioid overdose deaths among American Indian and Alaska Native communities increased five-fold from 1999 to 2019.

Looking at the other ethnic population incurring disproportionate rates of OUD, White patients are more likely to receive more pain management as part of their care, even though they are also at higher risk of developing OUD.

The PAS analysis highlights the existing inequities in OUD and points to broader systemic factors that disproportionately affect communities. The types of opioids driving these trends have changed over the years, but many of the underlying social determinants of health (SDOH) that drive these patterns have remained the same.

Collectively, healthcare needs to address the SDOH, OUD and myriad of inequities experienced among patient populations to improve health and outcomes, and positively impact hospital and health system margins.

Collaborating to Reduce Health Disparities

Premier and the PAS team are collaborating with the life sciences industry, leading health systems, community organizations and patient advocacy groups to co-create solutions that can help reduce disparities, improve outcomes and deliver equitable healthcare for all.

  • Driving action through research. PAS is working with Premier’s more than 4,400 health system members and the life sciences industry to support the collection and use of accurate equity-related data, improve clinical trial and research diversity, and engage the right stakeholders. As a recent example, the PAS team partnered with Henry Ford Innovations and eight leading life sciences organizations to host the inaugural “Advancing Health Equity Through innovation and Collaboration” initiative where they discussed vital strategies to address health inequities in a group of people who have been historically marginalized and underrepresented.
  • Leveraging standardized data and analytics. By standardizing the collection and use of robust equity-related data, public health officials, clinical researchers and health systems can learn more about SDOH, including the impact on health outcomes, costs and healthcare resource utilization. Combining patient and community voices with the comprehensive data contained with the PINC AI™ Healthcare Database (PHD) can help lead to deeper insights and inform solutions to address drivers of health and advance health equity.
  • Applying business intelligence to understand health inequities. Hospital data that shows opioid visits and utilization by race, ethnicity and payer in the inpatient and ED settings can help providers understand where they have opportunities to address SDOH and inequities in care. PAS conducted an analysis looking at these factors in the ED across nearly 750 hospitals to understand health disparities and the affected communities.
  • Building a Health Equity Collaborative for solution development in real time. The PINC AI™ Health Equity Collaborative will foster co-creation of solutions to help clinicians examine their own biases, reduce harm and drive clinical quality improvements.

Reducing disparities across health outcomes requires a diverse and inclusive environment where all patients can thrive and achieve optimal health outcomes. This will take everyone from the life sciences industry to community organizations to health systems working together to develop solutions that can be customized to patients’ needs and delivered at the right time and at the right cost.

Methodology 

Leveraging one of the largest hospital discharge systems in the U.S., the PINC AI ™ Healthcare Database (PHD), data scientists analyzed all discharges for ED outpatient visits and inpatient admissions occurred during Q1 of 2017 and Q1 of 2022. OUD was defined as having a principal or secondary discharge diagnosis of opioid abuse (ICD-10 diagnosis codes: F11.2 percent), opioid dependence (ICD-10 diagnosis codes: F11.2 percent), or unspecified opioid use (ICD-10 diagnosis codes: F11.9 percent) disorder. Prevalence of OUD was estimated for ED outpatient visits and inpatient admissions separately. Mean total cost of care was also reported for ED outpatient visits and inpatient admissions separately by OUD status. National estimates were created by leveraging prevalence and cost estimates from the PHD analysis and the total number of ED outpatient visits reported from the 2018 National Hospital Ambulatory Medical Care Survey and the total number of inpatient visits from the 2020 American Hospital Association Annual Survey.   

Read the additional blogs in the PINC AI™ opioids data series:
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