Funded Projects

Chronic pain is a persistent source of disability and reduced quality of life for aging adults. Chronic pain-related outcomes are disproportionately worse for aging African Americans, who report greater pain severity and worse pain-related disability compared to White peers. A significant pain risk factor for African Americans is chronic stress (including family-related stress), which is worsened by structural inequities that affect this population. Although many African Americans identify family support as critical for pain self-management, this influence has not been studied thoroughly. This project will study how pain conditions develop and persist for aging African Americans by analyzing existing data from African American participants in two large aging studies: Midlife in the U.S. (721 participants) and the Health and Retirement Study (2,698 participants). The research aims to determine how family emotional climate affects pain risk, taking into account structural factors like discrimination, socioeconomic disparity, and the influence of various neighborhood settings.

Guidelines published by the Centers for Disease Control and Prevention in 2016 recommended gradual reductions in opioid medication doses (opioid tapering) for people with chronic pain and substance use disorder and recommended that those patients with pain and opioid use disorder should be switched to opioid use disorder medications. Despite wide implementation, little is known about the consequences of opioid tapering among patients with co-occurring chronic pain and substance use disorder. This project will use various databases (Cerner Real-World DataTM, American Hospital Association data, and U.S. Census data) to create a representative electronic health records database. This database will be used to determine the relationship between opioid tapering, multidisciplinary pain treatment, and medications for opioid use disorder – as well as monitor outcomes for patients with chronic pain and co-occurring substance use disorder.

Monitoring and reporting substance use and substance use disorder is difficult to obtain in real-time using conventional methods. However, social media captures large amounts of data about substance use that are reported by diverse groups of people. Analysis of these data can provide population- or subpopulation-level insights, at low cost and in near real-time. This project aims to convert large amounts of social media data on substance use into actionable knowledge using advanced natural language processing and artificial intelligence approaches. The researchers will publicly release the aggregated statistics through a dedicated dashboard and provide user-friendly, open-source tools to determine trends and analyze disparities.

Addressing the current opioid overdose crisis requires tracking risky opioid use in a timely manner so that public health agencies can plan accordingly and supply life-saving resources. American Indian Tribes often lack such tools, even though American Indians and Alaska Natives have the highest rates of opioid overdose fatalities. This project will adapt commercialized monitoring technologies for use in Tribal communities, in consultation with affected Tribes. Through a partnership with a Tribal Fire Department and a software company providing data analytics for public safety agencies, this research will build a near real-time opioid overdose dashboard for use within Tribal boundaries. The findings may also improve data collection and outbreak monitoring for other substances, including methamphetamine and cocaine.

This research provides support to strengthen data management, data sharing, and data readiness efforts within the HEAL Initiative. This support further fosters collaboration among HEAL awardees and enables maximal data discoverability, interoperability, and reuse by aligning with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. It also provides an opportunity for existing HEAL Initiative award recipients to increase data “FAIR”-ness, participate in coordinated HEAL Initiative activities to build community around data sharing, and foster sustainability of HEAL Initiative digital assets.

Effective overdose prevention requires timely, location-specific data to efficiently direct resources and interventions as well as to inform healthcare policy. However, rarely is such information available, resulting in responses that are frequently too late. This project will partner with local government agencies from Los Angeles County, California, to rapidly acquire and analyze information in near real-time from multiple sources to identify overdose hotspots and determine overdose metrics. This information will be used to develop a publicly available Rapid Overdose Surveillance Los Angeles online dashboard with built-in analytics. The dashboard will help determine the scope and specifics of overdose and opioid use in Los Angeles County to help target response and guide mobile addiction treatment and harm reduction services.

Effective responses to the highly dynamic overdose crisis require accurate and timely information about the timing and location of drug overdoses, which is currently reported mainly through death certificates that take time to become available and thus limit life-saving responses. This project will comprehensively evaluate, optimize, and assess barriers and facilitators to adoption of a surveillance tool developed by the New York City Office of the Chief Medical Examiner. The tool uses data routinely collected during death investigations to predict in near real-time whether a death was due to an unintentional drug overdose. The findings will inform drug overdose mortality surveillance efforts in other states.

Sickle cell disease is an inherited blood disorder affecting about 100,000 Americans and more than 20 million people worldwide. It is caused by a mutation in the gene for beta-globin that results in the characteristic sickled shape of red blood cells, life-long severe pain, and shortened lifespan. Sickle cell disease pain episodes are usually unanticipated, making it hard for people with the condition to manage their pain and putting them at risk for increased use of opioids and poor health outcomes. This project will use existing real-time health data to identify factors that can predict onset, severity, and worsening of daily pain in children with sickle cell disease.

Temporomandibular joint (TMJ) disorders, which affect the joint connecting the lower jaw and the skull, are common and difficult chronic pain conditions. Pain management strategies that harness the body’s own pain relief mechanisms (including placebo effects in which pain relief cannot be attributed to a specific treatment), can reduce the severity and duration of TMJ-related chronic pain. Although research suggests that placebo effects may have a genetic basis, few, if any, genetic studies have examined this possibility in individuals with TMJ disorders. This project will use in-depth genetic, sociodemographic, clinical, and psychological data collected from adults with chronic TMJ disorders to better understand how the placebo effect works.

Musculoskeletal pain is common, costly, and affects millions of Americans. Clinical guidelines strongly recommend complementary and integrative treatments such as physical therapy, but nearly half of people receiving physical therapy for musculoskeletal pain seek additional care. Additional treatments such as medication and surgery are more aggressive and carry higher risk. This project will use data from a large physical therapy dataset and nationwide medical claims data to investigate why some people do not respond well to physical therapy for musculoskeletal pain, toward finding safe and effective options for these individuals.

It is unclear if long-term use of opioids by head and neck cancer patients affects risk for depression, which is higher in this population compared to people without cancer. This knowledge could inform interventions such as increased opioid prescription safety or alternative pain management approaches and could thus help reduce the risk for depression-related outcomes. This project will use data from a national cancer database linked to Medicare claims and a Veterans Administration database to determine whether people with head and neck cancer that take opioid medications for more than 90 days have increased risk for new-onset or worsening depression or suicide death.

Cerebral palsy is the most common physical disability in children. Those who have this condition experience pain throughout their lives. Although opioids are generally not recommended, many adults with cerebral palsy are prescribed them for pain. This project will assess the incidence of chronic pain conditions in adults with and without cerebral palsy as well as measure opioid treatment-related health outcomes in adults with cerebral palsy. This research will also evaluate pain treatment disparities related to race/ethnicity and insurance coverage using national medical claims databases.