Funded Projects

Pain is one of the most common and debilitating symptoms of a wide range of injuries and diseases. Safe and effective alternatives for treating pain that reduce dependence on opioids are, therefore, a primary goal of the NIH. This project proposes a non-invasive, non-pharmacological alternative to treat pain by combining an innovative electroencephalography (EEG)-based Neurofeedback (NF) solution in an immersive virtual reality (VR) environment. NF and VR have been shown to independently produce ameliorative effects on pain, and it is hypothesized that an NF training in VR would have synergistic effects, as VR would distract from pain perception to improve patient compliance in more engaging NF protocols that improve their ability to control pain perception. In the scope of this project, we will initially focus our work on chronic low back pain (cLBP), as this is a growing segment of chronic pain sufferers with a 39 percent worldwide lifetime prevalence, and whose sufferers have historically been heavy users of opiates; later stages of this project will expand this application to address other forms of pain.

Millions of Americans undergo surgery each year, with fewer than half of patients reporting adequate postoperative pain relief and approximately 75 percent reporting moderate to severe postoperative pain. Gaps in postoperative pain management that lead to the unnecessary introduction and over-prescription of opioids continue to exacerbate the opioid crisis, but virtual reality (VR) has been demonstrated to be an effective strategy for pain management. This project will enhance and improve the functionality of a VR-based technology, AppliedVR, to provide acute perioperative pain management through a new software-based VR medical device, RelieVRx™. As a non-opioid alternative intended to reduce postoperative pain, RelieVRx can potentially reduce the need for and utilization of opioids in the postoperative setting.

Current drug-screening immunoassays use benchtop analyzers that require experienced personnel, time, and a laboratory setup. Physicians without access to in-house testing have to send out patient samples for screening, resulting in unacceptable delays in the treatment of patients who are potentially suffering from chronic pain. This project, a partnership with BreviTest Technologies, LLC, aims to develop a low-cost, point-of-care (POC) urine drug testing (UDT) device to detect opioids. The goal is for a portable platform to deliver quantitative performance similar to a standard laboratory test for opioids within a 10-minute run time. If successful, this will provide a technology capable of performing rapid quantifications of urine drug levels in a physician’s office, providing an invaluable tool to render more effective pain management dosing to patients, thus paving the way toward lower toxicity and a better quality of life.

This project provides protected time for training and research activities that are required for an independent scientific career in delivering evidence-based treatments for people with opioid use disorder. The increasing presence of fentanyl in the drug supply creates challenges for the use of buprenorphine, because both patients and physicians want to avoid causing withdrawal. This research will interview both patients and physicians to understand their concerns and experiences and work with them to develop a buprenorphine induction toolkit to help balance the advantages of buprenorphine treatment against concerns about the potential presence of unknown fentanyl. 

This project creates the HEAL Data2Action Modeling and Economic Resource Center that will conduct research as well as support the HEAL Data2Action Innovation Projects with expertise and consultation about simulation modeling and economic evaluation methods. The consultation service will advise on how to select and use various research methods, including economic evaluation, simulation modeling, advanced statistical analysis, behavioral economics, treatment program organization research, and cost analysis. The center will use a dynamic simulation model of opioid use disorder to enhance data-driven decision making. The center will also provide online training resources, tools, and other resources to assess a variety of economic aspects related to the HEAL Data2Action Innovation Projects.

Reversing an opioid overdose requires a rapid response not available through standard emergency procedures. The Opioid Rapid Response System recruits and trains citizen responders to reverse overdoses with naloxone. It uses widely disseminated smart phone apps linking responders to an overdose through the 911 system. This project will complete the development of this system, test how well it works to reverse an opioid overdose, and prepare to share it widely. 

Older adults make up more than half of all surgical patients in the United States, putting them at risk for a range of harmful outcomes including misusing opioids, developing opioid use disorder (OUD), opioid overdose, and surgical complications. This project seeks to understand whether pre-surgery interventions can prevent harmful opioid-related outcomes. The research will combine data from a registry of electronic health records and from Medicare claims data to learn about the relationship between these interventions and opioid-related outcomes including persistent opioid use, OUD, and other harmful outcomes.

Neonatal Opioid Withdrawal Syndrome (NOWS) affects a growing number of neonates each year due to the ongoing opioid epidemic ravaging the United States. Complex neurobehavioral observation of newborns is the primary modality used. It is subjective and time-consuming by nature, requires significant expertise, and can lead to delays in treatment. The goal of this project is to develop an innovative, low-cost, non-invasive, and easy-to-use brain monitor to objectively assess the severity of withdrawal symptoms in newborns exposed to opioids and provide evidence-based decision support to care providers to improve both short- and long-term developmental outcomes. This device, referred to as NeoGUARD, is based on the continuous, automated, and real-time monitoring of brain function to detect EEG abnormalities shown to be related to NOWS and determine severity to guide pharmacological intervention. This study will focus on the initial prototyping and refinement of the hardware and software, as well as initial evaluations of its use.

Timely and accurate surveillance of fatal and non-fatal overdoses is necessary in light of the worsening overdose crisis, but data is rarely available in real-time. Tracking non-fatal overdoses is especially important because patients who overdose once are likely to experience additional and potentially fatal overdoses. This project aims to increase the quality and timeliness of non-fatal overdose data estimates by analyzing clinicians’ notes rather than clinical codes from emergency department and emergency medical services records. The datasets and models produced from this research will be used to build an interactive dashboard with up-to-date, county-level overdose-surveillance estimates for use by Kentucky first responders to aid in rapid allocation of resources.

Current clinical screening measures for opioid misuse are underused and susceptible to bias. This project will develop Beacon-OUD, a digital opioid misuse assessment. The tool generates an automated, standardized score, preventing potential judgements related to patient’s status and circumstances, limiting stigma. The research will further advance Beacon-OUD into a commercial product for use both as a stand-alone tool and as an electronic health record-integrated solution to encourage objective opioid misuse screening in large health care systems. 

Emergency departments (EDs) are key settings for identifying and treating opioid use disorder (OUD), but EDs are underused for this purpose. This project aims to develop a data system that automates and integrates electronic health record and administrative data from EDs into the Clinical Emergency Department Registry, partnering with the American College of Emergency Physicians. The research will assess the digital readiness of ED systems before developing and deploying the enhanced ED OUD data infrastructure. This research aims to guide near-real time hospital quality improvement initiatives, toward development of a web-based, near-real time dashboard that can be used in EDs across the country.

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.