The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to reduce opioid dependence. A critical challenge in the use of opioids on a long-term basis is balancing benefit and risk, based on determining the optimal dosage to manage the associated risks against side effects. Opioid tapers are used to manage this risk and may last from several weeks to several years. However, following the voluntary reduction of long-term opioid dosages, many patients report improvements in function, sleep, anxiety, and mood without worsening pain or even with decreased pain levels. Furthermore, tapers are typically used to manage opioid tolerance, hyperalgesia, enable more effective pain management prior to surgical procedures, or transition to another form of opioids or non-opioid pain medication. Nearly 18 million Americans may benefit from an opioid taper to improve the long-term management of their chronic pain and improve the safety and effectiveness of chronic opioid therapy. In particular, in rural communities, patients may not have access to pain specialists and rely on their primary care physicians for chronic pain management. The proposed technology provides a critical tool for opioid tapering to rural primary care physicians, where almost half of the opioids are prescribed. Using the clinical decision support tool, primary care physicians will have a virtual pain specialist advising of the anticipated predictive outcomes and actions to ensure a successful taper with direct feedback from the patient.This Small Business Innovation Research (SBIR) Phase I project will apply machine learning techniques to develop algorithms using a dataset that describes successful and unsuccessful tapers with clinical data, medical decision making, patient experience, and physician /patient interaction and communication. The predictive model will inform the medical decision-maker of the likelihood of successive patient events and their impact on the taper outcome based on real-time data about the patient's physical, psychological, social, and emotional experience. This innovation will be implemented on a smartphone platform to extend the physician / patient medical decision model beyond the clinical setting into the patient's environment. This will create a new model of a patient-centric taper wherein the estimated clinical outcomes and associated actions are informed by optimizing the patient experience.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
