SBIR Phase I: An Opioid Taper Clinical Decision Support Tool for Use in a Primary Care Outpatient Setting

这一小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是减少阿片类药物依赖。长期使用阿片类药物的一个关键挑战是，在确定管理相关风险和副作用的最佳剂量的基础上，平衡收益和风险。阿片类药物减量被用来管理这一风险，可能持续数周至数年。然而，在自愿减少长期阿片类药物剂量后，许多患者报告说，在功能、睡眠、焦虑和情绪方面有所改善，而不会加剧疼痛，甚至疼痛程度降低。此外，缩减通常用于管理阿片类药物耐受性、痛觉过敏、在手术前实现更有效的疼痛管理，或过渡到另一种形式的阿片类或非阿片类止痛药。近1800万美国人可能受益于阿片类药物的缩减，以改善对其慢性疼痛的长期管理，并提高慢性阿片类药物治疗的安全性和有效性。特别是，在农村社区，患者可能无法找到疼痛专家，并依赖他们的初级保健医生进行慢性疼痛管理。拟议的技术为农村初级保健医生提供了减少阿片类药物的关键工具，农村初级保健医生几乎一半的阿片类药物都是由农村初级保健医生开的。使用临床决策支持工具，初级保健医生将拥有一个虚拟的疼痛专家，为预期的预测结果和行动提供建议，以确保成功的锥化，并从患者那里获得直接反馈。这个小型企业创新研究(SBIR)第一阶段项目将应用机器学习技术，使用描述成功和不成功的锥化的数据集来开发算法，这些数据集包括临床数据、医疗决策、患者体验以及医生/患者的互动和交流。预测模型将根据有关患者的生理、心理、社会和情感体验的实时数据，向医疗决策者告知连续患者事件的可能性及其对缩减结果的影响。这项创新将在智能手机平台上实施，将医生/患者的医疗决策模式从临床环境扩展到患者环境。这将创建一个以患者为中心的缩减的新模式，其中通过优化患者体验来了解估计的临床结果和相关行动。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.