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

SBIR 第一阶段：用于初级保健门诊的阿片类药物逐渐减少临床决策支持工具

• 批准号: 2135508
• 负责人: Justin Kromelow
• 金额: $ 24.76万
• 依托单位: OPOS, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135508&HistoricalAwards=false
• 关键词: SBIR; Phase; Opioid; Taper; Clinical

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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是减少阿片类药物依赖。 长期使用类阿片的一个关键挑战是在确定最佳剂量以管理相关风险和副作用的基础上平衡获益和风险。 阿片类药物逐渐减少用于管理这种风险，可能持续数周到数年。然而，在自愿减少长期阿片类药物剂量后，许多患者报告功能，睡眠，焦虑和情绪得到改善，而不会加重疼痛甚至降低疼痛水平。此外，锥体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药物或非阿片类止痛药。 近1800万美国人可能受益于阿片类药物减量，以改善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，患者可能无法获得疼痛专家的帮助，只能依靠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阿片类药物逐渐减少的关键工具，其中近一半的阿片类药物是处方药。使用临床决策支持工具，初级保健医生将有一个虚拟的疼痛专家建议预期的预测结果和行动，以确保成功的锥形与直接反馈的病人。这个小企业创新研究（SBIR）第一阶段项目将应用机器学习技术开发算法，使用一个数据集，描述成功和不成功的锥形与临床数据，医疗决策，患者体验以及医生/患者互动和沟通。预测模型将基于关于患者的身体、心理、社会和情感体验的实时数据，告知医疗决策者连续患者事件的可能性及其对逐渐减少结果的影响。 这项创新将在智能手机平台上实现，将医生/患者医疗决策模型从临床环境扩展到患者环境。这将创建一个新的以患者为中心的锥形模型，其中通过优化患者体验来告知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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。