Predictive tool to prevent overdose in patients treated with prescription opioids

预防接受处方阿片类药物治疗的患者服用过量的预测工具

• 批准号: 9360093
• 负责人: Maciek Sasinowski
• 金额: $ 89.18万
• 依托单位: VENEBIO GROUP, LLC
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9360093
• 关键词: Acute Pain; Address; Adult; Agreement; Algorithmic Software; Algorithms; American; Analgesics; Assisted Living Facilities; Awareness; Behavior; Cessation of life; Clinical; Clinical Data; Clinical Decision Support Systems; Clinical Management; Code; Comorbidity; Computer software; Computerized Medical Record; Computers; Consensus; Databases; Development; Diagnostic; Economic Burden; Education; Educational Materials; Epidemic; Event; Focus Groups; Funding; Goals; Grouping; Health; Health Personnel; Healthcare; Home environment; ICD-9; Individual; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Internet; Legal patent; Measures; Medical; Medicine; Methods; Morbidity - disease rate; Opioid; Opioid Analgesics; Outcome; Overdose; Pain management; Patient Education; Patient risk; Patients; Performance; Pharmacy facility; Phase; Pilot Projects; Poisoning; Policies; Population; Predictive Value; Primary Health Care; Provider; Public Health; Quality Control; Research; Resources; Risk; Risk Factors; Safety Management; Scientist; Secure; Sensitivity and Specificity; Site; Software Tools; Surveys; System; Technology; Testing; Time; Toxic effect; United States; Update; Validation; Ventilatory Depression; Work; aged; base; chronic pain; clinically relevant; cost; design; diagnostic accuracy; epidemiology study; evidence base; experience; health care economics; improved; indexing; individual patient; innovation; mortality; overdose death; personalized decision; personalized medicine; predictive tools; prescription opioid; prevent; prospective; response; satisfaction; software systems; tool

Problem: Over the last two decades, unintentional opioid-related overdose has emerged as a major public health threat in the United States. This increasingly common, yet preventable, cause of morbidity and death among users of prescription opioids is partially due to a substantial expansion in the prescription of opioid analgesics to manage acute and chronic pain conditions. Within any given year during the past five, 15% of the U.S. population filled at least one opioid prescription. In 2012, 259 million opioid prescriptions were written in the U.S. – enough for every American adult to have one bottle of opioid painkillers in their home medicine cabinet. In 2013, nearly two million Americans aged 12 or older either abused or were dependent on opioid painkillers. Opioid poisoning or overdose deaths have more than quadrupled from 4,030 in 1999 to 18,893 in 2014. Total prescription opioid overdose costs in the U.S. were more than $20 billion in 2009.This is a significant and rapidly growing problem. Solution: Venebio Opioid Advisor (VOA) is a clinical decision support system (CDSS) based on VG’s existing, patent-pending, risk-index algorithm that accurately identifies individuals at risk for overdose or serious opioid-induced respiratory depression (OIRD) by utilizing evidence-based clinical data gathered from patient electronic medical records (EMRs) as opioids are being prescribed. VOA will be delivered via a stand-alone computer application, embedded in an EMR system, or alternatively located on a remote server accessible through a secure Internet connection. VOA will extract a patient’s relevant clinical data automatically from the EMR, assess the patient’s risk for opioid overdose, and present the patient’s risk score directly to the health care provider – enabling evidence-based guidance and education that is personalized to the individual patient's specific risk factor profile. The ability to identify individuals at elevated risk of experiencing prescription opioid-related toxicity or opioid overdose will provide awareness of the individual risk level to both the health care provider and the patient. Methods: The overarching objective of our proposed Phase II research is first to refine and validate the clinical content used to create the existing Venebio Opioid Advisor algorithm, then to incorporate this refined information, along with the additional, evidence-based guidance and educational content, into a clinical decision support system, and finally to validate this CDSS during a prospective pilot study of VOA in the real-world clinical pain management setting.

问题：在过去的二十年里，无意中与阿片类药物相关的过量用药已成为美国的一个主要公共卫生威胁。处方类阿片使用者中这种日益常见但可预防的发病和死亡原因部分是由于类阿片镇痛剂处方的大幅扩展，以管理急性和慢性疼痛状况。在过去五年的任何一年中，15%的美国人口至少服用了一种阿片类药物。2012年，美国开出了2.59亿张阿片类药物处方，足以让每个美国成年人在家里的药柜里放一瓶阿片类止痛药。2013年，近200万12岁或以上的美国人滥用或依赖阿片类止痛药。阿片类药物中毒或过量死亡人数从1999年的4，030人增加到2014年的18，893人。2009年，美国处方阿片类药物过量的总成本超过200亿美元，这是一个重要且迅速增长的问题。解决方法：Venebio阿片类药物顾问（VOA）是一种基于VG现有的、正在申请专利的风险指数算法的临床决策支持系统（CDSS），该算法通过利用从患者电子病历（EMR）中收集的循证临床数据准确识别存在过量或严重阿片类药物诱导的呼吸抑制（OIRD）风险的个体。VOA将通过嵌入EMR系统的独立计算机应用程序提供，或者位于可通过安全互联网连接访问的远程服务器上。VOA将从EMR中自动提取患者的相关临床数据，评估患者的阿片类药物过量风险，并将患者的风险评分直接呈现给医疗保健提供者-从而实现基于证据的指导和教育，并根据患者的具体风险因素进行个性化。识别个体经历处方阿片类药物相关毒性或阿片类药物过量风险升高的能力将为医疗保健提供者和患者提供对个体风险水平的认识。研究方法：我们提出的II期研究的总体目标是首先完善和验证用于创建现有Venebio阿片类药物Advisor算法的临床内容，然后将这些完善的信息与额外的循证指南和教育内容沿着纳入临床决策支持系统，最后，在真实世界临床疼痛管理环境中对VOA进行前瞻性试点研究期间验证该CDSS。