What You Should Know:

您应该知道：

–              FeelBetter, the leading provider of polypharmacy patient management technology and pioneer of Pharmaco-Clinical Intelligence, today announced a collaboration on a prospective research study with investigators at Brigham and Women’s Hospital in Boston.

–FeelBetter是多种药物患者管理技术的领先提供商和药物临床情报的先驱，今天宣布与波士顿布里格姆妇女医院的研究人员合作进行一项前瞻性研究。

–              The research will assess the impact of FeelBetter’s AI-based Precision Population Health Platform on polypharmacy patient management.

–该研究将评估FeelBetter基于人工智能的精准人群健康平台对多种药物患者管理的影响。

Revolutionizing Polypharmacy Management: FeelBetter’s Innovative Approach

革新多种药物管理：FeelBetter的创新方法

Launched in February 2024, this collaborative study will prospectively monitor patients under care at the hospital’s Phyllis Jen Center for Primary Care, assessing FeelBetter’s potential to enhance health outcomes while reducing healthcare utilization and costs. Building upon retrospective research from Brigham and Women’s Hospital in 2022, which demonstrated FeelBetter’s ability to predict medication-related adverse events among senior patients and suggest necessary changes to their medication routines, this new investigation aims to further validate its effectiveness..

这项合作研究于2024年2月启动，将对医院Phyllis Jen初级保健中心接受护理的患者进行前瞻性监测，评估FeelBetter在提高健康状况的同时降低医疗利用率和成本的潜力。基于布里格姆妇女医院（Brigham and Women's Hospital）2022年的回顾性研究，该研究证明FeelBetter有能力预测老年患者的药物相关不良事件，并建议对其药物常规进行必要的改变，这项新调查旨在进一步验证其有效性。。

Presented at the Society of General Internal Medicine (SGIM) 2023 Annual Meeting and the 2023 Annual Research Meeting (ARM) of AcademyHealth, the previous research indicated FeelBetter’s capability to stratify the risk of emergency department visits and hospitalizations among patients with complex medication regimes and multiple chronic conditions.

在普通内科学会（SGIM）2023年年度会议和学术健康2023年年度研究会议（ARM）上发表的先前研究表明，FeelBetter有能力对复杂药物治疗方案和多种慢性病患者的急诊就诊和住院风险进行分层。

Moreover, when coupled with medication management interventions, FeelBetter exhibited potential in reducing healthcare expenses and improving patient outcomes..

此外，当与药物管理干预相结合时，FeelBetter在减少医疗费用和改善患者预后方面表现出潜力。。

As part of the pilot program, FeelBetter will integrate its platform with Epic’s EHR system, streamlining workflows and enabling automated processes. Powered by Pharmaco-Clinical Intelligence, a groundbreaking fusion of AI-based analyses and evidence-based pharmacology and clinical capabilities, FeelBetter identifies high-risk patients for near-term hospitalization due to polypharmacy issues.

作为试点项目的一部分，FeelBetter将其平台与Epic的EHR系统集成，简化工作流程并实现自动化流程。在药物临床情报的支持下，FeelBetter将基于AI的分析与循证药理学和临床能力进行了开创性的融合，确定了由于多种药物问题导致的短期住院高危患者。

By recommending changes to medication regimens and other necessary clinical interventions while monitoring progress comprehensively, FeelBetter transforms the approach to polypharmacy management at both individual and population health levels..

通过建议改变药物治疗方案和其他必要的临床干预措施，同时全面监测进展情况，FeelBetter将个人和人群健康水平的多种药物管理方法转变为。。

FeelBetter pioneers Pharmaco-Clinical Intelligence, revolutionizing polypharmacy management through a comprehensive solution designed to address the challenges of suboptimal medication management. Leveraging AI and machine learning, FeelBetter’s technology empowers healthcare professionals to ensure the safety, efficacy, and appropriateness of their patients’ medication regimens..

FeelBetter是药物临床智能的先驱，通过旨在解决次优药物管理挑战的综合解决方案，彻底改变了多种药物管理。利用人工智能和机器学习，FeelBetter的技术使医疗保健专业人员能够确保患者用药方案的安全性、有效性和适当性。。

“Many polypharmacy problems aren’t detected until patients end up in the ER and, in seniors with several chronic diseases and conditions, the simultaneous use of multiple medications ultimately contributes to 10-30% of hospitalizations,” said Lisa Rotenstein, MD MBA MSc, the principal investigator of the study.

该研究的首席研究员、医学博士MBA硕士丽莎·罗滕斯坦（LisaRotenstein）说：“许多多种药物问题直到患者最终进入急诊室才被发现，对于患有多种慢性疾病和病症的老年人来说，同时使用多种药物最终会导致10%至30%的住院率。”。

“Our previous study showed that its platform can be used to identify which patients are at the highest risk of polypharmacy-related adverse events. Based on retrospective data, we’re excited to prospectively examine how the platform can potentially be used to improve patient outcomes, healthcare utilization, and cost efficiencies.”.

“我们之前的研究表明，它的平台可用于确定哪些患者发生多种药物相关不良事件的风险最高。根据回顾性数据，我们很高兴能前瞻性地研究该平台如何潜在地用于改善患者预后，医疗保健利用率和成本效率。”。