Suppr超能文献

评估 Smart About Meds(SAM)移动应用在出院患者中的有效性:一项随机对照试验方案。

Evaluating the effectiveness of the Smart About Meds (SAM) mobile application among patients discharged from hospital: protocol of a randomised controlled trial.

机构信息

Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

Department of Medicine, McGill University, Montreal, Quebec, Canada.

出版信息

BMJ Open. 2024 Nov 24;14(11):e084492. doi: 10.1136/bmjopen-2024-084492.

Abstract

INTRODUCTION

Almost half of patients discharged from hospital are readmitted or return to the emergency department (ED) within 90 days. Non-adherence to medication changes made during hospitalisation and the use of potentially inappropriate medications (PIMs) both contribute to postdischarge adverse events. We developed Smart About Meds (SAM), a patient-centred mobile application that targets medication non-adherence and PIMs use. This protocol describes a randomised controlled trial (RCT) to evaluate SAM.

METHODS AND ANALYSIS

A pragmatic, stratified RCT will evaluate SAM among 3250 adult patients discharged from hospital. At discharge, consenting participants will be randomised 1:1 to usual care or SAM. SAM integrates novel patient-centred features with pharmacist monitoring to manage non-adherence to new medication regimens. SAM also notifies patients of PIMs in their regimen, with advice to discuss with their physician.Following discharge, patients will be followed for 90 days to measure the primary composite outcome of ED visits, hospital readmissions and death. Secondary outcomes will include primary adherence to medication changes, secondary adherence to disease-modifying medications, patient empowerment and health-related quality of life.The primary outcome will be analysed according to intention-to-treat. Multivariable logistic regression will estimate differences between treatment groups in the proportion of patients experiencing the primary outcome and will assess modification of intervention effects by hospital, unit, age, sex and comorbidity burden. With a sample size of 3250, the study will have 80% power to detect a 5% absolute reduction in the primary outcome. Binary and continuous secondary outcomes will be assessed using multivariable logistic and linear regression, respectively.

ETHICS AND DISSEMINATION

The Research Ethics Board of the McGill University Health Centre in Montréal, Canada has approved this study. Results will be submitted for publication in a peer-reviewed journal and presented at scientific conferences. If effective, SAM will be made available in app stores.

TRIAL REGISTRATION NUMBER

NCT05371548.

摘要

简介

几乎有一半的出院患者在 90 天内再次入院或返回急诊科(ED)。在出院后,不遵守住院期间的药物调整以及使用潜在不适当的药物(PIMs)都会导致出院后不良事件的发生。我们开发了 Smart About Meds(SAM),这是一款以患者为中心的移动应用程序,旨在解决药物不依从和 PIM 使用的问题。本方案描述了一项随机对照试验(RCT),以评估 SAM。

方法与分析

一项实用的、分层的 RCT 将评估 3250 名从医院出院的成年患者对 SAM 的使用情况。在出院时,同意参与的患者将按照 1:1 的比例随机分配到常规护理或 SAM 组。SAM 将整合新颖的以患者为中心的功能与药剂师监测相结合,以管理新药物治疗方案的不依从性。SAM 还会通知患者其治疗方案中存在 PIM,并建议与医生讨论。出院后,将对患者进行 90 天的随访,以测量 ED 就诊、再次住院和死亡的主要复合结局。次要结局将包括对药物变化的主要依从性、对疾病改善药物的次要依从性、患者赋权和健康相关生活质量。主要结局将根据意向治疗进行分析。多变量逻辑回归将估计治疗组在出现主要结局的患者比例方面的差异,并评估干预效果在医院、科室、年龄、性别和合并症负担方面的变化。在样本量为 3250 的情况下,该研究将有 80%的效力检测出主要结局绝对减少 5%。二项和连续的次要结局将分别使用多变量逻辑回归和线性回归进行评估。

伦理与传播

加拿大蒙特利尔麦吉尔大学健康中心的伦理审查委员会已批准该研究。研究结果将提交给同行评议的期刊发表,并在科学会议上报告。如果有效,SAM 将在应用商店中提供。

试验注册号

NCT05371548。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b6b/11590805/26c8dc9b83dd/bmjopen-14-11-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验