预防老年人跌倒相关药物事件的临床决策支持系统和患者门户的效果：一项具有嵌入式过程和经济评估的群组随机对照试验方案（ADFICE_IT）。

Effects of a clinical decision support system and patient portal for preventing medication-related falls in older fallers: Protocol of a cluster randomized controlled trial with embedded process and economic evaluations (ADFICE_IT).

机构信息

Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

Amsterdam UMC Location University of Amsterdam, Internal Medicine, Section of Geriatric Medicine, Amsterdam, Netherlands.

出版信息

PLoS One. 2023 Sep 26;18(9):e0289385. doi: 10.1371/journal.pone.0289385. eCollection 2023.

DOI:10.1371/journal.pone.0289385

PMID:37751429

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10522018/

Abstract

BACKGROUND

Falls are the leading cause of injury-related mortality and hospitalization among adults aged ≥ 65 years. An important modifiable fall-risk factor is use of fall-risk increasing drugs (FRIDs). However, deprescribing is not always attempted or performed successfully. The ADFICE_IT trial evaluates the combined use of a clinical decision support system (CDSS) and a patient portal for optimizing the deprescribing of FRIDs in older fallers. The intervention aims to optimize and enhance shared decision making (SDM) and consequently prevent injurious falls and reduce healthcare-related costs.

METHODS

A multicenter, cluster-randomized controlled trial with process evaluation will be conducted among hospitals in the Netherlands. We aim to include 856 individuals aged ≥ 65 years that visit the falls clinic due to a fall. The intervention comprises the combined use of a CDSS and a patient portal. The CDSS provides guideline-based advice with regard to deprescribing and an individual fall-risk estimation, as calculated by an embedded prediction model. The patient portal provides educational information and a summary of the patient's consultation. Hospitals in the control arm will provide care-as-usual. Fall-calendars will be used for measuring the time to first injurious fall (primary outcome) and secondary fall outcomes during one year. Other measurements will be conducted at baseline, 3, 6, and 12 months and include quality of life, cost-effectiveness, feasibility, and shared decision-making measures. Data will be analyzed according to the intention-to-treat principle. Difference in time to injurious fall between the intervention and control group will be analyzed using multilevel Cox regression.

DISCUSSION

The findings of this study will add valuable insights about how digital health informatics tools that target physicians and older adults can optimize deprescribing and support SDM. We expect the CDSS and patient portal to aid in deprescribing of FRIDs, resulting in a reduction in falls and related injuries.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05449470 (7-7-2022).

摘要

背景

跌倒是 65 岁及以上成年人中与伤害相关的死亡和住院的主要原因。一个重要的可改变的跌倒风险因素是使用增加跌倒风险的药物 (FRIDs)。然而，减药并不总是被尝试或成功实施。ADFICE_IT 试验评估了临床决策支持系统 (CDSS) 和患者门户的联合使用，以优化老年跌倒者中 FRIDs 的减药。该干预旨在优化和增强共享决策 (SDM)，从而预防伤害性跌倒和降低医疗保健相关的成本。

方法

一项多中心、聚类随机对照试验，并进行过程评估，将在荷兰的医院中进行。我们旨在纳入 856 名因跌倒而就诊于跌倒诊所的 65 岁及以上的个体。该干预包括 CDSS 和患者门户的联合使用。CDSS 提供基于指南的减药建议和嵌入的预测模型计算的个体跌倒风险估计。患者门户提供教育信息和患者咨询的摘要。对照组的医院将提供常规护理。跌倒日历将用于在 1 年内测量首次伤害性跌倒的时间 (主要结局) 和次要跌倒结局。其他测量将在基线、3、6 和 12 个月进行，包括生活质量、成本效益、可行性和共享决策措施。数据将根据意向治疗原则进行分析。干预组和对照组之间伤害性跌倒的时间差异将使用多水平 Cox 回归进行分析。