通过自动短信程序确定出院后的需求:混合方法研究。

Aiden Ahn, Anna U Morgan, Robert E Burke, Katherine Honig, Judith A Long, Nancy McGlaughlin, Carlondra Jointer, David A Asch, Eric Bressman
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引用次数: 0

摘要

背景:短信已成为出院后吸引患者参与的一种流行策略。人们对患者如何使用这些程序以及通过这种方法满足了患者哪些类型的需求知之甚少:本研究的目的是描述在为期 30 天的自动短信计划中发现的出院后需求的类型和时间:该计划于 2021 年 1 月至 8 月在费城的一家初级保健诊所实施。在这项混合方法研究中,两名审查员对患者在该项目中表达的需求进行了定向内容分析,并根据众所周知的过渡性护理框架对其进行了分类。我们描述了需求类别的频率及其相对于出院的时间:共有 405 人报名参加,平均(标清)年龄为 62.7(16.2)岁,64.2% 为女性,47.4% 为黑人,49.9% 有医疗保险。在这些人群中,有 178 人(44.0%)在为期 30 天的计划中表达了至少一项需求。最常见的需求与症状(26.8%)、协调后续护理(20.4%)和药物问题(15.7%)有关。从出院到满足需求的平均(标清)天数为 10.8 天(7.9 天);不同需求类别的满足时间没有明显差异:结论:通过自动发短信程序确定的需求主要集中在与初级护理实践相关的三个领域,并在护理实践范围之内。该计划可作为医疗系统通过高效运营方式支持过渡的典范,分析结果可为今后此类计划的迭代提供参考。
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Postdischarge needs identified by an automated text messaging program: A mixed-methods study.

Background: Text messaging has emerged as a popular strategy to engage patients after hospital discharge. Little is known about how patients use these programs and what types of needs are addressed through this approach.

Objective: The goal of this study was to describe the types and timing of postdischarge needs identified during a 30-day automated texting program.

Methods: The program ran from January to August 2021 at a primary care practice in Philadelphia. In this mixed-methods study, two reviewers conducted a directed content analysis of patient needs expressed during the program, categorizing them along a well-known transitional care framework. We describe the frequency of need categories and their timing relative to discharge.

Results: A total of 405 individuals were enrolled; the mean (SD) age was 62.7 (16.2); 64.2% were female; 47.4% were Black; and 49.9% had Medicare insurance. Of this population, 178 (44.0%) expressed at least one need during the 30-day program. The most frequent needs addressed were related to symptoms (26.8%), coordinating follow-up care (20.4%), and medication issues (15.7%). The mean (SD) number of days from discharge to need was 10.8 (7.9); there were no significant differences in timing based on need category.

Conclusions: The needs identified via an automated texting program were concentrated in three areas relevant to primary care practice and within nursing scope of practice. This program can serve as a model for health systems looking to support transitions through an operationally efficient approach, and the findings of this analysis can inform future iterations of this type of program.

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