Suppr超能文献

使用带有支持中心的移动应用程序对慢性疼痛患者进行随访:单中心前瞻性研究。

Following Up Patients With Chronic Pain Using a Mobile App With a Support Center: Unicenter Prospective Study.

作者信息

Gómez-González Marta Antonia, Cordero Tous Nicolas, De la Cruz Sabido Javier, Sánchez Corral Carlos, Lechuga Carrasco Beatriz, López-Vicente Marta, Olivares Granados Gonzalo

机构信息

Department of Neurosurgery, Hospital Universitario Virgen de las Nieves, Av. Juan Pablo II s/n, Granada, 18013, Spain, 34 699699250.

Department of Human Anatomy, University of Granada, Granada, Spain.

出版信息

JMIR Hum Factors. 2025 Jan 22;12:e60160. doi: 10.2196/60160.

Abstract

BACKGROUND

Chronic pain is among the most common conditions worldwide and requires a multidisciplinary treatment approach. Spinal cord stimulation is a possible treatment option for pain management; however, patients undergoing this intervention require close follow-up, which is not always feasible. eHealth apps offer opportunities for improved patient follow-up, although adherence to these apps tends to decrease over time, with rates dropping to approximately 60%. To improve adherence to remote follow-up, we developed a remote follow-up system consisting of a mobile app for patients, a website for health care professionals, and a remote support center.

OBJECTIVE

Our objective was to evaluate patient adherence to remote follow-up using a system that includes a mobile app and a remote support center.

METHODS

After review of the literature and approval of the design of the follow-up system by a multidisciplinary committee, a team of experts developed a system based on a mobile app, a website for health care professionals, and a remote support center. The system was developed in collaboration with health care professionals and uses validated scales to capture patients' clinical data at each stage of treatment (ie, pretreatment phase, trial phase, and implantation phase). Data were collected prospectively between January 2020 to August 2023, including the number of total surveys sent, surveys completed, SMS text message reminders sent, and reminder calls made.

RESULTS

A total of 64 patients were included (n=40 women, 62.5%) in the study. By the end of the study, 19 (29.7%) patients remained in the pretreatment phase, 8 (12.5%) patients had completed the trial phase, and 37 (57.8%) reached the implantation phase. The mean follow-up period was 15.30 (SD 9.43) months. A total of 1574 surveys were sent, along with 488 SMS text message reminders and 53 reminder calls. The mean adherence rate decreased from 94.53% (SD 20.63%) during the pretreatment phase to 65.68% (SD 23.49%) in the implantation phase, with an overall mean adherence rate of 87.37% (SD 15.37%) for the app. ANOVA showed that adherence was significantly higher in the earlier phases of treatment (P<.001).

CONCLUSIONS

Our remote follow-up system, supported by a remote support center improves adherence to follow-up in later phases of treatment, although adherence decreased over time. Further studies are needed to investigate the relationship between adherence to the app and pain management.

摘要

背景

慢性疼痛是全球最常见的病症之一,需要多学科治疗方法。脊髓刺激是疼痛管理的一种可能治疗选择;然而,接受这种干预的患者需要密切随访,但这并不总是可行的。电子健康应用程序为改善患者随访提供了机会,尽管对这些应用程序的依从性往往会随着时间的推移而下降,降至约60%。为了提高对远程随访的依从性,我们开发了一个远程随访系统,该系统包括一个供患者使用的移动应用程序、一个供医疗保健专业人员使用的网站和一个远程支持中心。

目的

我们的目的是评估患者对使用包括移动应用程序和远程支持中心的系统进行远程随访的依从性。

方法

在查阅文献并经多学科委员会批准随访系统设计后,一个专家团队开发了一个基于移动应用程序、供医疗保健专业人员使用的网站和远程支持中心的系统。该系统是与医疗保健专业人员合作开发的,并使用经过验证的量表在治疗的每个阶段(即治疗前阶段、试验阶段和植入阶段)收集患者的临床数据。在2020年1月至2023年8月期间前瞻性收集数据,包括发送的总调查问卷数量、完成的调查问卷数量、发送的短信提醒数量和拨打的提醒电话数量。

结果

共有64名患者纳入研究(n = 40名女性,占62.5%)。到研究结束时,19名(29.7%)患者仍处于治疗前阶段,8名(12.5%)患者完成了试验阶段,37名(57.8%)患者进入了植入阶段。平均随访期为15.30(标准差9.43)个月。共发送了1574份调查问卷,以及488条短信提醒和53次提醒电话。平均依从率从治疗前阶段的94.53%(标准差20.63%)降至植入阶段的65.68%(标准差23.49%),该应用程序的总体平均依从率为87.37%(标准差15.37%)。方差分析显示,治疗早期阶段的依从性显著更高(P <.001)。

结论

我们的远程随访系统在远程支持中心的支持下提高了治疗后期阶段的随访依从性,尽管依从性随着时间的推移而下降。需要进一步研究来调查对应用程序的依从性与疼痛管理之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9243/11776344/9f7efeb6e01d/humanfactors-v12-e60160-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验