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囊性纤维化个性化检测要点(CFPOPD):一个交互式网络应用程序。

Cystic Fibrosis Point of Personalized Detection (CFPOPD): An Interactive Web Application.

作者信息

Wolfe Christopher, Pestian Teresa, Gecili Emrah, Su Weiji, Keogh Ruth H, Pestian John P, Seid Michael, Diggle Peter J, Ziady Assem, Clancy John Paul, Grossoehme Daniel H, Szczesniak Rhonda D, Brokamp Cole

机构信息

Division of Biostatistics & Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.

Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, United States.

出版信息

JMIR Med Inform. 2020 Dec 16;8(12):e23530. doi: 10.2196/23530.

Abstract

BACKGROUND

Despite steady gains in life expectancy, individuals with cystic fibrosis (CF) lung disease still experience rapid pulmonary decline throughout their clinical course, which can ultimately end in respiratory failure. Point-of-care tools for accurate and timely information regarding the risk of rapid decline is essential for clinical decision support.

OBJECTIVE

This study aims to translate a novel algorithm for earlier, more accurate prediction of rapid lung function decline in patients with CF into an interactive web-based application that can be integrated within electronic health record systems, via collaborative development with clinicians.

METHODS

Longitudinal clinical history, lung function measurements, and time-invariant characteristics were obtained for 30,879 patients with CF who were followed in the US Cystic Fibrosis Foundation Patient Registry (2003-2015). We iteratively developed the application using the R Shiny framework and by conducting a qualitative study with care provider focus groups (N=17).

RESULTS

A clinical conceptual model and 4 themes were identified through coded feedback from application users: (1) ambiguity in rapid decline, (2) clinical utility, (3) clinical significance, and (4) specific suggested revisions. These themes were used to revise our application to the currently released version, available online for exploration. This study has advanced the application's potential prognostic utility for monitoring individuals with CF lung disease. Further application development will incorporate additional clinical characteristics requested by the users and also a more modular layout that can be useful for care provider and family interactions.

CONCLUSIONS

Our framework for creating an interactive and visual analytics platform enables generalized development of applications to synthesize, model, and translate electronic health data, thereby enhancing clinical decision support and improving care and health outcomes for chronic diseases and disorders. A prospective implementation study is necessary to evaluate this tool's effectiveness regarding increased communication, enhanced shared decision-making, and improved clinical outcomes for patients with CF.

摘要

背景

尽管预期寿命稳步提高,但患有囊性纤维化(CF)肺病的个体在整个临床过程中仍会经历肺部功能的快速衰退,最终可能导致呼吸衰竭。用于准确及时提供有关快速衰退风险信息的床旁工具对于临床决策支持至关重要。

目的

本研究旨在通过与临床医生合作开发,将一种用于更早、更准确预测CF患者肺功能快速衰退的新算法转化为一个可集成到电子健康记录系统中的基于网络的交互式应用程序。

方法

从美国囊性纤维化基金会患者登记处(2003 - 2015年)随访的30879例CF患者中获取纵向临床病史、肺功能测量数据和时间不变特征。我们使用R Shiny框架并通过对医疗服务提供者焦点小组(N = 17)进行定性研究来迭代开发该应用程序。

结果

通过应用程序用户的编码反馈确定了一个临床概念模型和4个主题:(1)快速衰退的模糊性,(2)临床实用性,(3)临床意义,以及(4)具体的建议修订。这些主题被用于将我们的应用程序修订为当前发布的版本,可在线进行探索。本研究提高了该应用程序在监测CF肺病患者方面的潜在预后效用。进一步的应用程序开发将纳入用户要求的其他临床特征,以及更模块化的布局,这对医疗服务提供者和家庭互动可能会有用。

结论

我们创建交互式视觉分析平台的框架能够实现应用程序的通用开发,以综合、建模和转换电子健康数据,从而增强临床决策支持并改善慢性病和疾病的护理及健康结果。有必要进行一项前瞻性实施研究,以评估该工具在增加沟通、加强共同决策以及改善CF患者临床结果方面的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efa8/7773511/bde0504404dd/medinform_v8i12e23530_fig1.jpg

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