Evidence map›Paper›PMID 39472836›Full record

ArticleBMC public health2024

An electronic patient-reported outcome symptom monitor: the Chinese experience with rapid development of a ready-to-go symptom monitor.

Jingyu Zhang, Qing Guo, Jiaojiao Chen, Yajie Liu, Dan Kang, Rumei Xiang, Jiaheng Shi, Jinliang Yang, Xiaojun Tang, Yuxian Nie and 5 more

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Jingyu ZhangState Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, No. 1, Medical College Road, Yuzhong District, Chongqing, 400016, China.
Qing GuoePRO Vision (Beijing) Health Technology Co., Ltd., Beijing, China.
Jiaojiao ChenSchool of Public Health, Chongqing Medical University, Chongqing, China.
Yajie LiuGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Dan KangSchool of Public Health, Chongqing Medical University, Chongqing, China.
Rumei XiangSchool of Public Health, Chongqing Medical University, Chongqing, China.
Jiaheng ShiGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Jinliang YangGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xiaojun TangSchool of Public Health, Chongqing Medical University, Chongqing, China.
Yuxian NieState Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, No. 1, Medical College Road, Yuzhong District, Chongqing, 400016, China.
Jingfu QiuSchool of Public Health, Chongqing Medical University, Chongqing, China.
Xu WangePRO Vision (Beijing) Health Technology Co., Ltd., Beijing, China.
Zhu YangDepartment of Gynecology and Obstetrics, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jie Liu *Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China. dr.liujie@163.com.
Qiuling Shi *State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, No. 1, Medical College Road, Yuzhong District, Chongqing, 400016, China. qshi@cqmu.edu.cn.

Funding

Fundamental Research Funds for the Central public welfare research institutes NO. ZZ15-WT-05Science and Technology Innovation Key R&D Program of Chongging No. CSTB2022TIAD-STX0013The Postdoctoral Fellowship Program of CPSF GZC20233357
6 · The paper itself

Abstract

backgroundMonitoring symptoms is crucial for the early detection of disease progression and timely intervention, which is essential for reducing severe cases and mortality rates in rapidly spreading pandemics, such as COVID-19. Therefore, during infectious disease pandemics, the rapid development of real-time symptom monitoring platforms is essential. This study aimed to explore the urgent development process of an electronic system for patient-reported outcome monitoring in emergency situations.

methodsThe development of the electronic patient-reported outcome COVID-19 symptom monitoring platform (ePRO-CoV-SM) included the following steps: (1) modifying an electronic patient-reported outcome symptom-reporting platform to assess patients with COVID-19 and validating its feasibility and sensitivity for longitudinal symptom measurement; (2) updating the system to accommodate the newly emerged severe acute respiratory syndrome coronavirus 2 BA.2.2 variant; and (3) applying it in real-world settings. Literature review, expert consultation, and subject-group discussions were used to develop symptom items. Response rate and missing item rate were used as validation indicators for ePRO-CoV-SM.

resultsThe ePRO-CoV-SM (2.0) consists of a core set of symptom items, a WeChat mini program, an online project design backend, a management and communication front, and a database. During the 2020 verification, the response rate of ePRO symptom monitoring reached 89.47% and the item missing rate was 0.33%, the monitoring revealed that a considerable number of asymptomatic patients were experiencing undesirable symptoms during the isolation period. In its real-world application in 2022, the response rate was 85.93% and the item missing rate was 4.84%, the monitoring found the symptom burden was higher in the younger group (18-40 years old) than in the older group (40-67 years old), and over 30% of patients reported symptoms such as cough (36.08%), dry mouth (35.67%), sleep disorders (32.27%), appetite loss (32.17%), and sputum (30.79%) during the isolation period.

conclusionsElectronic patient-reported outcome measurement was demonstrated to be sensitive and feasible for monitoring symptoms in patients with COVID-19. By integrating smartphone-based data collection with real-time online data transmission and secure data storage using Secure Sockets Layer encryption, an electronic platform for monitoring critical symptoms can be rapidly established in emergency situations.

Indexed as

COVID-19Patient Reported Outcome MeasuresAdolescentAdultChinaFemaleHumansMaleMiddle AgedSARS-CoV-2Symptom AssessmentCOVID-19Electronic Patient-Reported OutcomeElectronic platformSymptom

Identifiers

PMID39472836
PMCPMC11520658

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.