Evidence map›Paper›PMID 34882572›Full record

ArticleJMIR public health and surveillance2022

An Evaluation of the Text Illness Monitoring (TIM) Platform for COVID-19: Cross-sectional Online Survey of Public Health Users.

Heather A Joseph, Susan Z Ingber, Chelsea Austin, Caroline Westnedge, F V Strona, Leslie Lee, Ami B Shah, Lauren Roper, Anita Patel

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Heather A Joseph *Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, Chamblee, GA, United States.ORCID 0000-0003-0470-6759
Susan Z IngberDivision of Viral Hepatitis, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0002-5290-8884
Chelsea AustinDepartment of Health Policy and Behavioral Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States.ORCID 0000-0001-7825-4551
Caroline WestnedgeFederal Civilian Division, General Dynamics Information Technology, Atlanta, GA, United States.ORCID 0000-0001-7972-0702
F V StronaDivision of STD Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0001-5614-9953
Leslie LeeOffice of the Director, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0002-0333-8838
Ami B ShahFederal Civilian Division, General Dynamics Information Technology, Atlanta, GA, United States.ORCID 0000-0003-3579-8609
Lauren RoperOffice of the Director, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0001-6504-9735
Anita PatelOffice of the Director, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.ORCID 0000-0002-1268-9402
Centers for Disease Control and Prevention · USGeneral Dynamics (United States) · USGeorgia State University · USNational Center for Environmental Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe US public health response to the COVID-19 pandemic has required contact tracing and symptom monitoring at an unprecedented scale. The US Centers for Disease Control and Prevention and several partners created the Text Illness Monitoring (TIM) platform in 2015 to assist US public health jurisdictions with symptom monitoring for potential novel influenza virus outbreaks. Since May 2020, 142 federal, state, and local public health agencies have deployed TIM for COVID-19 symptom monitoring.

objectiveThe aim of this study was to evaluate the utility, benefits, and challenges of TIM to help guide decision-making for improvements and expansion to support future public health emergency response efforts.

methodsWe conducted a brief online survey of previous and current TIM administrative users (admin users) from November 28 through December 21, 2020. Closed- and open-ended questions inquired about the onboarding process, decision to use TIM, groups monitored with TIM, comparison of TIM to other symptom monitoring systems, technical challenges and satisfaction with TIM, and user support. A total of 1479 admin users were invited to participate.

resultsA total of 97 admin users from 43 agencies responded to the survey. Most admin users represented the Indian Health Service (35/97, 36%), state health departments (26/97, 27%), and local or county health departments (18/97, 19%), and almost all were current users of TIM (85/94, 90%). Among the 43 agencies represented, 11 (26%) used TIM for monitoring staff exclusively, 13 (30%) monitored community members exclusively, and 19 (44%) monitored both staff and community members. Agencies most frequently used TIM to monitor symptom development in contacts of cases among community members (28/43, 65%), followed by symptom development among staff (27/43, 63%) and among staff contacts of cases (24/43, 56%). Agencies also reported using TIM to monitor patients with COVID-19 for the worsening of symptoms among staff (21/43, 49%) and community members (18/43, 42%). When asked to compare TIM to previous monitoring systems, 78% (40/51) of respondents rated TIM more favorably than their previous monitoring system, 20% (10/51) said there was no difference, and 2% (1/51) rated the previous monitoring system more favorably than TIM. Most respondents found TIM favorable in terms of time burden, staff burden, timeliness of the data, and the ability to monitor large population sizes. TIM compared negatively to other systems in terms of effort to enroll participants (ie, persons TIM monitors) and accuracy of the data. Most respondents (76/85, 89%) reported that they would highly or somewhat recommend TIM to others for symptom monitoring.

conclusionsThis evaluation of TIM showed that agencies used TIM for a variety of purposes and rated TIM favorably compared to previously used monitoring systems. We also identified opportunities to improve TIM; for example, enhancing the flexibility of alert deliveries would better meet admin users' varying needs. We also suggest continuous program evaluation practices to assess and respond to implementation gaps.

Indexed as

COVID-19Cross-Sectional StudiesHumansPandemicsPublic HealthSARS-CoV-2Surveys and Questionnairescontact tracingCOVID-19SMS text systemsymptom monitoring

Identifiers

PMID34882572
PMCPMC8823610
OpenAlexW4200401135

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.