Evidence map›Paper›PMID 34098882›Full record

ArticleBMC infectious diseases2021

Web-based, rapid and contactless management of ambulatory patients for SARS-CoV-2-testing.

Jannik Stemler, Oliver A Cornely, Torsten Noack-Schönborn, Corinna Fohrholz, Sofie Schumacher, Leonard Poluschkin, Bernd Binder, Clara Lehmann, Georg Langebartels

Abstract read
In one paragraph

Article in BMC infectious diseases, 2021. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

9 authors.

Jannik StemlerDepartment I of Internal Medicine, Excellence Centre for Medical Mycology (ECMM), University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.ORCID https://orcid.org/0000-0001-9152-2469
Oliver A CornelyDepartment I of Internal Medicine, Excellence Centre for Medical Mycology (ECMM), University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.ORCID https://orcid.org/0000-0001-9599-3137
Torsten Noack-SchönbornDepartment for Clinical affairs and Crisis management, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.
Corinna FohrholzHealex GmbH, Sophienstraße 5, 51149, Cologne, Germany.
Sofie SchumacherDepartment I of Internal Medicine, Excellence Centre for Medical Mycology (ECMM), University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.ORCID https://orcid.org/0000-0002-8805-1421
Leonard PoluschkinDepartment of Otorhinolaryngology, Head and Neck Surgery, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.ORCID https://orcid.org/0000-0002-2727-2765
Bernd BinderInformation Technology uk-it, Medical Applications, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.
Clara LehmannDepartment I of Internal Medicine, Excellence Centre for Medical Mycology (ECMM), University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany.
Georg LangebartelsDepartment for Clinical affairs and Crisis management, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50973, Cologne, Germany. georg.langebartels@uk-koeln.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the SARS-CoV-2 pandemic a mass casualty incident of ambulatory patients occurred at the COVID-19 rapid response infrastructure (CRRI) facility at the University Hospital of Cologne (UHC). We report the development of a patient-centred mobile-device solution to support efficient management of the facility, triage of patients and rapid delivery of test results.

methodsThe UHC-Corona Web Tool (CWT) was developed as a web-based software useable on each patient's smartphone. It provides, among others, a self-reported medical history including type and duration of symptoms and potential risk contacts and links all retrieved information to the digital patient chart via a QR code. It provides scheduling of outpatient appointments and automated transmission of SARS-CoV-2 test results.

resultsThe UHC-CWT was launched on 9 April 2020. It was used by 28,652 patients until 31 August 2020. Of those, 15,245 (53,2%) consulted the CRRI, representing 43,1% of all CRRI patients during the observed period. There were 8304 (29,0%) specifications concerning travel history and 17,145 (59,8%) indications of ≥1 symptom of SARS-CoV-2 infection. The most frequently indicated symptoms were sore throat (60,0%), headache (50,7%), common cold (45,1%) and cough (42,6%) while 11,057 (40,2%) patients did not report any symptoms. After implementation of the UHC-CWT, the amount of patient contacts per physician rose from 38 to 98,7 per day. The personnel for communication of test results were reduced from four on seven days to one on five days.

conclusionThe UHC-CWT is an effective digital solution for management of large numbers of outpatients for SARS-CoV-2 testing.

Indexed as

InternetAmbulatory Care FacilitiesCOVID-19COVID-19 TestingElectronic Health RecordsGermanyHospitals, UniversityHumansMaleMedical History TakingPandemicsSmartphoneSurveys and QuestionnairesTravelTriageCOVID-19 pandemicDigital medicineSARS-CoV-2 testing strategyWeb-based patient management

Identifiers

PMID34098882
PMCPMC8182346

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.