Evidence map›Paper›PMID 34236993›Full record

Observational studyJournal of medical Internet research2021

Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study.

Birju Patel, Stacie Vilendrer, Samantha M R Kling, Ian Brown, Ryan Ribeira, Matthew Eisenberg, Christopher Sharp

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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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

7 authors at 1 institution in 1 country.

Birju PatelDepartment of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States.ORCID 0000-0001-7673-6143
Stacie VilendrerEvaluation Sciences Unit, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0003-2317-5973
Samantha M R KlingEvaluation Sciences Unit, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0001-9169-763X
Ian BrownDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0003-0656-2621
Ryan RibeiraDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0002-4782-2410
Matthew EisenbergDepartment of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States.ORCID 0000-0003-3970-1886
Christopher SharpDepartment of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States.ORCID 0000-0001-7169-6904
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown.

objectiveThis study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.

methodsA pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.

resultsThere were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P<.001 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, P<.001 for change in daily average).

conclusionsTelemedicine was rapidly adopted with the intent of minimizing pathogen exposure to health care workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline health care clinicians.

Indexed as

TelemedicineWorkflowCOVID-19Cross InfectionEmergency Service, HospitalHealth PersonnelHumansPandemicsSARS-CoV-2Time FactorsCOVID-19delivery of health careemergency departmentimpactinfectious diseaseobservationalreal timereal-time locating systemrisktelehealthtelemedicinetransmissionwearablewearable electronic devices

Identifiers

PMID34236993
PMCPMC8315159
OpenAlexW3167604438

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.