Evidence map›Paper›PMID 33294596›Full record

ArticleJournal of patient experience2020

Evaluating the Telehealth Experience of Patients With COVID-19 Symptoms: Recommendations on Best Practices.

Saif Khairat, Malvika Pillai, Barbara Edson, Robert Gianforcaro

Abstract read
In one paragraph

Article in Journal of patient experience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Factors Affecting Family Caregivers' Satisfaction During Virtual Care Visits.Studies in health technology and informatics · 2024
    Article
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  6. 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

4 authors.

Saif KhairatCarolina Health Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-8992-2946
Malvika PillaiCarolina Health Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Barbara EdsonUNC Health, Chapel Hill, NC, USA.
Robert GianforcaroUNC Health, Chapel Hill, NC, USA.

Funding

An Interdisciplinary Program for Advanced Training in Health Data AnalyticsT15LM012500 · NLM · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MOSTAFA, JAVED · 2017 to 2021
$2.9M
NLM NIH HHS T15 LM012500
6 · The paper itself

Abstract

Positive patient experiences are associated with illness recovery and adherence to medication. To evaluate the virtual care experience for patients with COVID-19 symptoms as their chief complaints. We conducted a cross-sectional study of the first cohort of patients with COVID-19 symptoms in a virtual clinic. The main end points of this study were visit volume, wait times, visit duration, patient diagnosis, prescriptions received, and satisfaction. Of the 1139 total virtual visits, 212 (24.6%) patients had COVID-19 symptoms. The average wait time (SD) for all visits was 75.5 (121.6) minutes. The average visit duration for visits was 10.5 (4.9) minutes. The highest volume of virtual visits was on Saturdays (39), and the lowest volume was on Friday (19). Patients experienced shorter wait times (SD) on the weekdays 67.1 (106.8) minutes compared to 90.3 (142.6) minutes on the weekends. The most common diagnoses for patients with COVID-19 symptoms were upper respiratory infection. Patient wait times for a telehealth visit varied depending on the time and day of appointment. Long wait times were a major drawback in the patient experience. Based on patient-reported experience, we proposed a list of general, provider, and patient telehealth best practices.

Indexed as

patient experiencerecommendationstelehealthvirtual visits

Identifiers

PMID33294596
PMCPMC7705823

What OpenQuestion holds

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LicenceCC BY-NC
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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.