Evidence map›Paper›PMID 32619595›Full record

ArticleUrology2020

Video Visits as a Substitute for Urological Clinic Visits.

Juan J Andino, Mark-Anthony Lingaya, Stephanie Daignault-Newton, Parth K Shah, Chad Ellimoottil

Abstract read
In one paragraph

Article in Urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Juan J AndinoDepartment of Urology, Michigan Medicine, Ann Arbor, MI. Electronic address: juanjose@med.umich.edu.
Mark-Anthony LingayaUniversity of Michigan Medical School, Ann Arbor, MI.
Stephanie Daignault-NewtonDepartment of Urology, Michigan Medicine, Ann Arbor, MI.
Parth K ShahDepartment of Urology, Michigan Medicine, Ann Arbor, MI.
Chad EllimoottilDepartment of Urology, Michigan Medicine, Ann Arbor, MI; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI.

Funding

AHRQ HHS K08 HS027632
6 · The paper itself

Abstract

objectiveTo evaluate whether video visits were being used as substitutes to clinic visits prior to COVID-19 at our institution's outpatient urology centers.

methodsWe reviewed 600 established patient video visits completed by 13 urology providers at a tertiary academic center in southeast Michigan. We compared these visits to a random, stratified sample of established patient clinic visits. We assessed baseline demographics and visit characteristics for both groups. We defined our primary outcome ("revisit rate") as the proportion of additional healthcare evaluation (ie, office, emergency room, hospitalization) by a urology provider within 30 days of the initial encounter.

resultsPatients seen by video visit tended to be younger (51 vs 61 years, P <.001), would have to travel further for a clinic appointment (82 vs 68 miles, P <.001), and were more likely to be female (36 vs 28%, P = .001). The most common diagnostic groups evaluated through video visits were nephrolithiasis (40%), oncology (18%) and andrology (14.3%). While the 30-day revisit rates were higher for clinic visits (4.3% vs 7.5%, P = .01) primarily due to previously scheduled appointments, revisits due to medical concerns were similar across both groups (0.5% vs 0.67%; P = .60).

conclusionsVideo visits can be used to deliver care across a broad range of urologic diagnoses and can serve as a substitute for clinic visits.

Indexed as

BetacoronavirusTelemedicineUrologyVideoconferencingAdultAmbulatory CareCoronavirus InfectionsCOVID-19FemaleHumansMaleMiddle AgedOffice VisitsPandemicsPneumonia, ViralRetrospective Studies

Identifiers

PMID32619595
PMCPMC7834609

What OpenQuestion holds

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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.