Evidence map›Paper›PMID 34969330›Full record

ArticleAnnals of medicine2022

Transition to telemedicine and its impact on missed appointments in community-based clinics.

Omolola E Adepoju, Minji Chae, Winston Liaw, Tracy Angelocci, Paul Millard, Omar Matuk-Villazon

Open access · goldAbstract read
In one paragraph

Article in Annals of medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
13.4field-weighted citation impact, top 1% 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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 76 citations in OpenAlex.

  1. Pooled it
  2. Telemedicine Implementation for Safety Net Populations: A Systematic Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2024
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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

6 authors at 5 institutions in 2 countries.

Omolola E AdepojuDepartment of Health Systems and Population Health Sciences, College of Medicine, University of Houston, Houston, TX, USA.
Minji ChaeHumana Integrated Health System Sciences Institute, University of Houston, Houston, TX, USA.
Winston LiawDepartment of Health Systems and Population Health Sciences, College of Medicine, University of Houston, Houston, TX, USA.
Tracy AngelocciLone Star Circle of Care, Georgetown, TX, USA.
Paul MillardLone Star Circle of Care, Georgetown, TX, USA.
Omar Matuk-VillazonDepartment of Health Systems and Population Health Sciences, College of Medicine, University of Houston, Houston, TX, USA.
The University of Texas Health Science Center at Houston · USCircle of Care · AULone Star College · USUniversity of Houston · USUniversity of Houston System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe Coronavirus Aid, Relief, and Economic Security Act led to the rapid implementation of telemedicine across health care office settings. Whether this transition to telemedicine has any impact on missed appointments is yet to be determined. This study examined the relationship between telemedicine usage and missed appointments during the COVID-19 pandemic.

methodThis retrospective study used appointment-level data from 55 Federally Qualified Health Centre clinics in Texas between March and November 2020. To account for the nested data structure of repeated appointments within each patient, a mixed-effects multivariable logistic regression model was used to examine associations between telemedicine use and missed appointments, adjusting for patient sociodemographic characteristics, geographic classification, past medical history, and clinic characteristics. The independent variable was having a telemedicine appointment, defined as an audiovisual consultation started and finalized via a telemedicine platform. The outcome of interest was having a missed appointment (yes/no) after a scheduled and confirmed medical appointment. Results from this initial model were stratified by appointment type (in-person vs. telemedicine).

resultsThe analytic sample included 278,171 appointments for 85,413 unique patients. The overall missed appointment rate was 18%, and 25% of all appointments were telemedicine appointments. Compared to in-person visits, telemedicine visits were less likely to result in a missed appointment (OR = 0.87,

conclusionsTelemedicine is strongly associated with fewer missed appointments. Although our findings suggest a residual lag in minority populations, specific patient populations, including those with frequent prior visits or chronic conditions, those seeking mental health services, and those living in metropolitan areas were less likely to miss telemedicine appointments than in-person visits. These findings highlight how telemedicine can enable effective and accessible care by reducing missed healthcare appointments.KEY MESSAGESTelemedicine was associated with 13% lower odds of missed appointments.Patients with frequent medical visits or those living with chronic diseases were less likely to miss telemedicine appointments but more likely to miss in-person appointments.Patients seeking mental health services were less likely to miss telemedicine appointments but more likely to miss in-person appointments.Similarly, those living in metropolitan areas were less likely to miss telemedicine appointments but more likely to miss in-person appointments.

Indexed as

Appointments and SchedulesCommunity Health CentersCOVID-19PandemicsTelemedicineHumansRetrospective Studiesaccess to health careCOVID-19federally qualified health centresmissed appointmentspatient no-showstelemedicine

Identifiers

PMID34969330
PMCPMC8725902
OpenAlexW4205358211

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.