Evidence map›Paper›PMID 37773609›Full record

Observational studyJournal of medical Internet research2023

Identifying Inequities in Video and Audio Telehealth Services for Primary Care Encounters During COVID-19: Repeated Cross-Sectional, Observational Study.

Lorraine R Buis, Lindsay K Brown, Melissa A Plegue, Reema Kadri, Anna R Laurie, Timothy C Guetterman, V G Vinod Vydiswaran, Jiazhao Li, Tiffany C Veinot

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Lorraine R BuisDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-5855-9972
Lindsay K BrownSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-1671-4983
Melissa A PlegueDepartment of Pediatrics, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-6032-534X
Reema KadriDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-0935-3761
Anna R LaurieDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID 0009-0008-7501-6441
Timothy C GuettermanDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-0093-858X
V G Vinod VydiswaranSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-3122-1936
Jiazhao LiSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-8219-5638
Tiffany C VeinotSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-1200-9515
University of Michigan · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic resulted in rapid changes in how patient care was provided, particularly through the expansion of telehealth and audio-only phone-based care.

objectiveThe goal of this study was to evaluate inequities in video and audio-only care during various time points including the initial wave of the COVID-19 pandemic, later stages of the pandemic, and a historical control. We sought to understand the characteristics of care during this time for a variety of different groups of patients that may experience health care inequities.

methodsWe conducted a retrospective analysis of electronic health record (EHR) data from encounters from 34 family medicine and internal medicine primary care clinics in a large, Midwestern health system, using a repeated cross-sectional, observational study design. These data included patient demographic data, as well as encounter, diagnosis, and procedure records. Data were obtained for all in-person and telehealth encounters (including audio-only phone-based care) that occurred during 3 separate time periods: an initial COVID-19 period (T2: March 16, 2020, to May 3, 2020), a later COVID-19 period (T3: May 4, 2020, to September 30, 2020), and a historical control period from the previous year (T1: March 16, 2019, to September 30, 2019). Primary analysis focused on the status of each encounter in terms of whether it was completed as scheduled, it was canceled, or the patient missed the appointment. A secondary analysis was performed to evaluate the likelihood of an encounter being completed based on visit modality (phone, video, in-person).

resultsIn total, there were 938,040 scheduled encounters during the 3 time periods, with 178,747 unique patients, that were included for analysis. Patients with completed encounters were more likely to be younger than 65 years old (71.8%-74.1%), be female (58.8%-61.8%), be White (75.6%-76.7%), and have no significant comorbidities (63.2%-66.8%) or disabilities (53.2%-61.1%) in all time periods than those who had only canceled or missed encounters. Effects on different subpopulations are discussed herein.

conclusionsFindings from this study demonstrate that primary care utilization across delivery modalities (in person, video, and phone) was not equivalent across all groups before and during the COVID-19 pandemic and different groups were differentially impacted at different points. Understanding how different groups of patients responded to these rapid changes and how health care inequities may have been affected is an important step in better understanding implementation strategies for digital solutions in the future.

Indexed as

Health Services AccessibilityPrimary Health CareTelemedicineAgedCOVID-19Cross-Sectional StudiesDelivery of Health CareFemaleHumansPandemicsRetrospective Studiesclinical encountersCOVID-19electronic health recordshealth equitytelemedicine

Identifiers

PMID37773609
PMCPMC10544805
OpenAlexW4385639989

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.