Evidence map›Paper›PMID 39386066›Full record

ArticleJAMIA open2024

Patterns of healthcare utilization according to health equity determinants during the first year of the pandemic at Johns Hopkins Medicine.

Kai-Wen K Yang, Ilia Rattsev, Zoljargal Lkhagvajav, Natalie Flaks-Manov, Kevin Gorman, Jeremy Aaron Epstein, Ciprian M Crainiceanu, Casey O Taylor

Abstract read
In one paragraph

Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Kai-Wen K YangJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.
Ilia RattsevJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.
Zoljargal LkhagvajavJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.
Natalie Flaks-ManovJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.
Kevin GormanJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.
Jeremy Aaron EpsteinDivision of Hospital Medicine, Johns Hopkins Hospital, Baltimore, MD 21224, United States.
Ciprian M CrainiceanuDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, United States.
Casey O TaylorJohns Hopkins Whiting School of Engineering, Institute for Computational Medicine, Baltimore, MD 21218, United States.ORCID https://orcid.org/0000-0001-9302-5968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Rapid telehealth adoption happened at the onset of the coronavirus disease 2019 (COVID-19) pandemic, resulting in a move from Materials and Methods: This was an observational cohort study of Johns Hopkins Medicine (JHM) patients. We analyzed utilization of video, telephone, and in-person patient-provider visits by eligible patients between March 16, 2019 and December 31, 2020. Percent changes in average weekly patient-provider visits from Results: There was a 39% drop in patient-provider visits from the pre-pandemic to the early 2020 pandemic period, and a 24% drop from pre-pandemic to the late 2020 pandemic period. We discovered 21 groups according to health equity determinates and visit departments with patterns of disproportionately smaller or greater drops in visits during the first year of the pandemic, when compared to the total population: Discussion: Our study provides evidence of health equity determinant groups having disproportionally smaller or greater drops in visits during the first year of the pandemic. The observed differences may have been influenced by changing telehealth offerings during the first year of the pandemic. Groups with disproportionately smaller drops in visits early 2020 ( Conclusion: We describe 4 main patterns to characterize groups with disproportionately smaller or greater drops in visits during the first year of the pandemic. While this work did not specifically study vulnerable populations, these patterns set the stage for further studies of such groups.

Indexed as

COVID-19health equitypatient acceptance of health caresocial determinants of healthtelemedicine

Identifiers

PMID39386066
PMCPMC11458551

What OpenQuestion holds

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LicenceCC BY
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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.