Evidence map›Paper›PMID 36595737›Full record

ArticleJMIR cancer2023

Telehealth Use Following COVID-19 Within Patient-Sharing Physician Networks at a Rural Comprehensive Cancer Center: Cross-sectional Analysis.

Liyang Yu, You-Chi Liu, Sarah L Cornelius, Bruno T Scodari, Gabriel A Brooks, Alistair James O'Malley, Tracy Onega, Erika L Moen

Open access · goldAbstract read
In one paragraph

Article in JMIR cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
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  7. Broadband Data Forensics: Spatiotemporal Variations of the Download/Upload Speed Metric Commonly Used to Evaluate Potential Telehealth Accessibility.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2024
    Article
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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

8 authors at 3 institutions in 1 country.

Liyang YuDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.ORCID https://orcid.org/0000-0001-6050-2190
You-Chi LiuQuantitative Social Sciences program, Dartmouth College, Hanover, NH, United States.ORCID https://orcid.org/0000-0001-9668-2242
Sarah L CorneliusDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.ORCID https://orcid.org/0000-0002-7722-7276
Bruno T ScodariDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.ORCID https://orcid.org/0000-0003-3198-0876
Gabriel A BrooksDepartment of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States.ORCID https://orcid.org/0000-0003-3984-9995
Alistair James O'MalleyThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, NH, United States.ORCID https://orcid.org/0000-0001-8389-6217
Tracy OnegaDepartment of Population Sciences, University of Utah, Salt Lake City, NH, United States.ORCID https://orcid.org/0000-0002-1633-3040
Erika L MoenDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.ORCID https://orcid.org/0000-0002-9800-8742
Dartmouth College · USDartmouth–Hitchcock Medical Center · USUniversity of Utah · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Improving cancer health equity by targeting physician networksR37CA263936 · NCI · DARTMOUTH COLLEGE · PI MOEN, ERIKA · 2021 to 2025
$2.3M
Access, Utilization and Outcomes of Cancer Services in the Era of TelemedicineR01CA267990 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Tracy Onega, Fahui Wang · 2022 to 2026
$1.8M
NCI NIH HHS P30 CA023108NCI NIH HHS R01 CA267990NCI NIH HHS R37 CA263936
6 · The paper itself

Abstract

backgroundIn response to the COVID-19 pandemic, cancer centers rapidly adopted telehealth to deliver care remotely. Telehealth will likely remain a model of care for years to come and may not only affect the way oncologists deliver care to their own patients but also the physicians with whom they share patients.

objectiveThis study aimed to examine oncologist characteristics associated with telehealth use and compare patient-sharing networks before and after the COVID-19 pandemic in a rural catchment area with a particular focus on the ties between physicians at the comprehensive cancer center and regional facilities.

methodsIn this retrospective observational study, we obtained deidentified electronic health record data for individuals diagnosed with breast, colorectal, or lung cancer at Dartmouth Health in New Hampshire from 2018-2020. Hierarchical logistic regression was used to identify physician factors associated with telehealth encounters post COVID-19. Patient-sharing networks for each cancer type before and post COVID-19 were characterized with global network measures. Exponential-family random graph models were performed to estimate homophily terms for the likelihood of ties existing between physicians colocated at the hub comprehensive cancer center.

resultsOf the 12,559 encounters between patients and oncologists post COVID-19, 1228 (9.8%) were via telehealth. Patient encounters with breast oncologists who practiced at the hub hospital were over twice as likely to occur via telehealth compared to encounters with oncologists who practiced in regional facilities (odds ratio 2.2, 95% CI 1.17-4.15; P=.01). Patient encounters with oncologists who practiced in multiple locations were less likely to occur via telehealth, and this association was statistically significant for lung cancer care (odds ratio 0.26, 95% CI 0.09-0.76; P=.01). We observed an increase in ties between oncologists at the hub hospital and oncologists at regional facilities in the lung cancer network post COVID-19 compared to before COVID-19 (93/318, 29.3%, vs 79/370, 21.6%, respectively), which was also reflected in the lower homophily coefficients post COVID-19 compared to before COVID-19 for physicians being colocated at the hub hospital (estimate: 1.92, 95% CI 1.46-2.51, vs 2.45, 95% CI 1.98-3.02). There were no significant differences observed in breast cancer or colorectal cancer networks.

conclusionsTelehealth use and associated changes to patient-sharing patterns associated with telehealth varied by cancer type, suggesting disparate approaches for integrating telehealth across clinical groups within this health system. The limited changes to the patient-sharing patterns between oncologists at the hub hospital and regional facilities suggest that telehealth was less likely to create new referral patterns between these types of facilities and rather replace care that would otherwise have been delivered in person. However, this study was limited to the 2 years immediately following the initial outbreak of COVID-19, and longer-term follow-up may uncover delayed effects that were not observed in this study period.

Indexed as

cancer careCOVID-19electronic health record datahealth systemnetwork analysisoncologistoncologypatient networkpatient-sharing networksrural cancer caretelehealthtelemedicine

Identifiers

PMID36595737
PMCPMC9848440
OpenAlexW4313451525

What OpenQuestion holds

Textmetadata
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.