MétaCan
Menu
Back to cohort
Record W4386751307 · doi:10.2196/45518

Telehealth Availability for Cancer Care During the COVID-19 Pandemic: Cross-Sectional Study

2023· article· en· W4386751307 on OpenAlexvenueno aff
Victoria A. Marks, Walter Hsiang, James Nie, Waez Umer, Afash Haleem, Bayan Galal, Irene Pak, Dana Kim, Michelle C. Salazar, Haddon Pantel, Elizabeth R. Berger, Daniel J. Boffa, Jaime A. Cavallo, Michael Leapman

Bibliographic record

VenueJMIR Cancer · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsTelehealthCoronavirus disease 2019 (COVID-19)PandemicCross-sectional study2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineTelemedicineHealth careVirologyPolitical scienceOutbreakDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Telehealth was an important strategy for maintaining continuity of cancer care during the coronavirus pandemic and has continued to play a role in outpatient care; however, it is unknown whether services are equally available across cancer hospitals. OBJECTIVE: This study aimed to assess telehealth availability at cancer hospitals for new and established patients with common cancers to contextualize the impact of access barriers to technology on overall access to health care. METHODS: We conducted a national cross-sectional secret shopper study from June to November 2020 to assess telehealth availability at cancer hospitals for new and established patients with colorectal, breast, and skin (melanoma) cancer. We examined facility-level factors to determine predictors of telehealth availability. RESULTS: Of the 312 investigated facilities, 97.1% (n=303) provided telehealth services for at least 1 cancer site. Telehealth was less available to new compared to established patients (n=226, 72% vs n=301, 97.1%). The surveyed cancer hospitals more commonly offered telehealth visits for breast cancer care (n=266, 85%) and provided lower access to telehealth for skin (melanoma) cancer care (n=231, 74%). Most hospitals (n=163, 52%) offered telehealth for all 3 cancer types. Telehealth availability was weakly correlated across cancer types within a given facility for new (r=0.16, 95% CI 0.09-0.23) and established (r=0.14, 95% CI 0.08-0.21) patients. Telehealth was more commonly available for new patients at National Cancer Institute-designated facilities, medical school-affiliated facilities, and major teaching sites, with high total admissions and below-average timeliness of care. Telehealth availability for established patients was highest at Academic Comprehensive Cancer Programs, nongovernment and nonprofit facilities, medical school-affiliated facilities, Accountable Care Organizations, and facilities with a high number of total admissions. CONCLUSIONS: Despite an increase in telehealth services for patients with cancer during the COVID-19 pandemic, we identified differences in access across cancer hospitals, which may relate to measures of clinical volume, affiliation, and infrastructure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.142
GPT teacher head0.508
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJMIR CancerSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207