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Record W4288073185 · doi:10.2196/33768

Adoption of Telemedicine in a Rural US Cancer Center Amid the COVID-19 Pandemic: Qualitative Study

2022· article· en· W4288073185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Cancer · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of Health
KeywordsTelemedicineSpecialtyMedicinePandemicThematic analysisHealth careQualitative researchFamily medicineNursingOutpatient clinicMedical emergencyCoronavirus disease 2019 (COVID-19)Internal medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic necessitated a rapid shift to telemedicine to minimize patient and provider exposure risks. While telemedicine has been used in a variety of primary and specialty care settings for many years, it has been slow to be adopted in oncology care. Health care provider and administrator perspectives on factors affecting telemedicine use in oncology settings are not well understood, and the conditions associated with the COVID-19 pandemic offered the opportunity to study the adoption of telemedicine and the resulting provider and staff perspectives on its use. OBJECTIVE: The aim of this paper is to study the factors that influenced telemedicine uptake and sustained use in outpatient oncology clinics at a US cancer center to inform future telemedicine practices. METHODS: We used purposive sampling to recruit a mix of oncology specialty providers, practice managers, as well as nursing and administrative staff representing 5 outpatient oncology clinics affiliated with the Dartmouth Cancer Center, a large regional cancer center in the northeast of United States, to participate in semistructured interviews conducted over 6 weeks in spring 2021. The interview guide was informed by the 5 domains of the Consolidated Framework for Implementation Research, which include inner and outer setting factors, characteristics of the intervention (ie, telemedicine modality), individual-level factors (eg, provider and patient characteristics), and implementation processes. In total, 11 providers, 3 leaders, and 6 staff participated following verbal consent, and thematic saturation was reached across the full sample. We used a mixed deductive and inductive qualitative analysis approach to study the main influences on telemedicine uptake, implementation, and sustainability during the first year of the COVID-19 pandemic across the 5 settings. RESULTS: The predominant influencers of telemedicine adoption in this study were individual provider experiences and assumptions about patient preference and accessibility. Providers' early telemedicine experiences, especially if negative, influenced preferences for telephone over video and affected sustained use. Telemedicine was most favorably viewed for lower-acuity cancer care, visits less dependent on physical exam, and for patient and caregiver education. A lack of clinical champions, leadership guidance, and vision hindered the implementation of standardized practices and were cited as essential for telemedicine sustainability. Respondents expressed anxiety about sustaining telemedicine use if reimbursements for telephonic visits diminished or ceased. Opportunities to enhance future efforts include a need to provide additional guidance supporting telemedicine use cases and evidence of effectiveness in oncology care and to address provider concerns with communication quality. CONCLUSIONS: In a setting of decentralized care processes, early challenges in telemedicine implementation had an outsized impact on the nature and amount of sustained use. Proactively designed telemedicine care processes with attention to patient needs will be essential to support a sustained role for telemedicine in cancer care.

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.

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 score0.251
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.109
GPT teacher head0.499
Teacher spread0.389 · 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