Skip to content
PaperFren

Telemedicine

How did rural telemedicine change in COVID?

Chu C, Cram P, Pang A, et al. · Journal of medical Internet research · 2021

Open access · cc by · source: Europe PMC

Rural Ontario telemedicine use jumped from about 1.4% of patients in 2012 to 28% in early 2020 as temporary billing codes expanded virtual care.

Study at a glance

Design
Other — Ontario health-administrative descriptive comparison of telemedicine use in 2012, 2016, and early 2020
N
N=1033271 · 2020 rural resident denominator; 290,401 (28.1%) with ≥1 telemedicine visit (vs 14,666/1,017,546 in 2012)
Population
Rural Ontario patients in health-administrative data
Outcome
Prevalence and demographic patterns of telemedicine use

Structured fields used in claim comparison tables when every cited study has a complete layer.

Key findings

Rural telemedicine users rose from 14,666 (1.4%) to 290,401 (28.1%). Pre-pandemic use concentrated in Northern Ontario and younger adults; during COVID, use broadened geographically, skewed female, rose with age, and surged in urban as well as rural areas.

Methodology

Using health-administrative data, investigators compared rural patients with ≥1 telemedicine visit in 2012, 2016, and the first half of 2020, describing age, sex, region, income, and chronic-disease patterns as COVID-era fee codes enabled broader virtual visits.

Limitations

Utilization data do not measure clinical quality, equity of outcomes, or whether virtual visits replaced necessary in-person exams safely.

How this study connects

Role on claims

Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.

  • SupportsTelemedicineconcept

    Multiple studies in this library examine telemedicine with empirical patient or population outcomes rather than opinion alone.

    Evidence for the claim as stated.

  • SupportsTelemedicineconcept

    Rural telemedicine users rose from 14,666 (1.4%) to 290,401 (28.1%). Pre-pandemic use concentrated in Northern Ontario and younger adults; during COVID, use broadened geographically, skewed female, rose with age, and surged in urban as well as rural areas.

    Evidence for the claim as stated.

  • SupportsTelemedicineconcept

    Effect sizes and settings differ across telemedicine studies — digital vs clinic, trial vs observational — so results should not be pooled casually.

    Evidence for the claim as stated.

  • Repeated administrative snapshots of rural telemedicine in Ontario are sometimes filed with surveys even though nobody filled a questionnaire. Users rose from 14,666 (1.4%) in earlier years to 290,401 (28.1%) in the first half of 2020 as COVID-era fee codes broadened virtual visits. Pre-pandemic use concentrated in Northern Ontario and younger adults; during COVID, use broadened geographically, skewed female, rose with age, and surged in urban as well as rural areas. Utilisation is not clinical quality or safe substitution for needed exams.

    Evidence for the claim as stated.

  • Hypothetical acceptance, reported coverage, administrative utilisation and CRT endline surveys are four different measurement jobs. Libya's 79.6% at ≥90% efficacy is a stated intention under a scenario. Seasonal flu coverage of ~21% and pandemic coverage of 11.1% are recalled past behaviour. Telemedicine's jump from 1.4% to 28.1% is billing data. SASA!'s ~50% IPV contrast is a randomised community comparison that used surveys. Averaging those percentages as 'survey findings on uptake' erases the disagreements.

    Evidence for the claim as stated.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

  • Scope difference — different assays, populations, or outcomes

    SupportsTelemedicine

    Effect sizes and settings differ across telemedicine studies — digital vs clinic, trial vs observational — so results should not be pooled casually.

  • Scope difference — different assays, populations, or outcomes

    Hypothetical acceptance, reported coverage, administrative utilisation and CRT endline surveys are four different measurement jobs. Libya's 79.6% at ≥90% efficacy is a stated intention under a scenario. Seasonal flu coverage of ~21% and pandemic coverage of 11.1% are recalled past behaviour. Telemedicine's jump from 1.4% to 28.1% is billing data. SASA!'s ~50% IPV contrast is a randomised community comparison that used surveys. Averaging those percentages as 'survey findings on uptake' erases the disagreements.

Related papers in this topic

Same topic cluster — not a recommendation engine.