MétaCan
Menu
Back to cohort
Record W2617847949 · doi:10.2196/jmir.7374

Virtual Visits and Patient-Centered Care: Results of a Patient Survey and Observational Study

2017· article· en· W2617847949 on OpenAlexaffabout
Kimberlyn McGrail, Megan Ahuja, Chad Leaver

Bibliographic record

VenueJournal of Medical Internet Research · 2017
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsCanada Health InfowayInstitute of Health Services and Policy Research
Fundersnot available
KeywordsObservational studyFamily medicineMedicineHealth careVirtual patientCohortMEDLINEIntervention (counseling)Primary careNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Virtual visits are clinical interactions in health care that do not involve the patient and provider being in the same room at the same time. The use of virtual visits is growing rapidly in health care. Some health systems are integrating virtual visits into primary care as a complement to existing modes of care, in part reflecting a growing focus on patient-centered care. There is, however, limited empirical evidence about how patients view this new form of care and how it affects overall health system use. OBJECTIVE: Descriptive objectives were to assess users and providers of virtual visits, including the reasons patients give for use. The analytic objective was to assess empirically the influence of virtual visits on overall primary care use and costs, including whether virtual care is with a known or a new primary care physician. METHODS: The study took place in British Columbia, Canada, where virtual visits have been publicly funded since October 2012. A survey of patients who used virtual visits and an observational study of users and nonusers of virtual visits were conducted. Comparison groups included two groups: (1) all other BC residents, and (2) a group matched (3:1) to the cohort. The first virtual visit was used as the intervention and the main outcome measures were total primary care visits and costs. RESULTS: During 2013-2014, there were 7286 virtual visit encounters, involving 5441 patients and 144 physicians. Younger patients and physicians were more likely to use and provide virtual visits (P<.001), with no differences by sex. Older and sicker patients were more likely to see a known provider, whereas the lowest socioeconomic groups were the least likely (P<.001). The survey of 399 virtual visit patients indicated that virtual visits were liked by patients, with 372 (93.2%) of respondents saying their virtual visit was of high quality and 364 (91.2%) reporting their virtual visit was "very" or "somewhat" helpful to resolve their health issue. Segmented regression analysis and the corresponding regression parameter estimates suggested virtual visits appear to have the potential to decrease primary care costs by approximately Can $4 per quarter (Can -$3.79, P=.12), but that benefit is most associated with seeing a known provider (Can -$8.68, P<.001). CONCLUSIONS: Virtual visits may be one means of making the health system more patient-centered, but careful attention needs to be paid to how these services are integrated into existing health care delivery systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.265
GPT teacher head0.508
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations200
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Medical Internet ResearchSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207