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Record W2606652276 · doi:10.23889/ijpds.v1i1.392

Virtual visits: Friend or foe of patient-centred care?

2017· article· en· W2606652276 on OpenAlexaffabout
Kim McGrail

Bibliographic record

VenueInternational Journal for Population Data Science · 2017
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedical prescriptionPrimary careMedicineFamily medicineCohortPaymentPopulationService (business)Health careVirtual patientMedical emergencyNursingWorld Wide WebBusinessComputer science

Abstract

fetched live from OpenAlex

ABSTRACT BackgroundPatient-initiated virtual visit consultations in primary care are a new form of care that is increasingly available in parts of Canada. There is a need to develop an understanding of patient perspectives on virtual visits and how they affect patient experience, access to care, and health services utilization patterns from a system perspective. This paper will shed some light on this new form of patient care delivery. ApproachWe accessed fee-for-service physician payment data, patient and physician demographic data, and PharmaNet prescription data, from 2010/11–2013/14. We examined overall utilization of GP virtual visits defined by BC physician billing codes to understand the characteristics of providers and patients providing and using these services. We assessed the relationship of virtual visits with other types of care including referrals to specialist services, medication prescribing, and overall costs of physician care. We used a matched cohort and time series analysis to answer the question of whether virtual visits displace or add to other forms of patient care. ResultsWhile the growth in virtual visits has been rapid in BC, these services still represent a very small proportion of overall primary care. There are patient users in urban and rural regions of BC, but less than 1% of the BC population has had a virtual visit. Users of virtual visits tend to be younger and use is more likely for people with one or more major conditions (measured by ADGs). Only 144 primary care GPs (out of close to 5,000 in BC) provided virtual visits in 2013/14. About one-third of patients have a virtual visit with a physician already known to them, with the rest seeing a physician for the first time during their virtual visit. These visits do not appear to add costs to care, though there is a suggestion that it they are more effective as part of an ongoing therapeutic relationship. ConclusionVirtual visits are a small portion of total primary care but are expected to increase. In some cases virtual visits appear to supplement existing forms of access, offering a new means by which to interact with a known provider. In other cases virtual care is with a new provider, which may suggest walk-in clinic type of service use. The implications of these two scenarios are clearly different, and further research with longer follow-up will be helpful in understanding long-term implications.

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)0.014
metaresearch head score (Gemma)0.108
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.108
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.008
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0190.002

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 head0.103
GPT teacher head0.456
Teacher spread0.353 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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