MétaCan
Menu
Back to cohort
Record W4214533912 · doi:10.9778/cmajo.20210065

Patient and caregiver perspectives on virtual care: a patient-oriented qualitative study

2022· article· en· W4214533912 on OpenAlexafffundvenueabout
Sophy Chan-Nguyen, Anne O’Riordan, Angela Morin, Lisa McAvoy, Eun‐Young Lee, Veronica Lloyd, Ramana Appireddy

Bibliographic record

VenueCMAJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersCanadian Institutes of Health Research
KeywordsFocus groupQualitative researchThe InternetGrounded theoryConfidentialityPatient portalHealth careNursingPsychologyData collectionMedicineMedical educationWorld Wide WebComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Since the onset of the COVID-19 pandemic, virtual care solutions have been rapidly adopted across the country to provide safe, quality care to diverse patient populations. The objective of this qualitative case study was to understand patient and caregiver experiences of virtual care to identify barriers and gather suggestions to address them. METHODS: In this patient-oriented project, we sought to understand gaps in virtual care experienced by patients and caregivers, using virtual focus groups. With the assistance of a patient research liaison, we engaged 2 patient partners as full partners; they participated in study conception, data collection, data analysis and knowledge translation. Recruitment was done through email by disseminating the study poster to 30 community organizations and health units in Ontario and British Columbia. We conducted a constructivist, qualitative study guided by grounded theory methodology. One researcher employed in-vivo coding, followed by axial coding with focus group participants, followed by selective coding with the study team. The study took place from November to December 2020. RESULTS: We conducted 6 focus groups with 13 patients and 5 caregivers. The analysis resulted in 6 major themes and 17 minor themes. Key findings showed that barriers related to access to technology and Internet, language and cultural differences were challenges to virtual care. Participants identified special considerations surrounding caregiver and family involvement; privacy, consent and confidentiality; and the patient-physician relationship. Participants suggested that technology and the Internet be universally accessible and that virtual care modalities be integrated (e.g., consolidated patient portal) to improve virtual care. INTERPRETATION: There are multiple patient-identified barriers to accessing virtual care in Canada; patients can provide insights into ways to address these barriers. Future research should include robust patient engagement to explore ways to address these challenges and barriers to ensure that virtual care can be equitable, accessible and safe for all users. PLAIN LANGUAGE SUMMARY: Although virtual care has been rapidly adopted and scaled up in health care institutions across the country, few improvements informed by patient and caregiver experiences have been made. Driven by concerns expressed by patient partners, our study team undertook a patient-partnered qualitative study to understand the barriers of virtual care from the perspectives and experiences of patients and caregivers. Our study team created the interview guide drawing from our previous patient-oriented qualitative studies and designed an orientation package to provide resources related to the focus groups and to introduce participants to the study team. Drawing from local health teams, clinics and patient advisory groups, the study team recruited 13 patients and 5 caregivers to participate in 6 focus group interviews. An analysis based on grounded theory was undertaken, with participation from both the study team and participants. Lack of access to technology or Internet and language barriers were determined to be the primary challenges in virtual care. Special considerations to caregiver and family involvement, privacy and confidentiality, as well as the patient-physician relationship were considered priorities to improving access to virtual care. Participants offered recommendations and potential solutions to address barriers and challenges in virtual care, which can serve to encourage large-scale policy and programmatic changes in patient-centred ways.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.398
Teacher spread0.360 · 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.

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

Citations33
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueCMAJ OpenSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207