Patient and healthcare provider reported barriers and enablers to virtual or remote-only follow-up models for cardiovascular implantable electronic devices: protocol for a qualitative framework synthesis
Bibliographic record
Abstract
BACKGROUND: Virtual care models are used to follow-up patients with cardiovascular implantable electronic devices (CIED), including pacemakers, implantable cardioverter defibrillators, and cardiac resynchronization therapy. There is increasing interest in the expansion of virtual, or even remote-only, CIED care models to alleviate resource and economic burden to both patients and specialty device clinics and to maintain or improve equity and access to high-quality cardiovascular care. This qualitative framework synthesis aims to identify barriers and enablers to virtual care models from both the perspective of the patient and device clinics. How setting, context, equity factors or other aspects influence these factors, or satisfaction with care, will also be investigated. METHODS: We will perform a systematic literature search in MEDLINE, Embase, PsycINFO, CINAHL, Proquest Dissertations & Theses, other EBM Reviews, and trial registry databases. Screening will be completed by two independent review authors. Original research articles having a qualitative component (i.e., qualitative, mixed-, or multi-method) are eligible. Study populations of interest are (a) individuals with a CIED or (b) healthcare providers involved in any aspect of virtual or remote follow-up of patients with CIEDs. Eligibility will be restricted to studies published after January 1, 2000 in English or French. Data will be captured using standardized templates based on the domains and constructs of the Theoretical Domains Framework and the Warwick Patient Experiences Framework. The Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research will be applied to all included studies. The GRADE-CERQual approach will be applied to assess and summarize confidence in key findings. Reporting will follow the enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) statement. Detailed descriptive results will be presented, and summary of qualitative findings tables will be produced. DISCUSSION: While a number of trials have captured the clinical effectiveness and safety of virtual follow-up for CIEDs, there has been less attention given to factors affecting use and implementation of remote care by patients and healthcare providers or satisfaction with care. Results from this qualitative framework synthesis will provide important lived experience data from both patients and healthcare providers which will be essential to incorporate in clinical guidelines. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020160533.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".