Protocol for a Multistage Mixed-Methods Evaluation of Multidisciplinary Chronic Kidney Disease Care Quality Following Integration of Virtual and In-Person Care During the COVID-19 Pandemic
Bibliographic record
Abstract
Background: Multidisciplinary care of patients with chronic kidney disease (CKD) as it previously existed was predicated on an evidence and experience base of improved patient outcomes within an established and well-described service delivery model. The onset of the COVID-19 pandemic brought with it a departure from this established care delivery model toward integration of virtual care and in-person care. Objective: To develop an evaluation framework to determine whether this shift in service delivery models has affected quality of multidisciplinary kidney care and/or patient-clinician interactions and relationships. Design: A sequential multiphase, mixed-methods evaluation. Setting: All 15 British Columbia (BC) multidisciplinary kidney care clinics (KCCs). Participants: All patients and all clinicians in all KCCs across BC will be invited to participate in the planned evaluation. Measurements: Qualitative and quantitative feedback from patients and families living with CKD and KCC clinicians. Methods: The planned multiphase evaluation of virtual care integration in KCCs will be conducted across all 15 KCCs in the province of BC, Canada. The following phases are proposed: (1) review of current virtual care integration and practices, (2) assessment of patient and clinician experiences and perspectives via semi-structured interviews, (3) validation of those patient and clinician perspectives via survey of a larger sample, (4) compilation and analysis of all phases to provide informed recommendations for patient and visit format selection in a mixed in-person and virtual multidisciplinary clinic setting. Limitations: This work will not capture any information about the relationship between differences in virtual usage parameters and clinical outcomes or financial implications. Conclusions: There is no existing framework for either evaluation of multidisciplinary CKD care quality in a virtual setting or evaluation of care quality following a substantial change in service delivery models. The proposed evaluation protocol will enable better understanding of the nuances in kidney care delivery in this new format and inform how best to optimize the integration of virtual and pre-existing formats into kidney clinic care delivery beyond the pandemic. Beyond the current evaluation, this protocol may be of use for other jurisdictions to evaluate their own local instances of virtual care implementation and integration. The model may be adapted to evaluate quality of multidisciplinary kidney care delivery following other changes to clinic service delivery models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.114 | 0.084 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.085 | 0.014 |
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 source (direct Gemma or distilled Codex), 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".