Multi-stakeholder Engagement and Development of a Virtual Care Toolkit for Integrated Guideline-Based Low Back Pain Management
Bibliographic record
Abstract
Introduction: The abrupt COVID-19 related healthcare closures across Ontario, Canada resulted in a rapidly growing backlog of patients referred to the Provincial Rapid Access Clinics (RACs) Program, designed to manage patients suffering from unmanageable low back pain (LBP). Left untreated or poorly treated, LBP can lead to a significant burden on patients and the health system. Expeditious implementation of virtual care (VC) became a necessity, however, frontline clinicians identified lack of confidence and experience with LBP-VC. To ensure continuity in patient-centered care, a Toolkit was developed to enable delivery of a standardized guideline-based integrated LBP pathway through VC. Aims, Objectives, Theory or Methods: A coordinated in-depth multi-stakeholder engagement process was utilized to address clinicians’ concerns to promote confident adoption of VC. A system-level rapid response approach led through a centralized clinical and digital provincial infrastructure was used for Toolkit development. Toolkit structure, content and refinement was determined through an iterative mix-methods approach undertaken with provincial LBP stakeholders on how best to implement an established evidence-based shared-care LBP clinical pathway through VC. This approach facilitated acceptable strategies for barrier mitigation and enabled optimization to be rapidly developed on a provincial level with necessary resources and guidelines to deliver standardized LBP-VC across Ontario. Highlights or Results or Key Findings: Toolkit resources have been adopted across 16 urban and rural regions in Ontario. Engaging front-line clinicians, (including spine surgeons), was critical for active implementation of VC that was safe, effective, and met professional requirements. Stakeholders for operational oversight included government, hospital and regional administrators, and professional colleges and associations. With collaborative provincial leadership, barriers and enablers to LBP-VC were systematically identified. Extensive multi-stakeholder consultation which included patient feedback, provided pragmatic information related to privacy; informed consent; professional standards; regional variations, and clinical and patient barriers and enablers. Emergent themes included technology requirements, administrative processes, educational needs, and professional standards. Four hundred and forty LBP-VC patient satisfaction questionnaires were completed (June 2020-May 2021). Based on a 5-point Likert scale, (5 most positive), overall satisfaction and likelihood of participating again was 4.7/5. Qualitative analysis revealed three themes with VC, importance of human connection, patient-perceived virtual physical examination limitations and VC efficiencies. Conclusions: A Toolkit enabled a standardized province-wide approach to LBP-VC. Multi-stakeholder engagement was utilized to understand barriers, identify enablers, and ultimately promote patient and provider adoption and confidence with LBP-VC. With collaborative leadership, and extensive engagement, clinical resources and guidelines were developed and implemented province-wide with excellent face-validity based on patient and provider feedback and uptake. Implications for applicability/transferability, sustainability and limitations: There is a need to further assess patient preference for care delivery during normal and non-emergency circumstances (COVID-19). Future directions include validating LBP-VC physical examination findings compared to hands-on assessment. There is also a need to explore cost-effectiveness of LBP-VC at scale; patient-related factors including demographics, satisfaction, preference, and acceptance with LBP-VC; treatment outcomes, including surgical; safety considerations such as security of online platforms, physical patient safety during the assessment; and comparing rate of escalation to surgeon with in-person and virtual assessment.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".