A Protocol for Identifying and Integrating a Core Set of Patient Reported Outcome Measures into Rehabilitation and Community Spinal Cord Injury Care (Preprint)
Bibliographic record
Abstract
BACKGROUND Ensuring care is patient-centered can be particularly challenging in spinal cord injury (SCI). Due to the sudden onset and variable severity, people with SCI often experience a wide range of limitations and secondary complications that evolve over time. Patient-Reported Outcomes (PROs) offer a primary way of monitoring secondary complications, tracking changes in functioning over time, and identifying clinical issues that are salient to the person with SCI. Despite the potential for using PROs in clinical practice, there exist barriers, which impede the implementation of PROs in clinical settings. PRO data must be perceived to be relevant, meaningful and actionable to those who will have to invest the time and effort to collect it. Hypothesis: We hypothesize that collection of SCI-PROs at regular intervals will be feasible and acceptable, will increase patient engagement, satisfaction, communication, and shared decision-making between patients and providers, facilitate goal setting and problem-solving, and increase the focus on patient-valued outcomes. We also hypothesize that this type of clinical encounter will not only provide skill enhancement for clinicians but also increase positive psychological functioning, social participation and engagement, and overall quality of life of persons with SCI. OBJECTIVE 1) Develop a participatory stakeholder-driven process to identify a minimal battery of essential SCI PROs and clinician ratings (SCI-CORE) that will be collected regularly via online electronic data capture with real-time scoring and reporting (EDCR), and 2) to assess acceptability, and feasibility and fidelity of integrating SCI-CORE EDCR into routine care in rehabilitation settings, and 3) evaluate the impact of using longitudinal SCI-CORE assessments on patient and clinicians perceptions. METHODS Phase 1 will use a participatory approach with our stakeholders (n=200) to identify a harmonized core set of PROs for use in SCI rehabilitation. Phase 2 will develop the PRO prototype battery and platform including a customized interface. In Phase 3, we will implement and evaluate the SCI-PRO intervention in a user’s needs assessment allowing us to evaluate facilitators and barriers to implementation and sustainability. Evaluation: Data will be collected through standardized questionnaires, focus groups, individual interviews, local administrative data, and patient chart reviews and web analytics from the e-PRO system and we will evaluate the tool’s reach, acceptability, feasibility and fidelity of implementation and measure the perceptions of care and change in health-related quality of life RESULTS Results of this demonstration study will potentially have an impact that is relevant to make health care more patient-centered, increase shared decision-making, promote self-management, and facilitate clinical research across the SCI network CONCLUSIONS If hypothesized outcomes are observed, data will be used as preliminary data for a full scale RCT evaluating the effectiveness of this approach across settings in the US and Canada. CLINICALTRIAL
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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 | 0.089 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.142 | 0.040 |
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".