Development of a Cocreated Perioperative Joint Replacement Digital Care Pathway to Improve Surgical Outcomes Following Joint Replacement: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Recently, perioperative care has gained attention for its ability to improve outcomes, reduce costs, and enhance patient satisfaction, especially when multidisciplinary support is involved. Despite these benefits, patient compliance remains low due to limited engagement in program design and practical barriers such as transportation, particularly for older adults. Co-designed digital health solutions offer a promising, scalable approach to delivering personalized, accessible perioperative care, with emerging evidence supporting their feasibility and effectiveness in patients who undergo joint replacement. OBJECTIVE: The objectives of this study protocol are to outline the methods to address three study aims: (1) understand gaps and unmet needs, including knowledge, perceptions, barriers, and acceptability, during the perioperative patient journey of hip and knee arthroplasty; (2) co-create a novel patient-centric digital care pathway (DCP) that provides education and systematically captures patient-reported outcomes; and (3) evaluate the feasibility of implementation, appropriateness, and acceptability of the pathway when tested in patients undergoing nontraumatic hip and knee joint arthroplasty. METHODS: This mixed methods co-design and implementation study will be conducted across 3 phases informed by the generative co-design framework for health care interventions. In phase 1 (predesign), patient interviews and journey mapping will be used to identify perioperative care gaps to be addressed in the DCP. In phase 2 (co-design), care gaps will be collaboratively framed, and iterative prototyping of the DCP will be conducted with consumer feedback and pilot testing. In phase 3 (evaluation), the feasibility of the DCP will be assessed using a previously reported framework. Inclusion criteria will vary across phases, focusing on people with lived experience or undergoing hip or knee joint replacement and relevant clinical or administrative staff. RESULTS: The study was funded in September 2024, with phase 1 commencing in July 2025 and phase 2 in October 2025. Phase 3 is projected to commence before the end of 2025 and conclude 6 months later. As of October 2025, 13 people had been recruited, interviews were completed for phase 1, and recruitment for phase 2 had commenced. CONCLUSIONS: This protocol enhances methodological transparency by detailing the co-design approach, strengthening the evidence base, and supporting the development of a credible, transferable DCP. It addresses the lack of patient-centric perioperative programs in joint replacement care by incorporating individual needs and preferences. The digital format helps overcome access barriers, such as transport limitations, enabling patients to engage with the pathway anywhere. Additionally, patient-reported outcome measures collected through the DCP will improve understanding of recovery trajectories following hip and knee replacements. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/85701.
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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 | 0.088 | 0.077 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.012 |
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".