Co-design of a digital solution for total hip and knee arthroplasty journey: A case study
Bibliographic record
Abstract
End-users’ involvement is crucial to develop human-centered solutions; patient acceptance and endorsement by clinicians will be achieved when the features of digital solutions align with their needs and expectations. The aim of the study was to develop the overall concept of digital solution to increase transparency, foster patient adherence, and improve patient-provider communication across the entire total hip and knee arthroplasty journey from admission to discharge, and beyond. Two-stage iterative co-design process was used. Systematic literature reviews and qualitative interviews were conducted to understand the problem. In addition, co-creation sessions were used develop the solution for a reference implementation. As a result, a total of 19 technical and functional requirements were identified. In addition, ten additional functional requirements were identified for future design. The results demonstrate the overall concept of a digital solution for the reference implementation. The uniqueness of the solution lies in the vision of wider integrated systems, which could offer a clinical platform for clinicians to provide patient-focused care remotely, while monitoring patients’ progress closely.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".