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Record W6947594847 · doi:10.3899/jrheum.2025-0314.121

Assessing Quality of Post-TJR Rehabilitation: Care Gaps and Patient Perspectives

2025· article· en· W6947594847 on OpenAlexaffvenueabout

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsCentres Intégré Universitaires de Santé et de Services SociauxResearch CanadaVancouver Coastal Health Research InstituteVancouver Biotech (Canada)Vancouver Coastal Health
Fundersnot available
KeywordsRehabilitationUsabilityCLARITYDelphi methodPatient satisfactionQuality (philosophy)Descriptive statisticsIntervention (counseling)MEDLINE

Abstract

fetched live from OpenAlex

Objectives Patients’ access to and experiences with rehabilitation care after total hip (THR) and knee (TKR) replacement surgery vary greatly across Canada. To better understand these differences and increase access to acceptable, effective and equitable care, we developed quality indicators (QIs). The 10 QIs based on literature reviews and a Delphi consensus process,[1,2] reflect the minimum standard of rehabilitation care that patients should expect to receive after THR and TKR. Methods To capture patients’ perspectives and care experiences, we created a patient QI questionnaire and co-tested its usability with patient partners, to ensure clarity and ease of use. Patients indicated whether they received the QI-specific assessment or intervention (5-point ordinal scale) and rated its importance to them (4-point scale). We collected demographic and treatment information and explored respondents’ rehabilitation experiences and satisfaction with outcomes. The English survey was administered through REDCap and fully launched January 2024 for individuals who had a recent THR or TKR and completed their supervised rehabilitation. A French language version will be launched shortly. We performed descriptive data analysis (means, standard deviation, percentages). Results To date, 192 individuals completed the full questionnaire with representation from all provinces and territories (Table 1). On average, respondents reported that 45.1% (SD 23.8%) and 43.4% (SD 28.2%) of the QIs were met for THR and TKR respectively. Adherence was lowest for QI-2 (comprehensive physical exam) and highest for QI-6 (assessing/supporting physical activity). The QI with highest importance ratings related to QI-9 (exercise interventions) for both procedures. We found discordance between patients’ ratings of what was done (QI met) and what was important. For example (TKR), QI-3 (use of standardized patient-reported outcome measure for function), was met for 40% of patients yet 63% rated this as very important. Overall satisfaction with outcomes of surgery and rehabilitation (satisfied/very satisfied) were the same for THR (91%) and TKR (90%); however, a higher proportion of individuals with a THR (56%) were very satisfied compared to TKR (48%). Overall experience ratings (good/excellent) were similar (THR 77%, TKR 82%). Additional analyses of associations between respondent demographics, QI adherence, and rehab care experience and satisfaction will be presented. Table 1 Select participant demographics for English language survey Conclusion From the patient perspective, there is low overall physiotherapist adherence to the 10 THR and TKR rehabilitation QIs. Patients’ importance ratings for many of these QIs highlight the need for change in clinical practice and further testing of the QIs to assess their impact on patient outcomes and care experiences. [1.] Westby M. Osteoarthritis Cartilage 2018;26:370-82. [2.] Westby M. Physiother Canada 2022;e20220083.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.327
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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