The use of patient-reported outcome measures in hip and knee arthroplasty in Alberta
Bibliographic record
Abstract
PROMs are part of routine measurement for hip and knee replacement in Alberta, Canada. We provide an overview of how PROMs are implemented in routine care, and how we use PROMs data for decision-making at different levels within the health system. The Alberta Bone and Joint Health Institute (ABJHI) ran a randomized controlled trial to determine the effectiveness and cost-effectiveness of an evidence-based care pathway for hip and knee arthroplasty in 2004. The study included several PROMs questionnaires: Western Ontario and McMaster Universities Osteoarthritis Index, Health Utility Index, Short Form 36 and the EQ-5D-3L. Subsequently, the focus shifted to spread and scale of the care pathway provincially. WOMAC and EQ-5D-3L and a patient experience survey were selected for provincial adoption - captured before surgery, three-months post-surgery, and 12-months post-surgery. These PROMs data were integrated into research and routine clinical practice at the micro, meso and macro levels. At the micro level, PROMs data are used at the individual patient and provider level for patients to provide input on their care and as a tool to communicate with their healthcare providers. We examined the relationship of appropriateness and patient reported outcomes in a prospective cohort study. We evaluated whether routinely collected PROMs could be integrated into a patient decision aid to better inform shared decision making. At the meso level, continuous quality improvement reports are provided routinely to individual health care providers, hospitals and clinics on their performance against the measurement framework and standard key performance indicators. At the macro level, PROMs data are used to evaluate system performance by comparing outcomes across different jurisdictions or over time and support health policy decision making. Combined with administrative databases, we have used simulation models to reflect transition through the continuum of care from disease onset through end-stage care regarding the burden of disease, healthcare resource requirements and associated healthcare costs. The addition of PROMs data in clinical repositories and analyses enables the system to identify and address issues of continuous quality improvement against a measurement framework of performance indicators and to explicitly recognize the trade-offs that are inherent in any resource-constrained system.
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 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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".