Clinical Pathways in Knee and Hip Arthroplasty: Narrative Review on Sustainability, Quality, and Resource Management
Bibliographic record
Abstract
Background: Increasing arthroplasty volumes are testing health care system capacity, budgets, and workforce resilience. Clinical pathways (CPWs) provide a practical, evidence-based structure that aligns perioperative actions from preparation through follow-up. In this review, we treat three aims as coprimary: quality (patient outcomes and adherence to best practice); resource management and efficiency at the episode level (eg, length of stay, perioperative flow, direct costs); and sustainability, defined as the ability to maintain high-quality services over time by optimizing financial, human, and environmental resources while safeguarding equitable access. Objective: This study aimed to describe the main CPW subtypes used in hip and knee arthroplasty and synthesize evidence on their effects on quality of care, resource management, and sustainability. Methods: We conducted a narrative review of studies indexed in PubMed and Cochrane (2013-2024) that evaluated CPWs in total hip and knee arthroplasty. Screening and selection were documented with a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-style flow diagram for transparency, and findings were synthesized thematically. Results: Across CPW models, consistent signals of benefit were identified. Enhanced Recovery After Surgery (ERAS) pathways accelerate recovery and enable earlier discharge without increasing complications, often reducing opioid exposure and time to mobilization. Integrated Clinical Pathways improve standardization and multidisciplinary coordination across settings, reducing unwarranted variability and supporting safer transitions of care. Fast-track programs emphasize early mobilization and streamlined perioperative processes, improving patient flow and satisfaction while decreasing length of stay. Outpatient arthroplasty pathways allow same-day discharge in carefully selected, low-risk patients, reducing bed occupancy and freeing inpatient capacity. Virtual clinics support remote follow-up, patient education, and complication surveillance, decreasing unnecessary in-person visits and optimizing clinician time. Collectively, these pathways align quality improvement with sustainability by lowering bed-days, improving adherence to evidence-based practices, and enabling more efficient use of operating rooms, wards, and workforce. Conclusions: This review highlights the importance of CPWs in improving care delivery and patient outcomes in orthopedic surgery. Future efforts should refine CPWs, integrate digital tools and platforms, adopt standardized sustainability metrics, and stay flexible to evolving service demands.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".