Web-Based Follow-up After Total Joint Arthroplasty Proves to Be Cost-Effective, but Is It Safe?
Bibliographic record
Abstract
Commentary Osteoarthritis is one of the most common conditions seen and treated by orthopaedic surgeons worldwide. With mean life expectancy continuing to increase and an ongoing obesity epidemic, the incidence of osteoarthritis is only expected to increase in the future. Total joint arthroplasty is a cost-effective procedure to reduce pain and improve function in patients with advanced osteoarthritis. However, with the increasing demand for this procedure, wait times for the surgery continue to increase. It is projected that approximately 4 million total hip and knee arthroplasties will be performed per year in the United States alone by the year 20301. This increase is associated with an overall increase in health-care costs. In their study, Marsh et al. aimed to compare the cost-effectiveness of web-based follow-up after total joint arthroplasty with that of in-person follow-up. They randomized 229 patients to receive one of these two methods of follow-up and recorded travel costs, time required by the patient, and resource use during the first year of follow-up. They performed a cost analysis from the payer (Ontario Ministry of Health and Long-Term Care) perspective and also from the societal perspective. They reported several important findings. First, they found a reduction in costs (reported in Canadian dollars) from the payer perspective for the patients who received web-based follow-up ($159) compared with in-person follow-up ($185), although the difference was not significant. In light of the recent changes in the United States health-care system, cost-effectiveness and decreasing overall health care-costs are becoming increasing priorities. The results of this study are encouraging and could certainly affect clinical practice, not only in Canada and the United States but all over the world. Especially in countries with a more socialized health-care system (e.g., in parts of Europe), cost-efficiency is a major focus in health care as the discrepancy between supply and demand can lead to an increase in wait times for patients. Careful monitoring of patients with total joint implants is important in both the short and long term. Therefore, reducing the number of follow-up appointments or the length of follow-up is not an option. Even several years after the index procedure, patients continue to be at risk for periprosthetic joint infection, implant wear, loosening, and catastrophic failure. Meding et al.2 reviewed the outcomes of 16,414 primary total knee arthroplasties to determine the time to reoperation for specific failure mechanisms. The median times to failure for the most common failure mechanisms were 1.9 years for infection, 3.1 years for tibial collapse, 4.9 years for implant loosening, and 5.6 years for instability. On the basis of these results, the authors recommended routine follow-up at six months, one year, three years, eight years, twelve years, and every five years thereafter. Even closer follow-up was recommended for those patients with greater pain in the early postoperative period or a high body mass index (≥41 kg/m2). The consequences of complications after total joint replacement surgery can be devastating. However, if a complication is identified at an early stage, treatment is usually less technically demanding for the surgeon; less costly for the health-care payer; and, most important, less debilitating for the patient. By definition, web-based follow-up excludes physical examination of the patient by the surgeon. It would be important to know whether this leads to complications being missed. According to the latest recommendations from the Infectious Diseases Society of America (IDSA), the workup for a possible periprosthetic joint infection should start with a thorough history and physical examination; if there is any suspicion of infection, it should proceed with tests for the erythrocyte sedimentation rate and/or C-reactive protein level, radiographs, arthrocentesis, blood cultures, and advanced imaging3. Although physical examination was not performed in the web-based follow-up group, Marsh et al. indicated that the web-based follow-up sufficed for identifying any issues, as there were no patients in their web-based follow-up group for whom the surgeon believed a complication was missed. However, their sample size may not have been large enough to include an adequate number of patients with complications, possibly causing a type-II error. Another important finding of the study by Marsh et al. was that the societal cost for the web-based follow-up (CDN$222) was also lower than that for in-person follow-up (CDN$245). Other authors have previously identified this benefit as well. Sharareh et al.4 offered patients additional Skype visits in the immediate postoperative period. Although they did not evaluate the cost-effectiveness of this approach, they did demonstrate a reduction in unscheduled clinic visits and telephone calls. This indicates that web-based, Skype, or other remote methods of communication between patients and their surgeon might lead to a decrease in the use of other health-care resources such as the answering service, primary care doctor, emergency department, or urgent care clinic. This can, in turn, decrease overall health-care costs. In conclusion, the study by Marsh et al. showed that a web-based follow-up assessment for tracking patient progress and outcomes following total hip and total knee arthroplasty has lower associated costs, from both the societal and the health-care payer perspective, compared with in-person follow-up. The authors should be commended on a well-conducted, methodologically sound study pointing out the relevance of cost-effectiveness of health care and avoidance of unnecessary office visits. However, future research with a larger patient cohort is needed to demonstrate the safety of web-based follow-up. Complication rates after total joint replacement are relatively low, and early signs and symptoms of complications may be subtle and could therefore be missed when a thorough physical examination is not routinely performed. Lowering health-care costs is important, but patient safety should come first.
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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 | 0.011 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".