Construction and Application of an Informatics Based Multidisciplinary Management Model for Osteoarthritis Patients in Community
Bibliographic record
Abstract
Background Osteoarthritis has a high rate of disability and deformity, and can be combined with several physical and mental diseases. However, the early symptoms of the disease are not obvious. At present, there are problems in the management of osteoarthritis in the community such as uncoordinated management, inadequate methods and imperfect systems. Objective To construct and evaluate an informatics-based multidisciplinary management model for osteoarthritis patients in community, to promote the management of community osteoarthritis patients and improve the prognosis of the patients. Methods First a multidisciplinary management model of osteoarthritis patients in the community was constructed, including hierarchical management process of patients based on risk factor stratification, the multidisciplinary management team and its division of diagnosis and treatment, then an informatics based multidisciplinary management process was constructed, and information software development was completed. From July 2019 to July 2020, 80 patients with knee osteoarthritis who attended the general outpatient clinics of Dinghai and Daqiao Community Health Service Centers in Shanghai, and the orthopedics outpatient clinics of Yangpu District Central Hospital were randomly assigned into multidisciplinary management groups and general management group, with 40 patients in each group. The patients in general group were given conventional treatment, while the patients in multidisciplinary group were adopted information-based multidisciplinary management. Visual analogue scale (VAS) scores, Western Ontario McMaster University (WOMAC) osteoarthritis index score, the simplified scale of Arthritis Quality Of Life Measurement Scale (AIMS2) scores, Health Literacy Management Scale (HeLMS) scores, and body mass index (BMI) were assessed before and after 12 weeks of management, respectively. Results Before treatment, there were no significant differences in VAS score, WOMAC osteoarthritis index score, AIMS2 score, Helms score, and BMI between patients with knee osteoarthritis in the multidisciplinary and general groups (P>0.05) . After 12 weeks of treatment, the VAS and WOMAC score of both the multidisciplinary and general groups went down, and the health literacy AIMS2 scores and Helms total score were higher after treatment than those before. The difference was statistically significant (P<0.05) . After 12 weeks of treatment, the AIMS2 total score and Helms total score of patients in the multidisciplinary group were higher than those in the general group, and the VAS score, WOMAC osteoarthritis index, and BMI were lower than those in the general group, with significant differences (P<0.05) . Conclusion The implementation of an informatics based community multidisciplinary management model for patients with osteoarthritis of the knee can effectively reduce the patients' joint pain and control their weight, improve their ability of daily living and health literacy, improve the quality of life of patients, and delay the progress of the disease.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".