A Comparative Study of Rehabilitation Information Systems in 8 Countries: A Literature Review
Bibliographic record
Abstract
Objectives: This study aims to comparatively review the rehabilitation information systems in 8 countries: Canada, the United States, the United Kingdom, Sweden, Australia, Malaysia, Russia, and Iran. Methods: A comprehensive review of published studies without a time limit was explored by searching the keywords, titles, and abstracts. Studies were obtained from the Web of Science, Scopus, PubMed, and Embase databases on May 2, 2021. We also did a Google search engine to explore rehabilitation information system websites in each country. The inclusion criteria included all English and Persian articles in the field of rehabilitation information registration systems or minimum data sets and the availability of complete text of the articles. A total of 13151 related studies were extracted and finally 25 main articles and 6 websites were selected. A similar standard checklist was used to extract and compare the findings. The data items in this checklist included reference, country, registry name, established year, founder, scope, standard classification systems (coding system), data elements, and subcategories of data elements of the registry. Results: The literature review revealed that the United States has international rehabilitation outcomes in three areas of inpatient, outpatient, and pediatric rehabilitation that collect data from around the world. Australia has a national clinical registry for outpatient and inpatient rehabilitation outcomes for adults and children. Canada, with its national rehabilitation reporting system, gathers only adult inpatient rehabilitation information. In sweden, the Swedish Rehabilitation Medical Register includes rehabilitation activities in both inpatient and outpatient care. Rehabilitation in Malaysia with no data sharing and integration is still in its infancy. The rehabilitation information system in the UK only includes specialized rehabilitation services. In Iran, the Welfare Organization registers and collects (inpatient, outpatient, and home care) rehabilitation and financial data of the disabled with the “payment” system. In Russia, only some studies have proposed the launch of a rehabilitation information system. Discussion: The results of this literature review demonstrate that the most comprehensive rehabilitation information systems first belonged to the United States, and then to Australia, Canada, Sweden, the United Kingdom, and Iran in descending order. Meanwhile, a rehabilitation information system is being developed in Malaysia. However, Russia has not yet developed a comprehensive rehabilitation information system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".