Costs associated with management of non-communicable diseases in the Arab Region: a scoping review
Bibliographic record
Abstract
BACKGROUND: Global mortality rates resulting from non-communicable diseases (NCDs) are reaching alarming levels, especially in low- and middle-income countries, imposing a considerable burden on individuals and health systems as a whole. This scoping review aims at synthesizing the existing literature evaluating the cost associated with the management and treatment of major NCDs across all Arab countries; at evaluating the quality of these studies; and at identifying the gap in existing literature. METHODS: A systematic search was conducted using Medline electronic database to retrieve articles evaluating costs associated with management of NCDs in Arab countries, published in English between January 2000 and April 2016. 55 studies met the eligibility criteria and were independently screened by two reviewers who extracted/calculated the following information: country, theme (management of NCD, treatment/medication, or procedure), study design, setting, population/sample size, publication year, year for cost data cost conversion (US$), costing approach, costing perspective, type of costs, source of information and quality evaluation using the Newcastle-Ottawa Scale (NOS). RESULTS: The reviewed articles covered 16 countries in the Arab region. Most of the studies were observational with a retrospective or prospective design, with a relatively low to very low quality score. Our synthesis revealed that NCDs' management costs in the Arab region are high; however, there is a large variation in the methods used to quantify the costs of NCDs in these countries, making it difficult to conduct any type of comparisons. CONCLUSIONS: The findings revealed that data on the direct costs of NCDs remains limited by the paucity of this type of evidence and the generally low quality of studies published in this area. There is a need for future studies, of improved and harmonized methodology, as such evidence is key for decision-makers and directs health care planning.
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 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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".