Trends in cataract surgical treatment within the Brazilian national public health system over a 20-year period: Implications for Universal Eye Health as a global public health goal
Bibliographic record
Abstract
Cataract is a highly prevalent, treatable, and sight threatening condition considered one of the main focuses of public health policies addressing visual impairment and blindness towards Universal Eye Health. We aimed to investigate the trends on number of cataract surgical procedures performed through the Brazilian national health system (SUS) from 2000 to 2019 while also evaluating costs associated with it. The Brazilian Public Health System Information Database (DATASUS) was used as the primary data source for procedures including extracapsular cataract extraction (ECCE) and phacoemulsification. Trends along the years were evaluated through generalized linear models. A total of 8,424,521 cataract procedures were performed from 2000 to 2019, with a significant increase along the years from 228,145 in 2000 to 663,186 in 2019 (p<0.001), a cataract surgical procedure rate change from 13.15 to 32.28 procedures per 10,000 people. It was observed a significant increase on the number of phacoemulsification (p<0.001) and a significant decrease on the number of ECCE (p<0.001). A shift on the predominant technique has occurred between 2007 and 2008 with phacoemulsification increasing its percentual representativity from 34.3% to 69.7% of all procedures, reaching 96.1% in 2019. Phacoemulsification costs per procedure increased 30.5% from from USD$119.00 to USD$155.33 (p = 0.007) and the ECCE costs per procedure increased 29.1% from USD$78.57 to USD$101.43 (p = 0.001). There is an increasing trend of procedures related to cataract treatment performed through SUS along the 20-years period and a switch on the technique predominance from ECCE to phacoemulsification was observed after 2007. The costs associated with both techniques have increased but have not followed the country's overall inflation. Data derived from DATASUS is important to understand the overall panorama of ocular health offered by the national health system and to provide information to guide healthcare leaders on management and planning of public health policies within the 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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".