1. IAPB GA 9 Hyderabad 2012 What can be learned from the CSR/CSC; what remains unknown and what metrics could provide more information Marissa J. Carter, PhD MA

2. Cataract Metrics To understand how cataract surgery is impacting at the national or district level, we need to have data on at least 3 metrics:  The CSR (cataract surgical rate)  The CSC (cataract surgical coverage) at the 3 different VA thresholds  Outcomes for the surgery itself (and comparison to WHO criteria). More metrics would be nice, but requires large changes in data gathering.

3. Relationships Between CSR and CSC To understand possible relationships between the CSR and CSC, and what we can learn from them, we need resurveys of the same geographical area. This emphasizes why surveys (such as RAABs) should be done more than ONCE. Resurveys should be done every 5-10 years. CSR tells us how many surgeries are being performed while CSC tells us what proportion of the cataract blind are receiving the surgeries To understand the information that can be extracted, a series of illustrations will be presented.

4. Scenario 1: CSR increases but CSC blindness (<3/60) does not improve Reasons: blind ignored; CSR does not match cataract incidence nor address “backlog” CAUTION: CSC data is divided up according to VA; CSR cannot normally be divided this way

5. Scenario 2: CSR increases but CSC blindness (<3/60) becomes worse Reasons: blind ignored; CSR does not match cataract incidence nor address “backlog”

6. Scenario 3: CSR increases and CSC blindness (<3/60) greatly improves Reasons: blind addressed; CSR matches cataract incidence and addresses “backlog”

7. Scenario 4: CSR increases and CSC blindness (<3/60) improves but situation in rural areas is still poor Requires CSR and CSC data to be divided between urban and rural areas. CSR is much lower in rural areas and may be responsible for poor CSC

8. Scenario 5: CSR increases and CSC blindness (<3/60) improves but there is a gender inequity situation Requires CSR and CSC data to be divided between males and females. CSR is much lower for females and may be responsible for poor CSC

9. Scenario 6: CSR increases and CSC blindness (<3/60) improves but situation is better for persons with preoperative VA that is less severe May indicate that people with less severe preoperative VA are receiving proportionately more surgeries

10. Paraguay: CSC blindness (<3/60) improved greatly and CSR has doubled. Is the increase in CSR sufficient to account for CSC improvements? CSC data can be analyzed to estimate number of surgeries that have taken place

11. Scenario 8: CSR increases hugely along with CSC but SRR remains relatively poor If SRR remains poor, then CSR/CSC are meaningless

12. The Effect of Aging Populations The aging of populations due to increased lifespan is by far the largest factor that drives need for cataract surgery. If the CSR is not adjusted to keep pace with the increase in the population over 50 years old, then CSC will slowly decline.

13. Change in Population >= 50 Years from 2000 to 2011 Source: U.N. Data

14. More Data, More Possibilities for Analysis CSC data contains information on several factors, such as gender, and whether an area is rural or urban. CSR data currently does not contain data on these factors, or preoperative VA. If data on gender, location, and preoperative VA were reported, CSR could be come more useful and be combined with CSC and surgical outcome data. For some countries, location data is currently available when calculating CSRs.

15. Conclusions ●When a geographic area has been surveyed more than once, creating graphical outputs of CSR/CSC data can help visualize what has happened ●Most CSR data does not have factor information (i.e., rural/urban or male/female); adding this data would tell us much more ●Without SRR information (surgical outcomes), CSR/CSC does not tell us the whole story.