The Better Operative Outcomes Software Tool (BOOST) Prospective Study: Improving the Quality of Cataract Surgery Outcomes in Low-Resource Settings.

PURPOSE: Post-operative vision impairment is common among patients who have undergone cataract surgery in low-resource settings, impacting quality of clinical outcomes and patient experience. This prospective, multisite, single-armed, pragmatic validation study aimed to assess whether receiving tailored recommendations via the free Better Operative Outcomes Software Tool (BOOST) app improved surgical outcomes, as quantified by post-operative unaided distance visual acuity (UVA) measured 1-3 days after surgery. METHODS: During the baseline data collection round, surgeons in low and middle-income countries recorded clinical characteristics of 60 consecutive cataract cases in BOOST. Additional data on the causes of poor outcomes from 20 consecutive cases with post-operative UVA of <6/60 (4-12 weeks post-surgery) were entered to automatically generate tailored recommendations for improvement, before 60 additional consecutive cases were recorded during the follow-up study round. Average UVA was compared between cases recorded in the baseline study round and those recorded during follow-up. RESULTS: Among 4,233 cataract surgeries performed by 41 surgeons in 18 countries, only 2,002 (47.3%) had post-operative UVA 6/12 or better. Among the 14 surgeons (34.1%) who completed both rounds of the study (1,680 cases total), there was no clinically significant improvement in post-operative average UVA (logMAR units ±SD) between baseline (0.50 ± 0.37) and follow-up (0.47 ± 0.36) rounds (mean improvement 0.03, p = 0.486). CONCLUSIONS: Receiving BOOST-generated recommendations did not result in improved UVA beyond what could be expected from prospective monitoring of surgical outcomes alone. Additional research is required to assess whether targeted support to implement changes could potentiate the uptake of app-generated recommendations and improve outcomes.

A practical model for effective eye care delivery in Southeast Asian rural communities: A proposal built based on experts' recommendations.

PURPOSE: To evaluate rural community-based eye care models from the perspective of community ophthalmology experts and suggest sustainable technological solutions for enhancing rural eye care delivery. METHODS: A semi-structured descriptive survey, using close-ended and open-ended questions, was administered to the experts in community ophthalmology sourced through purposive sampling. The survey was self-administered and was facilitated through online platforms or in-person meetings. Uniform questions were presented to all participants, irrespective of their roles. RESULTS: Surveyed participants (n = 22 with 15 from India and 7 from Nepal) in high-volume tertiary eye hospitals faced challenges with resources and rural outreach. Participants had mixed satisfaction with pre-operative screening and theatre resources. Delayed presentations and inexperienced surgeons contributed to the surgery complications. Barriers to rural eye care included resource scarcity, funding disparities, and limited infrastructure. In rural/peri-urban areas 87% of participants agreed with providing primary eye care services, with more than 60% of the experts not in agreement with the makeshift center model of eye care delivery. Key components for an effective eye care model are sustainability, accessibility, affordability, and quality. These can be bolstered through a healthcare management platform and a human-chain supply distribution system. CONCLUSION: Tailored interventions are crucial for rural eye care, emphasizing the need for stronger human resources, optimized funding, and community awareness. Addressing challenges pertinent to delayed presentation and surgical training is vital to minimizing complications, especially with advanced cataracts. Enhancements in rural eye care demand a comprehensive approach prioritizing accessibility, affordability, and consistent quality.

Evaluation and model to achieve sex parity in cataract surgical coverage in Theni district, India.

BACKGROUND/AIMS: To propose an approach to determine the target ratio of cataract surgical rates (CSRs) of female to male subpopulations to increase sex parity in cataract surgical coverage (CSC), based on the sex gap in cataract burden and incidence, and demonstrate its application to Theni district, India. METHODS: A population-based longitudinal study between January 2016 and April 2018. We recruited 24 327 participants using random cluster sampling. We conducted detailed eye examinations of 7087 participants aged ≥40 years (4098 females, 2989 males). We fit exponential models to the age-specific and sex-specific cataract burden and estimated annual incidence rates. We developed a spreadsheet-based planning tool to compute the target CSR ratio of female to male subpopulations. RESULTS: Among those aged ≥40 years, cataract burden was 21.4% for females and 17.5% for males (p<0.05). CSC was 73.9% for females versus 78.6% for males (p<0.05), with an effective CSC of 52.6% for females versus 57.6% for males (p<0.05). Treating only incident cataracts each year requires a target CSR ratio of female to male subpopulations of 1.30, while addressing in addition 10% of the coverage backlog for females and 5% for males requires a target CSR ratio of 1.48. CONCLUSIONS: The female population in Theni district, as in many low-income and middle-income countries, bears a higher cataract burden and lower CSC. To enhance sex parity in coverage, both the higher number of annual incident cataracts and the larger backlog in females will need to be addressed.

Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis.

PURPOSE: To evaluate the diagnostic accuracy of artificial intelligence (AI)-based automated diabetic retinopathy (DR) screening in real-world settings. DESIGN: Systematic review and meta-analysis METHODS: We conducted a systematic review of relevant literature from January 2012 to August 2022 using databases including PubMed, Scopus and Web of Science. The quality of studies was evaluated using Quality Assessment for Diagnostic Accuracy Studies 2 (QUADAS-2) checklist. We calculated pooled accuracy, sensitivity, specificity, and diagnostic odds ratio (DOR) as summary measures. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO - CRD42022367034). RESULTS: We included 34 studies which utilized AI algorithms for diagnosing DR based on real-world fundus images. Quality assessment of these studies indicated a low risk of bias and low applicability concern. Among gradable images, the overall pooled accuracy, sensitivity, specificity, and DOR were 81%, 94% (95% CI: 92.0-96.0), 89% (95% CI: 85.0-92.0) and 128 (95% CI: 80-204) respectively. Sub-group analysis showed that, when acceptable quality imaging could be obtained, non-mydriatic fundus images had a better DOR of 143 (95% CI: 82-251) and studies using 2 field images had a better DOR of 161 (95% CI 74-347). Our meta-regression analysis revealed a statistically significant association between DOR and variables such as the income status, and the type of fundus camera. CONCLUSION: Our findings indicate that AI algorithms have acceptable performance in screening for DR using fundus images compared to human graders. Implementing a fundus camera with AI-based software has the potential to assist ophthalmologists in reducing their workload and improving the accuracy of DR diagnosis.

Neonatal mortality risk of vulnerable newborns by fine stratum of gestational age and birthweight for 230 679 live births in nine low- and middle-income countries, 2000-2017.

OBJECTIVE: To describe the mortality risks by fine strata of gestational age and birthweight among 230 679 live births in nine low- and middle-income countries (LMICs) from 2000 to 2017. DESIGN: Descriptive multi-country secondary data analysis. SETTING: Nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION: Liveborn infants from 15 population-based cohorts. METHODS: Subnational, population-based studies with high-quality birth outcome data were invited to join the Vulnerable Newborn Measurement Collaboration. All studies included birthweight, gestational age measured by ultrasound or last menstrual period, infant sex and neonatal survival. We defined adequate birthweight as 2500-3999 g (reference category), macrosomia as ≥4000 g, moderate low as 1500-2499 g and very low birthweight as <1500 g. We analysed fine strata classifications of preterm, term and post-term: ≥42+0 , 39+0 -41+6 (reference category), 37+0 -38+6 , 34+0 -36+6 ,34+0 -36+6 ,32+0 -33+6 , 30+0 -31+6 , 28+0 -29+6 and less than 28 weeks. MAIN OUTCOME MEASURES: Median and interquartile ranges by study for neonatal mortality rates (NMR) and relative risks (RR). We also performed meta-analysis for the relative mortality risks with 95% confidence intervals (CIs) by the fine categories, stratified by regional study setting (sub-Saharan Africa and Southern Asia) and study-level NMR (≤25 versus >25 neonatal deaths per 1000 live births). RESULTS: We found a dose-response relationship between lower gestational ages and birthweights with increasing neonatal mortality risks. The highest NMR and RR were among preterm babies born at <28 weeks (median NMR 359.2 per 1000 live births; RR 18.0, 95% CI 8.6-37.6) and very low birthweight (462.8 per 1000 live births; RR 43.4, 95% CI 29.5-63.9). We found no statistically significant neonatal mortality risk for macrosomia (RR 1.1, 95% CI 0.6-3.0) but a statistically significant risk for all preterm babies, post-term babies (RR 1.3, 95% CI 1.1-1.5) and babies born at 370 -386 weeks (RR 1.2, 95% CI 1.0-1.4). There were no statistically significant differences by region or underlying neonatal mortality. CONCLUSIONS: In addition to tracking vulnerable newborn types, monitoring finer categories of birthweight and gestational age will allow for better understanding of the predictors, interventions and health outcomes for vulnerable newborns. It is imperative that all newborns from live births and stillbirths have an accurate recorded weight and gestational age to track maternal and neonatal health and optimise prevention and care of vulnerable newborns.

Comparison of cataract surgery outcomes between a secondary and a tertiary eye hospital in Tamil Nadu, India.

PURPOSE: To examine the difference in post-operative visual outcomes of cataract surgeries between a tertiary and secondary centre at Aravind Eye Hospitals in Tamil Nadu, India. METHODS: Our retrospective cross-sectional study analysed cataract surgeries at a secondary centre and its associated tertiary centre in 2021. Our main outcome measures were postoperative best corrected visual acuity (BCVA), spherical equivalent, and intraoperative and postoperative complications. Two-sample proportion tests and logistic regression analyses were performed. RESULTS: The analysis of 32,302 cataract surgeries in 2021 of which 4357 were performed at the secondary centre and 27,945 were performed at the tertiary centre showed that the tertiary centre operated on more advanced cataract condition (p < 0.001). Intraoperative (p < 0.001) and post-operative complication rates (p < 0.001) were higher in the tertiary centre. The odds of effective outcomes (BCVA > = 6/12) controlling for all covariates are poorer (p < 0.0001) in the tertiary centre for both phacoemulsification (phaco) and manual small incision cataract surgeries (MSICS). CONCLUSION: World Health Organization recommendations for the effective outcome of cataract surgery are met by both the tertiary and secondary centres, but the odds of effective outcomes in the tertiary centre was lower after adjusting for all known factors. Further investigations of the causes of poor vision in both phaco and MSICS in the tertiary centre are needed to improve the situation.

Evaluation of a telemedicine-enabled universal eye health delivery model in rural southern India.

OBJECTIVES: To evaluate the accuracy of tele-ophthalmic examination (TOE) for common ocular conditions in comparison with the gold-standard in-person examination (IPE) for diagnosis and treatment advice. METHODS: In a prospective, diagnostic accuracy validation study, we recruited 339 consecutive new patients, aged ≥16 years, visiting a vision centre (VC) associated with Aravind Eye Hospital in south India during January and February, 2020. All participants underwent the TOE, followed by IPE on the same visit. The in-person ophthalmologist was masked to the TOE diagnosis and treatment advice. Data were analysed via the sensitivity specificity of TOE versus the gold-standard IPE. RESULTS: TOE achieved high sensitivity and specificity for identifying normal eyes with 87.4% and 93.5%, respectively. TOE had high sensitivity for cataracts (91.7%), infective conjunctivitis (72.2%), and moderate sensitivity for pterygium (62.5%), DR (57.1%), non-serious injury (41.7%), but low sensitivity for glaucoma (12.5%). TOE had high specificity ranging from 93.5% to 99.8% for all diagnoses. The sensitivity for treatment advice ranged from 58.1% to 77.2% and specificity from 96.9% to 100%. CONCLUSIONS: The TOE in VCs has acceptable accuracy to an IPE by an ophthalmologist for correctly identifying and treating major eye ailments. Through providing universal eye care to rural populations, this model may contribute to work toward achieving Universal Health Coverage, which is a linchpin of the health-related U.N. Sustainable Development Goals (SDG).

Factors Affecting Follow-Up Adherence of Glaucoma Patients.

PURPOSE: The objective of our study is to understand the factors associated with non-adherence to the physician's follow-up advice by persons with glaucoma. METHODS: We use a four-year panel dataset containing demographic, clinical, and intervention details and doctor's advised follow-up date for a random sample of 2,622 glaucoma patients from an Indian tertiary eye care hospital. We model this unique "advised follow-up date" in multivariate logistic regressions to identify factors associated with patients' coming early or late as against on-time. An OLS regression also examines an association between delayed follow-up and declining visual acuity. RESULTS: Demographic variables such as age, gender, distance to hospital, IOP, and visual acuity were not associated with delayed adherence to follow-up. Patients advised to review within 2 months (p < .001), paying patients (p < .001), and those habituated to routine follow-up (diabetes patients) (p < .01) are less likely to delay care-seeking. Patients are more likely to come on-time in visits immediately after clinical interventions relative to later ones (p < .001). Our second analysis reveals the presence of cataract and the very first post-surgery visit as factors influencing patients to come early. Our third analysis reveals that a higher proportion of delayed visits had resulted in worsening of vision in the glaucoma-affected eye. CONCLUSION: Our results suggest that active counselling by doctors, especially for routine follow-up visits, can help in better follow-up adherence and prevention of glaucoma-related visual impairment.

Bridging the Camera Domain Gap With Image-to-Image Translation Improves Glaucoma Diagnosis.

Purpose: The purpose of this study was to improve the automated diagnosis of glaucomatous optic neuropathy (GON), we propose a generative adversarial network (GAN) model that translates Optain images to Topcon images. Methods: We trained the GAN model on 725 paired images from Topcon and Optain cameras and externally validated it using an additional 843 paired images collected from the Aravind Eye Hospital in India. An optic disc segmentation model was used to assess the disparities in disc parameters across cameras. The performance of the translated images was evaluated using root mean square error (RMSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), 95% limits of agreement (LOA), Pearson's correlations, and Cohen's Kappa coefficient. The evaluation compared the performance of the GON model on Topcon photographs as a reference to that of Optain photographs and GAN-translated photographs. Results: The GAN model significantly reduced Optain false positive results for GON diagnosis, with RMSE, PSNR, and SSIM of GAN images being 0.067, 14.31, and 0.64, respectively, the mean difference of VCDR and cup-to-disc area ratio between Topcon and GAN images being 0.03, 95% LOA ranging from -0.09 to 0.15 and -0.05 to 0.10. Pearson correlation coefficients increased from 0.61 to 0.85 in VCDR and 0.70 to 0.89 in cup-to-disc area ratio, whereas Cohen's Kappa improved from 0.32 to 0.60 after GAN translation. Conclusions: Image-to-image translation across cameras can be achieved by using GAN to solve the problem of disc overexposure in Optain cameras. Translational Relevance: Our approach enhances the generalizability of deep learning diagnostic models, ensuring their performance on cameras that are outside of the original training data set.

The case for investment in eye health: systematic review and economic modelling analysis.

Objective: To assess how the returns on investment from correcting refractive errors and cataracts in low- and middle-income countries compare with the returns from other global development interventions. Methods: We adopted two complementary approaches to estimate benefit-cost ratios from eye health investment. First, we systematically searched PubMed® and Web of Science™ on 14 August 2023 for studies conducted in low-and-middle-income countries, which have measured welfare impacts associated with correcting refractive errors and cataracts. Using benefit-cost analysis, we compared these impacts to costs. Second, we employed an economic modelling analysis to estimate benefit-cost ratios from eye health investments in India. We compared the returns from eye health to returns in other domains across global health and development. Findings: We identified 21 studies from 10 countries. Thirteen outcomes highlighted impacts from refractive error correction for school students. From the systematic review, we used 17 out of 33 outcomes for benefit-cost analyses, with the median benefit-cost ratio being 36. The economic modelling approach for India generated benefit-cost ratios ranging from 28 for vision centres to 42 for school eye screening, with an aggregate ratio of 31. Comparing our findings to the typical investment in global development shows that eye health investment returns six times more benefits (median benefit-cost ratio: 36 vs 6). Conclusion: Eye health investments provide economic benefits with varying degrees based on the intervention type and location. Our findings underline the importance of incorporating eye health initiatives into broader development strategies for substantial societal returns.

Cataract surgery workload estimates in Theni district, India.

BACKGROUND/AIMS: To estimate the annual cataract surgery workload in Theni district, Tamil Nadu, India based on current utilisation of cataract services, prevalence of blindness and vision impairment (VI), and cataract burden-reduction goals. METHODS: We conducted a population-based longitudinal study between January 2016 and April 2018. We recruited 24 327 participants based on a random cluster sampling method; 7127 participants were ≥40 years. During the year following initial enrolment, we tracked utilisation of eye care services; and at the end of the 1-year period, we conducted a detailed eye examination of participants age ≥40. RESULTS: In the sample age ≥40 years, 13.0% had a visually significant cataract, and 17.8% had prior cataract surgery in at least one eye. The prevalence of cataract blindness based on presenting visual acuity in the better eye (PVABE)<3/60 was 0.34% and VI (PVABE<6/12) was 9.92%. 3.10% of the study population had obtained cataract surgery during 1 year, resulting in a cataract surgical rate of 9085. We estimated the effective cataract surgical coverage (eCSC) to be 54.5% and the CSC to be 75.7%, implying a sizeable quality gap. Prevalence, utilisation and coverage varied by age and gender. We estimated that a goal of eliminating the backlog of VI (PVABE<6/12) in 5 years would increase the annual cataract surgery workload by 11.5% from the current level. CONCLUSIONS: Our estimates of cataract surgery workloads under different scenarios can provide a useful input into planning of eye health services in Theni district.

Accuracy of an artificial intelligence-based mobile application for detecting cataracts: Results from a field study.

Purpose: To assess the accuracy of e-Paarvai, an artificial intelligence-based smartphone application (app) that detects and grades cataracts using images taken with a smartphone by comparing with slit lamp-based diagnoses by trained ophthalmologists. Methods: In this prospective diagnostic study conducted between January and April 2022 at a large tertiary-care eye hospital in South India, two screeners were trained to use the app. Patients aged >40 years and with a best-corrected visual acuity <20/40 were recruited for the study. The app is intended to determine whether the eye has immature cataract, mature cataract, posterior chamber intra-ocular lens, or no cataract. The diagnosis of the app was compared with that of trained ophthalmologists based on slit-lamp examinations, the gold standard, and a receiver operating characteristic (ROC) curve was estimated. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were computed. Results: The two screeners used the app to screen 2,619 eyes of 1,407 patients. In detecting cataracts, the app showed high sensitivity (96%) but low specificity (25%), an overall accuracy of 88%, a PPV of 92.3%, and an NPV of 57.8%. In terms of cataract grading, the accuracy of the app was high in detecting immature cataracts (1,875 eyes, 94.2%), but its accuracy was poor in detecting mature cataracts (73 eyes, 22%), posterior chamber intra-ocular lenses (55 eyes, 29.3%), and clear lenses (2 eyes, 2%). We found that the area under the curve in predicting ophthalmologists' cataract diagnosis could potentially be improved beyond the app's diagnosis based on using images only by incorporating information about patient sex and age (P < 0.0001) and best-corrected visual acuity (P < 0.0001). Conclusions: Although there is room for improvement, e-Paarvai app is a promising approach for diagnosing cataracts in difficult-to-reach populations. Integrating this with existing outreach programs can enhance the case detection rate.

Methods for a population-based Comprehensive Eye care Workload Assessment (CEWA) study in Southern India.

Eye care programs, in developing countries, are often planned using the prevalence of blindness and visual impairment, often estimated from Rapid Assessment of Avoidable Blindness (RAAB) surveys. A limitation of this planning approach is that it ignores the annual overall eye care requirements for a given population. Moreover, targets set are arbitrary, often influenced by capacity rather than need. To address this lacunae, we implemented a novel study design to estimate the annual need for comprehensive eye care in a 1.2 million populations. We conducted a population-based longitudinal study in Theni district, Tamil Nadu, India. All permanent residents of all ages were included. We conducted the study in three phases, (i) household-level enumeration and enrollment, (ii) basic eye examination (BEE) at household one-year post-enrollment, and (iii) assessment of eye care utilization and full eye examination (FEE) at central locations. All people aged 40 years and above were invited to the FEE. Those aged <40 years were invited to the FEE if indicated. In the main study, we enrolled 24,327 subjects (58% aged below 40 years and 42% aged 40 years and above). Of those less than 40 years, 72% completed the BEE, of whom 20% were referred for FEE at central location. Of the people aged ≥40 years, 70% underwent FEE. Our study design provides insights for appropriate long-term public health intervention planning, resource allocation, effective service delivery, and designing of eye care services for resource-limited settings.

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

INTRODUCTION: Infant and neonatal mortality estimates are typically derived from retrospective birth histories collected through surveys in countries with unreliable civil registration and vital statistics systems. Yet such data are subject to biases, including under-reporting of deaths and age misreporting, which impact mortality estimates. Prospective population-based cohort studies are an underutilized data source for mortality estimation that may offer strengths that avoid biases. METHODS: We conducted a secondary analysis of data from the Child Health Epidemiology Reference Group, including 11 population-based pregnancy or birth cohort studies, to evaluate the appropriateness of vital event data for mortality estimation. Analyses were descriptive, summarizing study designs, populations, protocols, and internal checks to assess their impact on data quality. We calculated infant and neonatal morality rates and compared patterns with Demographic and Health Survey (DHS) data. RESULTS: Studies yielded 71,760 pregnant women and 85,095 live births. Specific field protocols, especially pregnancy enrollment, limited exclusion criteria, and frequent follow-up visits after delivery, led to higher birth outcome ascertainment and fewer missing deaths. Most studies had low follow-up loss in pregnancy and the first month with little evidence of date heaping. Among studies in Asia and Latin America, neonatal mortality rates (NMR) were similar to DHS, while several studies in Sub-Saharan Africa had lower NMRs than DHS. Infant mortality varied by study and region between sources. CONCLUSIONS: Prospective, population-based cohort studies following rigorous protocols can yield high-quality vital event data to improve characterization of detailed mortality patterns of infants in low- and middle-income countries, especially in the early neonatal period where mortality risk is highest and changes rapidly.

Impact of practicing internal benchmarking on continuous improvement of cataract surgery outcomes: a retrospective observational study at Aravind Eye Hospitals, India.

OBJECTIVE: We aim to assess the effectiveness of a cataract surgery outcome monitoring tool used for continuous quality improvement. The objectives are to study: (1) the quality parameters, (2) the monitoring process followed and (3) the impact on outcomes. DESIGN AND PROCEDURES: In this retrospective observational study we evaluated a quality improvement (QI) method which has been practiced at the focal institution since 2012: internal benchmarking of cataract surgery outcomes (CATQA). We evaluated quality parameters, procedures followed and clinical outcomes. We created tables and line charts to examine trends in key outcomes. SETTING: Aravind Eye Care System, India. PARTICIPANTS: Phacoemulsification surgeries performed on 718 120 eyes at 10 centres (five tertiary and five secondary eye centres) from 2012 to 2020 were included. INTERVENTIONS: An internal benchmarking of surgery outcome parameters, to assess variations among the hospitals and compare with the best hospital. OUTCOME MEASURES: Intraoperative complications, unaided visual acuity (VA) at postoperative follow-up visit and residual postoperative refractive error (within ±0.5D). RESULTS: Over the study period the intraoperative complication rate decreased from 1.2% to 0.6%, surgeries with uncorrected VA of 6/12 or better increased from 80.8% to 89.8%, and surgeries with postoperative refractive error within ±0.5D increased from 76.3% to 87.3%. Variability in outcome measures across hospitals declined. Additionally, benchmarking was associated with improvements in facilities, protocols and processes. CONCLUSION: Internal benchmarking was found to be an effective QI method that enabled the practice of evidence-based management and allowed for harnessing the available information. Continuous improvement in clinical outcomes requires systematic and regular review of results, identifying gaps between hospitals, comparisons with the best hospital and implementing lessons learnt from peers.

Neonatal mortality risk of vulnerable newborns: A descriptive analysis of subnational, population-based birth cohorts for 238 203 live births in low- and middle-income settings from 2000 to 2017.

OBJECTIVE: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low- and middle-income countries (LMICs). DESIGN: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000. SETTING: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION: Live birth neonates. METHODS: We categorically defined five vulnerable newborn types based on size (large- or appropriate- or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies. MAIN OUTCOME MEASURES: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. RESULTS: There were 238 203 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.6, interquartile range [IQR] 2.0-2.9), PT + LGA (median RR 7.3, IQR 2.3-10.4), PT + AGA (median RR 6.0, IQR 4.4-13.2) and PT + SGA (median RR 10.4, IQR 8.6-13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies. CONCLUSIONS: Small and/or preterm babies in LIMCs have a considerably increased mortality risk compared with babies born at term and larger. This classification system may advance the understanding of the social determinants and biomedical risk factors along with improved treatment that is critical for newborn health.

Cataract services for all: Strategies for equitable access from a global modified Delphi process.

Vision loss from cataract is unequally distributed, and there is very little evidence on how to overcome this inequity. This project aimed to engage multiple stakeholder groups to identify and prioritise (1) delivery strategies that improve access to cataract services for under-served groups and (2) population groups to target with these strategies across world regions. We recruited panellists knowledgeable about cataract services from eight world regions to complete a two-round online modified Delphi process. In Round 1, panellists answered open-ended questions about strategies to improve access to screening and surgery for cataract, and which population groups to target with these strategies. In Round 2, panellists ranked the strategies and groups to arrive at the final lists regionally and globally. 183 people completed both rounds (46% women). In total, 22 distinct population groups were identified. At the global level the priority groups for improving access to cataract services were people in rural/remote areas, with low socioeconomic status and low social support. South Asia and Sub-Saharan Africa were the only regions in which panellists ranked women in the top 5 priority groups. Panellists identified 16 and 19 discreet strategies to improve access to screening and surgical services, respectively. These mostly addressed health system/supply side factors, including policy, human resources, financing and service delivery. We believe these results can serve eye health decision-makers, researchers and funders as a starting point for coordinated action to improve access to cataract services, particularly among population groups who have historically been left behind.

Managing Outpatient Cycle Times in Hospitals Using Integrated Closed-Loop Approaches.

Long waiting times in outpatient clinics have multiple adverse effects on patients and their attendants, staff and hospital management. Several approaches practiced to manage the cycle time have been proposed. The purpose of this study was to evaluate the impact of implementing closed-loop based multiple approaches together. This study was conducted in Aravind Eye Hospital (AEH), Madurai, India where several approaches to manage cycle times have been implemented over the years. Scheduling system was introduced to manage COVID-19 specific norms. We compared the cycle times in general outpatient clinics in a regime in which multiple approaches were practiced together before and after introducing scheduling to regimes in which individual approaches were practiced. We analysed how the cycle time varied by patient load. Cycle time for all patient days when the combined approach was used was 19% lower than baseline, and better than under each of the individual approaches. The outcome sustained even during the COVID-19 pandemic that necessitated additional processes and procedures. Therefore, implementing multiple approaches can be more effective to reduce the cycle time than implementing individual approaches.