Systemic and ocular outcomes in patients with young-onset type 2 diabetes.

PURPOSE: To analyze the systemic and ocular outcomes in patients with young-onset type 2 diabetes (YO-DM2) based on grade of presenting diabetic retinopathy (DR). METHODS: Retrospective cohort study analysis of empaneled patients with type 2 diabetes <40 years old with retinopathy screening within the Los Angeles Department of Health Services between 01/01/2017-07/01/2021 were included. Patients were stratified based on presenting severity of DR determined on fundus photographs or clinical examination. Patient's systemic co-morbidities and ocular outcomes were then compared across each group. Procedural (e.g. intravitreal injections) and surgical interventions (e.g. pars plana vitrectomy) were documented as performed by the treating physician. RESULTS: 2795 patients were screened from 12,456 patients diagnosed with diabetes younger than age 40 (22.4 %). Of these, 1496 patients were diagnosed with type 2 DM. 1084 (72.4 %) of patients presented without DR, 307 (20.5 %) presented with non-proliferative diabetic retinopathy (NPDR), and 105 (7.0 %) of patients presented with proliferative diabetic retinopathy (PDR). Increasing presenting diabetic retinopathy severity was associated with longer duration of diabetes, greater systemic comorbidities (e.g. diabetic foot disease, neuropathy, chronic kidney or end stage renal disease), worse baseline and final visual acuity, and required more procedural and surgical interventions. CONCLUSIONS: Worse presenting DR severity in patients young-onset type 2 diabetes was associated with greater comorbid systemic and ocular disease with worse visual acuity outcomes. <1 % of patients without diabetic retinopathy or with mild NPDR were likely to progress to PDR. Diabetic kidney disease was an independent risk factor for developing neovascular glaucoma and retinal detachments. Prompt evaluation and intervention in patients with YO-DM2 may help reduce the associated systemic and ocular morbidity.

Disparities in COVID-19 Disease Incidence by Income and Vaccination Coverage - 81 Communities, Los Angeles, California, July 2020-September 2021.

COVID-19 has disproportionately affected socially vulnerable communities characterized by lower income, lower education attainment, and higher proportions of minority populations, among other factors (1-4). Disparities in COVID-19 incidence and the impact of vaccination on incidence disparities by community income were assessed among 81 communities in Los Angeles, California. Median community vaccination coverage and COVID-19 incidence were calculated across household income strata using a generalized linear mixed effects model with Poisson distribution during three COVID-19 surge periods: two before vaccine availability (July 2020 and January 2021) and the third after vaccines became widely available in April 2021 (September 2021). Adjusted incidence rate ratios (aIRRs) during the peak month of each surge were compared across communities grouped by median household income percentile. The aIRR between communities in the lowest and highest median income deciles was 6.6 (95% CI = 2.8-15.3) in July 2020 and 4.3 (95% CI = 1.8-9.9) in January 2021. However, during the September 2021 surge that occurred after vaccines became widely availabile, model estimates did not identify an incidence disparity between the highest- and lowest-income communities (aIRR = 0.80; 95% CI = 0.35-1.86). During this surge, vaccination coverage was lowest (59.4%) in lowest-income communities and highest (71.5%) in highest-income communities (p<0.001). However, a significant interaction between income and vaccination on COVID-19 incidence (p<0.001) indicated that the largest effect of vaccination on disease incidence occured in the lowest-income communities. A 20% increase in community vaccination was estimated to have resulted in an additional 8.1% reduction in COVID-19 incidence in the lowest-income communities compared with that in the highest-income communities. These findings highlight the importance of improving access to vaccination and reducing vaccine hesitancy in underserved communities in reducing disparities in COVID-19 incidence.

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study.

BACKGROUND: Photographs of the external eye were recently shown to reveal signs of diabetic retinal disease and elevated glycated haemoglobin. This study aimed to test the hypothesis that external eye photographs contain information about additional systemic medical conditions. METHODS: We developed a deep learning system (DLS) that takes external eye photographs as input and predicts systemic parameters, such as those related to the liver (albumin, aspartate aminotransferase [AST]); kidney (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [ACR]); bone or mineral (calcium); thyroid (thyroid stimulating hormone); and blood (haemoglobin, white blood cells [WBC], platelets). This DLS was trained using 123 130 images from 38 398 patients with diabetes undergoing diabetic eye screening in 11 sites across Los Angeles county, CA, USA. Evaluation focused on nine prespecified systemic parameters and leveraged three validation sets (A, B, C) spanning 25 510 patients with and without diabetes undergoing eye screening in three independent sites in Los Angeles county, CA, and the greater Atlanta area, GA, USA. We compared performance against baseline models incorporating available clinicodemographic variables (eg, age, sex, race and ethnicity, years with diabetes). FINDINGS: Relative to the baseline, the DLS achieved statistically significant superior performance at detecting AST >36·0 U/L, calcium <8·6 mg/dL, eGFR <60·0 mL/min/1·73 m2, haemoglobin <11·0 g/dL, platelets <150·0 × 103/µL, ACR ≥300 mg/g, and WBC <4·0 × 103/µL on validation set A (a population resembling the development datasets), with the area under the receiver operating characteristic curve (AUC) of the DLS exceeding that of the baseline by 5·3-19·9% (absolute differences in AUC). On validation sets B and C, with substantial patient population differences compared with the development datasets, the DLS outperformed the baseline for ACR ≥300·0 mg/g and haemoglobin <11·0 g/dL by 7·3-13·2%. INTERPRETATION: We found further evidence that external eye photographs contain biomarkers spanning multiple organ systems. Such biomarkers could enable accessible and non-invasive screening of disease. Further work is needed to understand the translational implications. FUNDING: Google.

Effectiveness of Glaucoma Screening and Factors Associated with Follow-up Adherence among Glaucoma Suspects in a Safety-Net Teleretinal Screening Program.

PURPOSE: To evaluate rates and risk factors associated with follow-up adherence to in-person glaucoma evaluations and confirmed glaucoma diagnosis in glaucoma suspects identified through teleretinal diabetic retinopathy screening (TDRS). DESIGN: Retrospective cohort study SUBJECTS: Patients with diabetes identified through teleretinal screening to have large or asymmetric cup-to-disc ratios in a Los Angeles County safety-net primary care-based TDRS program. METHODS: Retrospective chart review was performed to obtain demographic and clinical information for patients with cup-to-disc ratios concerning for glaucoma on TDRS. Patients who completed an in-person follow-up appointment within 1 year of teleretinal screening were adherent. Factors associated with follow-up adherence and diagnosis of glaucoma were analyzed with chi-square and independent t tests along with multivariable logistic regressions. MAIN OUTCOME MEASURES: The proportion of patients with suspected glaucoma who adhered with in-person follow-up examination, proportion of patients with confirmed glaucoma diagnosis, and factors associated with follow-up adherence and glaucoma diagnosis. RESULTS: Eight-hundred seventeen patients with optic discs suspicious for glaucoma were included. Five-hundred thirty-four (65.4%) patients successfully completed an in-person glaucoma evaluation. Among these patients, 62.9% and 24.5% received a diagnosis of glaucoma suspect and glaucomatous optic neuropathy, respectively. Compared with patients aged < 50 years, patients aged 50 to 64 years had 1.57 times higher odds of being adherent with in-person visits (P = 0.036), whereas no difference was seen in those aged ≥ 65 years. For every $10 000 increase in the zip code median income, patients had 11% lower odds of being adherent (P = 0.031). Compared with Latino patients, Black patients had 3.52 times (P < 0.001) higher odds of having confirmed glaucoma. CONCLUSION: The majority of patients referred as glaucoma suspects on TDRS completed a follow-up examination, and nearly a quarter of those examined received a confirmed glaucoma diagnosis. Patients aged ≥ 50 and < 65 years along with those from lower-income neighborhoods were more likely to follow up for an in-person evaluation. Compared with Latino patients, Black patients had a higher risk for a confirmed glaucoma diagnosis. This demonstrates the effectiveness of glaucoma detection in a large-scale TDRS program for a safety-net patient population. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any materials discussed in this article.

Implementation of a pilot teleretinal screening protocol for hydroxychloroquine retinopathy in a Los Angeles County safety net clinic.

INTRODUCTION: This study aimed to determine whether teleretinal screening for hydroxychloroquine retinopathy (HCQR) improves clinical efficiency and adherence to recommended screening guidelines compared to face-to-face screening among patients in a large safety net medical system. METHODS: In this retrospective cohort study of a consecutive sample of 590 adult patients with active HCQ prescriptions seen in the outpatient ophthalmology clinic at Los Angeles County + University of Southern California Medical Center from 1 September 2018 to 25 November 2019, 203 patients underwent technician-only tele-HCQR screening (THRS), and 387 patients underwent screening with traditional face-to-face visits (F2FV) with an eye-care provider. Data on clinic efficiency measures (appointment wait time and encounter duration) and adherence to recommended screening guidelines were collected and compared between the two cohorts. RESULTS: Compared to F2FV, the THRS cohort experienced significantly shorter median (interquartile range) time to appointment (2.5 (1.5-4.6) vs. 5.1 (2.9-8.4) months; p < 0.0001), shorter median encounter duration (1 (0.8-1.4) vs. 3.7 (2.5-5.2) hours; p < 0.0001) and higher proportion of complete baseline screening (102/104 (98.1%) vs. 68/141 (48.2%); p < 0.001) and complete chronic screening (98/99 (99%) vs. 144/246 (58.5%); p < 0.001). DISCUSSION: A pilot THRS protocol was successfully implemented at a major safety net eye clinic in Los Angeles County, resulting in a 50.9% reduction in wait times for screening, 72.9% reduction in encounter duration and 49.9% and 40.5% increases in proportions of complete baseline and chronic screening, respectively. Tele-HCQ retinal screening protocols may improve timeliness to care and screening adherence for HCQR in the safety net setting.

Capillary density and caliber as assessed by optical coherence tomography angiography may be significant predictors of diabetic retinopathy severity.

PURPOSE: To validate retinal capillary density and caliber associations with diabetic retinopathy (DR) severity in different clinical settings. METHODS: This cross-sectional study assessed retinal capillary density and caliber in the superficial retinal layer of 3-mm OCTA scans centered on the fovea. Images were collected from non-diabetic controls and subjects with mild or referable DR (defined DR worse than mild DR) between February 2016 and December 2019 at secondary and tertiary eye care centers. Vessel Skeleton Density (VSD), a measure of capillary density, and Vessel Diameter Index (VDI), a measure of vascular caliber, were calculated from these images. Discriminatory performance of VSD and VDI was evaluated using multivariable logistic regression models predicting DR severity with adjustments for sex, hypertension, and hyperlipidemia. Area under the curve (AUC) was estimated. Model performance was evaluated in two different cohorts. RESULTS: This study included 594 eyes from 385 subjects. Cohort 1 was a training cohort of 509 eyes including 159 control, 155 mild non-proliferative DR (NPDR) and 195 referable DR eyes. Cohort 2 was a validation cohort consisting of 85 eyes including 16 mild NPDR and 69 referable DR eyes. In Cohort 1, addition of VSD and VDI to a model using only demographic data significantly improved the model's AUC for discrimination of eyes with any DR severity from controls (0.91 [95% CI, 0.88-0.93] versus 0.80 [95% CI, 0.76-0.83], p < 0.001) and eyes with referable DR from mild NPDR (0.90 [95% CI, 0.86-0.93] versus 0.69 [95% CI, 0.64-0.75], p < 0.001). The transportability of this regression model was excellent when implemented in Cohort 2 for the referable DR versus mild NPDR comparison. The odds ratio of having any DR compared to control subjects, and referable DR compared to mild DR decreased by 15% (95% CI: 12-18%), and 13% (95% CI: 10-15%), respectively, for every 0.001 unit increase in VSD after adjusting for comorbidities. CONCLUSION: OCTA-derived capillary density has real world clinical value for rapidly assessing DR severity.

DRRisk: A Web-based tool to Assess the Risk of Diabetic Retinopathy through Machine Learning on Electronic Health Records.

Objective: We developed a web-based tool for diabetic retinopathy (DR) risk assessment called DRRisk (https://drandml.cdrewu.edu/) using machine learning on electronic health record (EHR) data, with a goal of preventing vision loss in persons with diabetes, especially in underserved settings. Methods: DRRisk uses Python's Flask framework. Its user-interface is implemented using HTML, CSS and Javascript. Clinical experts were consulted on the tool's design. Results: DRRisk assesses current DR risk for people with diabetes, categorizing their risk level as low, moderate, or high, depending on the percentage of DR risk assigned by the underlying machine learning model. Discussion: A goal of our tool is to help providers prioritize patients at high risk for DR in order to prevent blindness. Conclusion: Our tool uses DR risk factors from EHR data to calculate a diabetic person's current DR risk. It may be useful for identifying unscreened diabetic patients who have undiagnosed DR.

Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system.

OBJECTIVE: Clinical guidelines recommend annual eye examinations to detect diabetic retinopathy (DR) in patients with diabetes. However, timely DR detection remains a problem in medically underserved and under-resourced settings in the United States. Machine learning that identifies patients with latent/undiagnosed DR could help to address this problem. MATERIALS AND METHODS: Using electronic health record data from 40 631 unique diabetic patients seen at Los Angeles County Department of Health Services healthcare facilities between January 1, 2015 and December 31, 2017, we compared ten machine learning environments, including five classifier models, for assessing the presence or absence of DR. We also used data from a distinct set of 9300 diabetic patients seen between January 1, 2018 and December 31, 2018 as an external validation set. RESULTS: Following feature subset selection, the classifier with the best AUC on the external validation set was a deep neural network using majority class undersampling, with an AUC of 0.8, the sensitivity of 72.17%, and specificity of 74.2%. DISCUSSION: A deep neural network produced the best AUCs and sensitivity results on the test set and external validation set. Models are intended to be used to screen guideline noncompliant diabetic patients in an urban safety-net setting. CONCLUSION: Machine learning on diabetic patients' routinely collected clinical data could help clinicians in safety-net settings to identify and target unscreened diabetic patients who potentially have undiagnosed DR.

The Utility of Recycled Eyeglasses: A Pilot Study at the Los Angeles County Department of Health Services.

Background: The cost of eyeglasses is variably covered by medical insurance and thus is a significant barrier for patients in lower socioeconomic classes. We evaluated the efficacy of Recycle Vision (RV) at LAC+USC Medical Center, a monthly clinic run by volunteer medical students that provides free donated eyeglasses. Methods: A convenience sample of 30 patients was surveyed from August 1, 2019 to December 31, 2019. Patients' prescriptions were matched with available eyeglasses based on spherical equivalent and axis of astigmatism using Winglasses software algorithm; patients selected glasses from these options based on subjective improvement of vision. All participants consented to a phone follow-up survey 1 month after initial visit to gauge satisfaction with glasses and rate difficulty in completing daily activities pre- and post-RV visit on a scale of 1 to 5 (5 being the greatest), with a 100% response rate. Results: Of the 30 study participants, 90% received eyeglasses from RV, with reported improvement in ease of daily activities of 3.96. 67% of respondents stated that if RV clinic did not exist, they would not have obtained glasses elsewhere; cost was the most commonly (70%) cited barrier. Upon follow-up, average likelihood of patients referring friends/family to RV was 4.07 (SD 1.14). Conclusion: The majority of RV patients received free eyeglasses and had subsequent improvement in their quality of life. This pilot study demonstrates that programs offering free eyeglasses can effectively correct refractive error and can offer a practical public health solution to improve functionality for underserved populations.

Evaluation of an Intervention to Reduce Low-Value Preoperative Care for Patients Undergoing Cataract Surgery at a Safety-Net Health System.

Importance: Preoperative testing for cataract surgery epitomizes low-value care and still occurs frequently, even at one of the nation's largest safety-net health systems. Objective: To evaluate a multipronged intervention to reduce low-value preoperative care for patients undergoing cataract surgery and analyze costs from various fiscal perspectives. Design, Setting, and Participants: This study took place at 2 academic safety-net medical centers, Los Angeles County and University of Southern California (LAC-USC) (intervention, n = 469) and Harbor-UCLA (University of California, Los Angeles) (control, n = 585), from April 13, 2015, through April 12, 2016, with 12 additional months (April 13, 2016, through April 13, 2017) to assess sustainability (intervention, n = 1002; control, n = 511). To compare pre- and postintervention vs control group utilization and cost changes, logistic regression assessing time-by-group interactions was used. Interventions: Using plan-do-study-act cycles, a quality improvement nurse reviewed medical records and engaged the anesthesiology and ophthalmology chiefs with data on overuse; all 3 educated staff and trainees on reducing routine preoperative care. Main Outcomes and Measures: Percentage of patients undergoing cataract surgery with preoperative medical visits, chest x-rays, laboratory tests, and electrocardiograms. Costs were estimated from LAC-USC's financially capitated perspective, and costs were simulated from fee-for-service (FFS) health system and societal perspectives. Results: Of 1054 patients, 546 (51.8%) were female (mean [SD] age, 60.6 [11.1] years). Preoperative visits decreased from 93% to 24% in the intervention group and increased from 89% to 91% in the control group (between-group difference, -71%; 95% CI, -80% to -62%). Chest x-rays decreased from 90% to 24% in the intervention group and increased from 75% to 83% in the control group (between-group difference, -75%; 95% CI, -86% to -65%). Laboratory tests decreased from 92% to 37% in the intervention group and decreased from 98% to 97% in the control group (between-group difference, -56%; 95% CI, -64% to -48%). Electrocardiograms decreased from 95% to 29% in the intervention group and increased from 86% to 94% in the control group (between-group difference, -74%; 95% CI, -83% to -65%). During 12-month follow-up, visits increased in the intervention group to 67%, but chest x-rays (12%), laboratory tests (28%), and electrocardiograms (11%) remained low (P < .001 for all time-group interactions in both periods). At LAC-USC, losses of $42 241 in year 1 were attributable to intervention costs, and 3-year projections estimated $67 241 in savings. In a simulation of a FFS health system at 3 years, $88 151 in losses were estimated, and for societal 3-year perspectives, $217 322 in savings were estimated. Conclusions and Relevance: This intervention was associated with sustained reductions in low-value preoperative testing among patients undergoing cataract surgery and modest cost savings for the health system. The findings suggest that reducing low-value care may be associated with cost savings for financially capitated health systems and society but also with losses for FFS health systems, highlighting a potential barrier to eliminating low-value care.

Implementation and Evaluation of a Large-Scale Teleretinal Diabetic Retinopathy Screening Program in the Los Angeles County Department of Health Services.

Importance: Diabetic retinopathy (DR) is the leading cause of blindness in adults of working age in the United States. In the Los Angeles County safety net, a nonvertically integrated system serving underinsured and uninsured patients, the prevalence of DR is approximately 50%, and owing to limited specialty care resources, the average wait times for screening for DR have been 8 months or more. Objective: To determine whether a primary care-based teleretinal DR screening (TDRS) program reduces wait times for screening and improves timeliness of needed care in the Los Angeles County safety net. Design, Setting, and Participants: Quasi-experimental, pretest-posttest evaluation of exposure to primary care-based TDRS at 5 of 15 Los Angeles County Department of Health Services safety net clinics from September 1, 2013, to December 31, 2015, with a subgroup analysis of random samples of 600 patients before and after the intervention (1200 total). Exposure: Primary care clinic-based teleretinal screening for DR. Main Outcomes and Measures: Annual rates of screening for DR before and after implementation of the TDRS program across the 5 clinics, time to screening for DR in a random sample of patients from these clinics, and a description of the larger framework of program implementation. Results: Among the 21 222 patients who underwent the screening (12 790 female, 8084 male, and 348 other gender or not specified; mean [SD] age, 57.4 [9.6] years), the median time to screening for DR decreased from 158 days (interquartile range, 68-324 days) before the intervention to 17 days (interquartile range, 8-50 days) after initiation of the program (P < .001). Overall annual screening rates for DR increased from 5942 of 14 633 patients (40.6%) before implementation to 7470 of 13 133 patients (56.9%) after initiation of the program at all 15 targeted clinics (odds ratio, 1.9; 95% CI, 1.3-2.9; P = .002). Of the 21 222 patients who were screened, 14 595 (68.8%) did not require referral to an eye care professional, 4160 (19.6%) were referred for treatment or monitoring of DR, and 2461 (11.6%) were referred for other ophthalmologic conditions. Conclusions and Relevance: A digital TDRS program was successfully implemented for the largest publicly operated county safety net population in the United States, resulting in the elimination of the need for more than 14 000 visits to specialty care professionals, a 16.3% increase in annual rates of screening for DR, and an 89.2% reduction in wait times for screening. Teleretinal DR screening programs have the potential to maximize access and efficiency in the safety net, where the need for such programs is most critical.

Fostering a Commitment to Quality: Best Practices in Safety-net Hospitals.

In 2007, the Martin Luther King, Jr.-Harbor Hospital (MLK-Harbor), which served a large safety-net population in South Los Angeles, closed due to quality challenges. Shortly thereafter, an agreement was made to establish a new hospital, Martin Luther King, Jr. Community Hospital (MLKCH), to serve the unmet needs of the community. To assist the newly appointed MLKCH Board of Directors in building a culture of quality, we conducted a series of interviews with five high-performing hospital systems. In this report, we describe our findings. The hospitals we interviewed achieved a culture of quality by: 1) developing guiding principles that foster quality; 2) hiring and retaining personnel who are stewards of quality; 3) promoting efficient resource utilization; 4) developing a well-organized quality improvement infrastructure; and 5) cultivating integrated, patient-centric care. The institutions highlighted in this report provide important lessons for MLKCH and other safety-net institutions.

Understanding the Knowledge Gap Experienced by U.S. Safety Net Patients in Teleretinal Screening.

Safety-net patients' socioeconomic barriers interact with limited digital and health literacies to produce a "knowledge gap" that impacts the delivery of healthcare via telehealth technologies. Six focus groups (2 African- American and 4 Latino) were conducted with patients who received teleretinal screening in a U.S. urban safety-net setting. Focus groups were analyzed using a modified grounded theory methodology. Findings indicate that patients' knowledge gap is primarily produced at three points during the delivery of care: (1) exacerbation of patients' pre-existing personal barriers in the clinical setting; (2) encounters with technology during screening; and (3) lack of follow up after the visit. This knowledge gap produces confusion, potentially limiting patients' perceptions of care and their ability to manage their own care. It may be ameliorated through delivery of patient education focused on both disease pathology and specific role of telehealth technologies in disease management.

Improving Accuracy of Grading and Referral of Diabetic Macular Edema Using Location and Extent of Hard Exudates in Retinal Photography.

BACKGROUND: Hard exudates (HE) are used as a surrogate marker for sight-threatening diabetic macular edema (DME) in most telemedicine-based screening programs in the world. This study investigates whether proximity of HE to the center of the macula, and extent of HE are associated with greater clinically significant macular edema (CSME) severity. A novel method for associating optical coherence tomography (OCT) scans with CSME was developed. METHODS: Eligible subjects were recruited from a DRS program in a community clinic in Oakland, California. Ocular fundus of each subject was imaged using 3-field 45-degree digital retinal photography and scanned using central 7-line spectral domain OCT. Two certified graders separated subjects into 2 groups, those with and without HE within 500 microns from the center of the macula. A modified DME severity scale, developed from Early Treatment Diabetic Retinopathy Study data and adapted to OCT thickness measurements, was used to stratify CSME into severe and nonsevere levels for all subjects. RESULTS: The probabilities of severe CSME in groups 1 and 2 were 14.4% (95% CI: 8.2%-23.8%) and 9% (95% CI: 2.4%-25.5%), respectively (P = .556). In post hoc analysis, increase in the number of sectors affected by HE within the central zone of the macula was associated with the increase in the probability of being diagnosed with severe CSME. CONCLUSION: We have proposed OCT-based classification of DME into severe and nonsevere CSME. Based on this limited analysis, severity of CSME is related more to extent of HE rather than proximity to the center of the macula.

Autonomy versus automation: perceptions of nonmydriatic camera choice for teleretinal screening in an urban safety net clinic.

OBJECTIVE: Teleretinal screening with nonmydriatic cameras has been presented as a means of increasing the number of patients assessed for diabetic retinopathy in urban safety net clinics. It has been hypothesized that automated nonmydriatic cameras may improve screening rates by reducing the learning curve for camera use. In this article, we examine the impact of introducing automated nonmydriatic cameras to urban safety net clinics whose photographers had previously used manual cameras. MATERIALS AND METHODS: We evaluated the impact of manual and automated digital nonmydriatic cameras on teleretinal screening using a quantitative analysis of readers' image quality ratings as well as a qualitative analysis, through in-depth interviews, of photographers' experiences. RESULTS: With the manual camera, 68% of images were rated "adequate" or better, including 24% rated "good" and 20% rated "excellent." With the automated camera, 61% were rated "adequate" or better, including 9% rated "good" and 0% rated "excellent." Photographers expressed frustration with their inability to control image-taking settings with the automated camera, which led to unexpected delays. CONCLUSIONS: For safety net clinics in which medical assistants are already trained to take photographs for diabetic retinopathy screening with a manual camera, the introduction of automated cameras may lead to frustration and paradoxically contribute to increased patient wait times. When photographers have achieved a high degree of aptitude with manual cameras and value the control they have over camera features, the introduction of automated cameras should be approached with caution and may require extensive training to increase user acceptability.