Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care.

PURPOSE: Retinal screening examinations can prevent vision loss resulting from diabetes but are costly and highly underused. We hypothesized that artificial intelligence-assisted nonmydriatic point-of-care screening administered during primary care visits would increase the adherence to recommendations for follow-up eye care in patients with diabetes. DESIGN: Prospective cohort study. PARTICIPANTS: Adults 18 years of age or older with a clinical diagnosis of diabetes being cared for in a metropolitan primary care practice for low-income patients. METHODS: All participants underwent nonmydriatic fundus photography followed by automated retinal image analysis with human supervision. Patients with positive or inconclusive screening results were referred for comprehensive ophthalmic evaluation. Adherence to referral recommendations was recorded and compared with the historical adherence rate from the same clinic. MAIN OUTCOME MEASURE: Rate of adherence to eye screening recommendations. RESULTS: By automated screening, 8.3% of the 180 study participants had referable diabetic eye disease, 13.3% had vision-threatening disease, and 29.4% showed inconclusive results. The remaining 48.9% showed negative screening results, confirmed by human overread, and were not referred for follow-up ophthalmic evaluation. Overall, the automated platform showed a sensitivity of 100% (confidence interval, 92.3%-100%) in detecting an abnormal screening results, whereas its specificity was 65.7% (confidence interval, 57.0%-73.7%). Among patients referred for follow-up ophthalmic evaluation, the adherence rate was 55.4% at 1 year compared with the historical adherence rate of 18.7% (P < 0.0001, Fisher exact test). CONCLUSIONS: Implementation of an automated diabetic retinopathy screening system in a primary care clinic serving a low-income metropolitan patient population improved adherence to follow-up eye care recommendations while reducing referrals for patients with low-risk features.

Factors Associated with Adherence to Screening Guidelines for Diabetic Retinopathy Among Low-Income Metropolitan Patients.

In this retrospective analysis of patients with diabetes in an academic primary care clinic in St. Louis, attendance at ophthalmic screening appointments was recorded over a two-year observation window. Factors associated with adherence were analyzed by multivariable regression. Among 974 total patients included, only 330 (33.9%) were adherent within a two-year period. Multivariate analyses identified older age, female gender, primary language other than English, and attendance at ancillary diabetes clinic visits as factors associated with improved diabetic retinopathy screening adherence. Factors not associated with adherence included race and insurance status.

Predictors of 30-day readmission after aneurysmal subarachnoid hemorrhage: a case-control study.

OBJECTIVE Despite persisting questions regarding its appropriateness, 30-day readmission is an increasingly common quality metric used to influence hospital compensation in the United States. However, there is currently insufficient evidence to identify which patients are at highest risk for readmission after aneurysmal subarachnoid hemorrhage (SAH). The objective of this study was to identify predictors of 30-day readmission after SAH, to focus preventative efforts, and to provide guidance to funding agencies seeking to risk-adjust comparisons among hospitals. METHODS The authors performed a case-control study of 30-day readmission among aneurysmal SAH patients treated at a single center between 2003 and 2013. To control for geographic distance from the hospital and year of treatment, the authors randomly matched each case (30-day readmission) with approximately 2 SAH controls (no readmission) based on home ZIP code and treatment year. They evaluated variables related to patient demographics, socioeconomic characteristics, comorbidities, presentation severity (e.g., Hunt and Hess grade), and clinical course (e.g., need for gastrostomy or tracheostomy, length of stay). Conditional logistic regression was used to identify significant predictors, accounting for the matched design of the study. RESULTS Among 82 SAH patients with unplanned 30-day readmission, the authors matched 78 patients with 153 nonreadmitted controls. Age, demographics, and socioeconomic factors were not associated with readmission. In univariate analysis, multiple variables were significantly associated with readmission, including Hunt and Hess grade (OR 3.0 for Grade IV/V vs I/II), need for gastrostomy placement (OR 2.0), length of hospital stay (OR 1.03 per day), discharge disposition (OR 3.2 for skilled nursing vs other disposition), and Charlson Comorbidity Index (OR 2.3 for score ≥ 2 vs 0). However, the only significant predictor in the multivariate analysis was discharge to a skilled nursing facility (OR 3.2), and the final model was sensitive to criteria used to enter and retain variables. Furthermore, despite the significant association between discharge disposition and readmission, less than 25% of readmitted patients were discharged to a skilled nursing facility. CONCLUSIONS Although discharge disposition remained significant in multivariate analysis, most routinely collected variables appeared to be weak independent predictors of 30-day readmission after SAH. Consequently, hospitals interested in decreasing readmission rates may consider multifaceted, cost-efficient interventions that can be broadly applied to most if not all SAH patients.