Background Self-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established. Objective This study aimed to estimate the diagnostic accuracy of self-reported vision loss measures compared to best-corrected visual acuity (BCVA), inform the design and selection of questions for future data collection, and identify the concordance between self-reported vision and measured acuity at the population level to support ongoing surveillance efforts. Methods We calculated accuracy and correlation between self-reported visual function versus BCVA at the individual and population level among patients from the University of Washington ophthalmology or optometry clinics with a prior eye examination, randomly oversampled for visual acuity loss or diagnosed eye diseases. Self-reported visual function was collected via telephone survey. BCVA was determined based on retrospective chart review. Diagnostic accuracy of questions at the person level was measured based on the area under the receiver operator curve (AUC), whereas population-level accuracy was determined based on correlation. Results The survey question, “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” had the highest accuracy for identifying patients with blindness (BCVA ≤20/200; AUC=0.797). The highest accuracy for detecting any vision loss (BCVA <20/40) was achieved by responses of “fair,” “poor,” or “very poor” to the question, “At the present time, would you say your eyesight, with glasses or contact lenses if you wear them, is excellent, good, fair, poor, or very poor” (AUC=0.716). At the population level, the relative relationship between prevalence based on survey questions and BCVA remained stable for most demographic groups, with the only exceptions being groups with small sample sizes, and these differences were generally not significant. Conclusions Although survey questions are not considered to be sufficiently accurate to be used as a diagnostic test at the individual level, we did find relatively high levels of accuracy for some questions. At the population level, we found that the relative prevalence of the 2 most accurate survey questions were highly correlated with the prevalence of measured visual acuity loss among nearly all demographic groups. The results of this study suggest that self-reported vision questions fielded in national surveys are likely to yield an accurate and stable signal of vision loss across different population groups, although the actual measure of prevalence from these questions is not directly analogous to that of BCVA.
ImportanceDiagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown.ObjectiveTo estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review.Design, Setting, and ParticipantsThis cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington–affiliated ophthalmology or optometry clinics from May 2018 to April 2020. Patients 16 years and older with an eye examination in the previous 2 years were included, oversampled for diagnosed major eye diseases and visual acuity loss.ExposuresPatients were assigned to vision and eye health condition categories based on diagnosis codes present in their billing claims history and EHR using the diagnostic case definitions of the US Centers for Disease Control and Prevention Vision and Eye Health Surveillance System (VEHSS) as well as clinical assessment based on retrospective medical record review.Main Outcome and MeasuresAccuracy was measured as area under the receiver operating characteristic curve (AUC) of claims and EHR-based diagnostic coding vs retrospective review of clinical assessments and treatment plans.ResultsAmong 669 participants (mean [range] age, 66.1 [16-99] years; 357 [53.4%] female), identification of diseases in billing claims and EHR data using VEHSS case definitions was accurate for diabetic retinopathy (claims AUC, 0.94; 95% CI, 0.91-0.98; EHR AUC, 0.97; 95% CI, 0.95-0.99), glaucoma (claims AUC, 0.90; 95% CI, 0.88-0.93; EHR AUC, 0.93; 95% CI, 0.90-0.95), age-related macular degeneration (claims AUC, 0.87; 95% CI, 0.83-0.92; EHR AUC, 0.96; 95% CI, 0.94-0.98), and cataracts (claims AUC, 0.82; 95% CI, 0.79-0.86; EHR AUC, 0.91; 95% CI, 0.89-0.93). However, several condition categories showed low validity with AUCs below 0.7, including diagnosed disorders of refraction and accommodation (claims AUC, 0.54; 95% CI, 0.49-0.60; EHR AUC, 0.61; 95% CI, 0.56-0.67), diagnosed blindness and low vision (claims AUC, 0.56; 95% CI, 0.53-0.58; EHR AUC, 0.57; 95% CI, 0.54-0.59), and orbital and external diseases (claims AUC, 0.63; 95% CI, 0.57-0.69; EHR AUC, 0.65; 95% CI, 0.59-0.70).Conclusion and RelevanceIn this cross-sectional study of current and recent ophthalmology patients with high rates of eye disorders and vision loss, identification of major vision-threatening eye disorders based on diagnosis codes in claims and EHR records was accurate. However, vision loss, refractive error, and other broadly defined or lower-risk disorder categories were less accurately identified by diagnosis codes in claims and EHR data.
for the IRIS Registry Analytic Centers Study GroupPurpose: To evaluate whether cataract surgery is associated with decreased risks of central retinal vein occlusion (CRVO) or branch retinal vein occlusion (BRVO) development using the American Academy of Ophthalmology Intelligent Research in Sight (IRISÒ) Registry.Design: Retrospective database study of the IRIS Registry data.Participants: Patients in the IRIS Registry who underwent cataract surgery and 1:1 matched control participants from the IRIS Registry using a decision tree classifier as a propensity model.Methods: Control and treatment groups initially were selected using Current Procedural Terminology codes for uncomplicated cataract surgery and other straightforward criteria. To accomplish treatmentecontrol matching, a decision tree classifier was trained to classify patients as treatment versus control based on a set of chosen predictors for treatment, where best-corrected visual acuity and age were the most important predictors. Treatment and control participants subsequently were matched using the classifier, the visit dates, and the identifications of the practice. Cox regression was performed on the matched groups to measure the hazard ratio (HR) of retinal vein occlusion development adjusted for age, sex, race, primary insurance type, and previous diagnosis of diabetic retinopathy (DR), glaucoma, and narrow angles.Main Outcome Measure: The HR of retinal vein occlusion developing in patients who underwent cataract surgery compared with matched control participants.Results: The HRs for CRVO and BRVO developing in patients who underwent cataract surgery compared with matched control participants who did not during the first year after either cataract surgery or baseline visit were 1.26 [95% confidence interval [CI], 1.16e1.38; P < 0.001] and 1.27 [95% CI, 1.19e1.36; P < 0.001], respectively, after controlling for age, sex, race, insurance, and history of DR, glaucoma, and narrow angles. Diabetic retinopathy was the strongest predictor associated with CRVO (2.79 [95% CI, 2.43e3.20; P < 0.001]) and BRVO (2.35 [95% CI, 2.09e2.64; P < 0.001]) development after cataract surgery.
BACKGROUND Understanding the expectations of early career acute care surgeons will help clarify the practice and employment models that will attract and retain high-quality surgeons, thereby sustaining our workforce. This study aimed to outline the clinical and academic preferences and priorities of early career acute care surgeons and to better define full-time employment. METHODS A survey on clinical responsibilities, employment preferences, work priorities, and compensation was distributed to early career acute care surgeons in the first 5 years of practice. A subset of agreeable respondents underwent virtual semistructured interviews. Both quantitative and thematic analysis were used to describe current responsibilities, expectations, and perspectives. RESULTS Of 471 surgeons, 167 responded (35%), the majority of whom were assistant professors within the first 3 years of practice (80%). The median desired clinical volume was 24 clinical weeks and 48 call shifts per year, 4 weeks less than their median current clinical volume. Most respondents (61%) preferred a service-based model. The top priorities cited in choosing a job were geography, work schedule, and compensation. Qualitative interviews identified themes related to defining full-time employment, first job expectations and realities, and the often-misaligned system and surgeon. CONCLUSION Understanding the perspectives of early career surgeons entering the workforce is important particularly in the field of acute care surgery where no standard workload or practice model exists. The wide variety of expectations, practice models, and schedule preferences may lead to a mismatch between surgeon desires and employment expectation. Consistent employment standards across our specialty would provide a framework for sustainability. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level III.
BACKGROUND Self-reported questions on blindness and vision problems are collected in many national surveys and may serve as important indicators for surveillance of visual health. However, the validity of these measures to predict prevalence and disparities in objectively measured visual function is unknown. OBJECTIVE To estimate the accuracy of self-reported vision loss measures fielded in national surveys compared to evaluated best-corrected visual acuity (BCVA) at both the individual and population level. METHODS We calculated measures of accuracy and correlation between self-reported visual function versus BCVA, on both an individual and population basis among University of Washington ophthalmology or optometry clinic patients with a prior eye examination, randomly selected with oversampling for visual acuity loss or diagnosed eye diseases. Self-reported visual function was collected via a telephone survey. BCVA was determined based on retrospective chart review. This study was approved by the Institutional Review Board at the University of Washington. RESULTS The survey question “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” had the highest accuracy among patients with blindness (BCVA ≤20/200), while the highest accuracy for detecting any vision loss (BCVA <20/40) was achieved by responses of “fair”, “poor” or “very poor” to the question “At the present time, would you say your eyesight, with glasses or contact lenses if you wear them, is excellent, good, fair, poor, or very poor”. On a population level, prevalence rates based on these two questions were highly correlated to prevalence based on BCVA among all sociodemographic groups. CONCLUSIONS While survey questions may not be sufficiently accurate to be used as a diagnostic test at the individual level, survey questions may accurately reflect demographic and socioeconomic variation in underlying BCVA and can be used to enhance population surveillance of vision loss.
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