Low Vision Rehabilitation Service Utilization Before and After Implementation of a Clinical Decision Support System in Ophthalmology.

Importance: Electronic clinical decision support systems apply clinical guidelines in real time and offer a new approach to improve referral and utilization of low vision rehabilitation (LVR) care. Objective: To characterize patients and factors associated with LVR service utilization with and without the use of an electronic health record (EHR) clinical decision support system (CDSS) alert. Design, Setting, and Participants: Quality improvement study using EHR data to compare patients who did and did not utilize LVR service after referral between November 6, 2017, and October 5, 2019, (primary) and to assess overall service utilization rate from September 1, 2016, to April 2, 2021, regardless of referral status (secondary). Participants in the primary analysis were patients at a large ophthalmology department in an academic medical center in the US who received an LVR referral recommendation from their ophthalmologist according to the CDSS alert. The secondary analysis included patients with best documented visual acuity (BDVA) worse than 20/40 before, during, and after the CDSS implementation. Data were analyzed from August 2021 to April 2022. Exposures: Number and locations of referral recommendations for LVR service according to the CDSS alert in the primary analysis; active CDSS implementation in the secondary analysis. Main Outcomes and Measures: LVR service utilization rate was defined as the number of patients who accessed service among those who were referred (primary) and among those with BDVA worse than 20/40 (secondary). EHR data on patient demographics (age, sex, race, ethnicity) and ophthalmology encounter characteristics (numbers of referral recommendations, encounter location, and BDVA) were extracted. Results: Of the 429 patients (median [IQR] age, 71 [53 to 83] years; 233 female [54%]) who received a CDSS-based referral recommendation, 184 (42.9%) utilized LVR service. Compared with nonusers of LVR, users were more likely to have received at least 2 referral recommendations (12.5% vs 6.1%; χ21 = 5.29; P = .02) and at an ophthalmology location with onsite LVR service (87.5% vs 78.0%; χ21 = 6.50; P = .01). Onsite LVR service (odds ratio, 2.06; 95% CI, 1.18-3.61) persisted as the only statistically significant factor after adjusting for patient demographics and other referral characteristics. Among patients whose BDVA was worse than 20/40 before, during, and after the CDSS implementation regardless of referral status, the LVR service utilization rate was 6.1%, 13.8%, and 7.5%, respectively. Conclusions and Relevance: In this quality improvement study, ophthalmologist referral recommendations and onsite LVR services at the location where patients receive other ophthalmic care were significantly associated with service utilization. Ophthalmology CDSSs are promising tools to apply clinical guidelines in real time to improve connection to care.

Approaching rehabilitation in patients with advanced glaucoma.

Vision loss from advanced glaucoma is currently irreversible and impairs functional visual ability to effectively perform everyday tasks in a number of distinct functional domains. Vision rehabilitation strategies have been demonstrated to be effective in low vision populations and should be utilized in persons with advanced glaucoma to reduce disability and improve quality of life. Initial challenges to rehabilitation include an incomplete understanding of vision rehabilitation by the physician and patient, motivation to integrate rehabilitation into the plan of care, and availability of suitable providers to deliver this care. Physicians, working with well-trained vision rehabilitation providers can maximize function in important visual domains customized to the patient based on their needs, specific complaints, severity/pattern of visual damage, and comorbidities. Potential rehabilitative strategies to be considered for reading impairment include spectacle correction, visual assistive equipment, and sensory substitution, while potential strategies to facilitate driving in those deemed safe to do so include refractive correction, lens design, building confidence, restriction of driving to safer conditions, and avoiding situations where cognitive load is high. Mobility is frequently disrupted in advanced glaucoma, and can be addressed through careful distance refraction, behavior modification, home modification, mobility aids, walking assistance (i.e., sighted guide techniques), and smartphone/wearable technologies. Visual motor complaints are best addressed through optimization of lighting/contrast, sensory substitution, IADL training, and education. Special rehabilitative concerns may arise in children, where plans must be coordinated with schools, and working adults, where patients should be aware of their rights to accommodations to facilitate specific job tasks.

Visual Acuity: Assessment of Data Quality and Usability in an Electronic Health Record System.

Objective: To examine the data quality and usability of visual acuity (VA) data extracted from an electronic health record (EHR) system during ophthalmology encounters and provide recommendations for consideration of relevant VA end points in retrospective analyses. Design: Retrospective, EHR data analysis. Participants: All patients with eyecare office encounters at any 1 of the 9 locations of a large academic medical center between August 1, 2013, and December 31, 2015. Methods: Data from 13 of the 21 VA fields (accounting for 93% VA data) in EHR encounters were extracted, categorized, recoded, and assessed for conformance and plausibility using an internal data dictionary, a 38-item listing of VA line measurements and observations including 28 line measurements (e.g., 20/30, 20/400) and 10 observations (e.g., no light perception). Entries were classified into usable and unusable data. Usable data were further categorized based on conformance to the internal data dictionary: (1) exact match; (2) conditional conformance, letter count (e.g., 20/30+2 - 3); (3) convertible conformance (e.g., 5/200 to 20/800); (4) plausible but cannot be conformed (e.g., 5/400). Data were deemed unusable when they were not plausible. Main Outcome Measures: Proportions of usable and unusable VA entries at the overall and subspecialty levels. Results: All VA data from 513 036 encounters representing 166 212 patients were included. Of the 1 573 643 VA entries, 1 438 661 (91.4%) contained usable data. There were 1 196 720 (76.0%) exact match (category 1), 185 692 (11.8%) conditional conformance (category 2), 40 270 (2.6%) convertible conformance (category 3), and 15 979 (1.0%) plausible but not conformed entries (category 4). Visual acuity entries during visits with providers from retina (17.5%), glaucoma (14.0%), neuro-ophthalmology (8.9%), and low vision (8.8%) had the highest rates of unusable data. Documented VA entries with providers from comprehensive eyecare (86.7%), oculoplastics (81.5%), and pediatrics/strabismus (78.6%) yielded the highest proportions of exact match with the data dictionary. Conclusions: Electronic health record VA data quality and usability vary across documented VA measures, observations, and eyecare subspecialty. We proposed a checklist of considerations and recommendations for planning, extracting, analyzing, and reporting retrospective study outcomes using EHR VA data. These are important first steps to standardize analyses enabling comparative research.

Using Electronic Clinical Decision Support to Examine Vision Rehabilitation Referrals and Practice Guidelines in Ophthalmology.

Purpose: To examine ophthalmologist use of an electronic health record (EHR)-based clinical decision support system (CDSS) to facilitate low vision rehabilitation (LVR) care referral. Methods: The CDSS alert was designed to appear when best documented visual acuity was <20/40 or hemianopia or quadrantanopia diagnosis was identified during an ophthalmology encounter from November 6, 2017, to April 5, 2019. Fifteen ophthalmologists representing eight subspecialties from an academic medical center were required to respond to the referral recommendation (order, don't order). LVR referral rates and ophthalmologist user experience were assessed. Encounter characteristics associated with LVR referrals were explored using multilevel logistic regression analysis. Results: The alert appeared for 3625 (8.9%) of 40,931 eligible encounters. The referral rate was 14.8% (535/3625). Of the 3413 encounters that met the visual acuity criterion only, patients who were worse than 20/60 were more likely to be referred, and 32.4% of referred patients were between 20/40 and 20/60. Primary reasons for deferring referrals included active medical or surgical treatment, refractive-related issues, and previous connection to LVR services. Eleven of the 13 ophthalmologists agreed that the alert was useful in identifying candidates for LVR services. Conclusions: A CDSS for patient identification and referral offers an acceptable mechanism to apply practice guidelines and prompt ophthalmologists to facilitate LVR care. Further study is warranted to optimize ophthalmologist user experience while refining alert criteria beyond visual acuity. Translational Relevance: The CDSS provides the framework for multi-center research to assess the development of pragmatic algorithms and standards for facilitating LVR care.

The NEI VFQ-25C: Calibrating Items in the National Eye Institute Visual Function Questionnaire-25 to Enable Comparison of Outcome Measures.

Purpose: To improve the usefulness of the National Eye Institute Visual Function Questionnaire-25 (NEI VFQ-25) by enabling estimation of measures on an invariant scale and comparisons between patients and across studies. Methods: Datasets of baseline NEI VFQ-25 responses from nine studies (seven retina randomized trials, n = 2770; two low vision studies, n = 572) were combined. The method of successive dichotomizations was applied to patient ratings of the main NEI VFQ-25 and six supplemental items to estimate Rasch model parameters using the R package 'msd.' Calibrated item measures and rating category thresholds were estimated for the NEI VFQ-25, as well as for two domain-specific versions: the NEI VFQ-VF that includes only visual function items and the NEI VFQ-SE that includes only socioemotional items. Results: Calibrated item measures were estimated from study participants (n = 3342) ranging in age from 19 to 103 years, with mean (SD) age of 69.3 (11) years and a mean logMAR visual acuity of 0.30 (Snellen 20/40). Item measure estimates had high precision (standard error range, 0.026-0.085 logit), but person measure estimates had lower precision (standard error range, 0.108-0.499 logit). Items were well targeted to most persons, but not to those with higher levels of function. Conclusions: Calibrated item measures and rating category thresholds enable researchers and clinicians to estimate visual, socioemotional, and combined measures on an invariant scale using the NEI VFQ-25. Translational Relevance: Applying NEI VFQ 25C calibrated item measures (software provided) to the NEI VFQ-25, users can estimate overall, visual, and socioemotional function measures for individual patients.

Calibration of the Activity Inventory Item Bank: A Patient-Reported Outcome Measurement Instrument for Low Vision Rehabilitation.

Purpose: To provide calibrated item measures and rating category thresholds for the Activity Inventory (AI), an adaptive visual function questionnaire, from difficulty ratings obtained from a large sample of new low vision patients at pre-rehabilitation baseline. Methods: Baseline AI (510 items) rating scale data from five previous low vision rehabilitation outcome studies (n = 3623) were combined, and the method of successive dichotomizations was used to estimate calibrated item measures and rating category thresholds. Infit statistics were analyzed to evaluate the fit of the data to the model. Factor analysis was applied to person measures estimated from different subsets of items (e.g., functional domains such as reading, mobility) to evaluate differential person functioning. Results: Estimated item measures were well targeted to the low vision patient population. The distribution of infit statistics confirmed the validity of the estimated measures and the two-factor structure previously observed for the AI. Conclusions: Our calibrated item measures and rating category thresholds enable researchers to estimate changes in visual ability from low vision rehabilitation on the same scale, facilitating comparisons between studies. Translational Relevance: The work described in this paper provides calibrated item measures and rating category thresholds for a visual function questionnaire to measure patient-centered outcomes in low vision clinical research. The calibrated AI also can be used as a patient outcome measure and quality assurance tool in clinical practice.

Developing an Ophthalmology Clinical Decision Support System to Identify Patients for Low Vision Rehabilitation.

Purpose: The purpose of this study was to develop and evaluate an electronic health record (EHR) clinical decision support system to identify patients meeting criteria for low vision rehabilitation (LVR) referral. Methods: In this quality improvement project, we applied a user-centered design approach to develop an interactive electronic alert for LVR referral within the Johns Hopkins Wilmer Eye Institute. We invited 15 ophthalmology physicians from 8 subspecialties to participate in the design and implementation, and to provide user experience feedback. The three project phases incorporated development evaluation, feedback analysis, and system refinement. We report on the final alert design, firing accuracy, and user experiences. Results: The alert was designed as physician-centered and patient-specific. Alert firing relied on visual acuity and International Classification of Diseases (ICD)-10 diagnosis (hemianopia/quadrantanopia) criteria. The alert suppression considerations included age < 5 years, recent surgeries, prior LVR visit, and related alert actions. False positive rate (firing when alert should have been suppressed or when firing criteria not met) was 0.2%. The overall false negative rate (alert not firing when visual acuity or encounter diagnosis criteria met) was 5.6%. Of the 13 physicians who completed the survey, 8 agreed that the alert is easy to use, and 12 would consider ongoing usage. Conclusions: This EHR-based clinical decision support system shows reliable firing metrics in identifying patients with vision impairment and promising acceptance by ophthalmologist users to facilitate care and LVR referral. Translational Relevance: The use of real-time data offers an opportunity to translate ophthalmic guidelines and best practices into systematic action for clinical care and research purposes across subspecialties.

Association of Visual Acuity Improvement With Uncorrected Refractive Error in Patients New to Low Vision Clinics.

Importance: There is substantial socioeconomic and individual burden from uncorrected refractive error (URE) and chronic ocular disease. Understanding the association of visual acuity (VA) reduction with URE and the adults most likely to benefit from refraction may help support clinical decision-making in ophthalmologic care and maximize patient outcomes. Objectives: To assess the magnitude of VA improvement associated with URE among adults under ophthalmic care who obtain low vision rehabilitation (LVR) services and identify the characteristics of the patients who are most likely to experience improvement. Design, Setting, and Participants: This retrospective case series assessed patients 20 years or older who were new to the LVR clinics from August 1, 2013, to December 31, 2015, and who had habitual VA between 20/40 and counting fingers (not including) and underwent refraction. Data analysis was performed from April 4, 2018, to December 20, 2019. Exposures: Patient demographics and clinical data, including habitual and refraction VA, refraction, and disease diagnosis. Habitual VA was categorized as mild (VA worse than 20/40 and at least 20/60), moderate (VA worse than 20/60 and better than 20/200), severe (VA 20/200 or worse and better than 20/500), and profound (VA 20/500 or worse) vision impairment (VI). Main Outcomes and Measures: At least 2-line VA improvement and any VA improvement (≥1-line) by refraction. Results: Among the 2923 patients new to LVR clinics, 1773 (mean [SD] age, 70 [18.2] years; 1069 [60.3%] female) were included in these analyses. The mean habitual VA was 20/100 (mean [SD], 0.67 [0.36] logMAR). At least 2-line improvement was observed in 493 patients (27.8%), and any VA improvement was seen in 1023 patients (57.7%). At least 2-line improvement was observed in 54 patients (34.8%) with corneal disorders and was more likely seen among patients aged 40 to <65 years compared with those aged 20 to <40 years (odds ratio [OR], 1.57; 95% CI, 1.02-2.41), African American patients compared with white patients (OR, 1.41; 95% CI, 1.08-1.85), or patients with moderate VI compared with mild VI (OR, 1.36; 95% CI, 1.07-1.72). Conclusions and Relevance: The findings suggest that URE is prevalent among patients with ocular disease and accessing LVR and that refractive evaluation should be considered for patients with ocular disease and reduced VA, especially working-age adults aged 40 to <65 years, African American patients, and those with moderate VI.

Low Vision Care - Out of Site. Out of Mind.

PURPOSE: To estimate the number of patients accessing eye care with low vision (LV) at a large multi-site ophthalmology institute who utilize low vision rehabilitation (LVR) services and compare their characteristics to individuals who do not utilize LVR services. METHODS: This is an electronic health record-based retrospective chart analysis. Patients with LV were identified as having at least one encounter in 2014 where the best visual acuity (VA) in the better-seeing eye was worse than 20/40. Utilization of LVR services across 9 clinic locations was evaluated. Logistic regression analyses were used to examine patient characteristics associated with service utilization. RESULTS: Of the 7,752 LV patients, 1,585 (20%) utilized LVR services over the 17-month period. Those utilizing LVR were more likely to have VA between 20/60 and 20/200 or between 20/200 and 20/500 than non-users (P < .001). The highest LVR utilization rates were in patients evaluated in retina (23%), glaucoma (22%), and neuro-ophthalmology (18%) subspecialties. Patients seen at clinic locations with onsite LVR services available were more likely to utilize services (odds ratio [OR] ranged from 2.69 [95% confidence interval, 95% CI: 1.63-4.44] to 4.94 [95% CI: 2.12-11.48] across location categories), as were patients who had evidence of fluctuations in VA measurements (OR = 3.33, 95% CI: 2.89-3.84). CONCLUSIONS: Patients are more likely to utilize services when VA is moderately to severely impaired, VA fluctuations are present, or when LVR services are provided at the same location where other ophthalmic services are obtained. These estimates are important for developing interventions aimed at improving LVR utilization.

Leveraging Electronic Health Records to Identify and Characterize Patients with Low Vision.

PURPOSE: To use electronic health record (EHR) data to estimate the prevalence and characteristics of low-vision (LV) patients. METHODS: EHR data were obtained for all patients at the nine clinical locations of the Wilmer Eye Institute in 2014. LV status at each visit was defined as visual acuity (VA) worse than 20/40 in the better-seeing eye. Prevalence and incidence estimates were determined over a 12-month period. Demographic and clinical data were used to compare the characteristics of patients with and without LV. Logistic regression analyses were used to determine prevalence and incidence estimates adjusted for age, sex, race, and ethnicity. RESULTS: A total of 100,755 patients were included in the analysis. There were 7752 (7.7%) prevalent and 1962 (2.1%) incident cases of LV. Among patients with LV, 55% had VA between 20/40 and 20/60. Outside of LV clinics, retina and glaucoma clinics had the highest prevalence (18% and 14%, respectively) and incidence (5% and 4%, respectively) of LV. The urban hospital center had twice the prevalence of LV than suburban clinics (11.5% vs. 5.6%). The odds of prevalent LV was greatest among patients 80 years and older (odds ratio = 6.18; 95% confidence interval: 5.62-6.80) as compared to those 20-39 years old. CONCLUSIONS: EHR can be used to estimate the prevalence and describe the characteristics of patients with LV seeking ophthalmic care. The highest prevalence rates of LV are observed in the urban setting and among patients obtaining retina and glaucoma care.

The Effect of a Head-mounted Low Vision Device on Visual Function.

SIGNIFICANCE: Head-mounted low vision devices have received considerable attention in recent years owing to rapidly developing technology, facilitating ease of use and functionality. Systematic clinical evaluations of such devices remain rare but are needed to steer future device development. PURPOSE: The purpose of this study was to investigate, in a multicenter prospective trial, the short- and medium-term effects of a head-worn vision enhancement device (eSight Eyewear). METHODS: Participants aged 13 to 75 years with stable vision (distance acuity, 20/60 to 20/400; visual field diameter >20°) were recruited across six sites. Data were collected at baseline (no device), at fitting (with device), and after 3 months of everyday use. Outcome measures were visual ability measured by the Veterans Affairs Low Vision Visual Functioning Questionnaire 48, distance acuity (Early Treatment Diabetic Retinopathy Study), reading performance (MNREAD chart), contrast sensitivity (MARS chart), face recognition, and a modified version of the Melbourne Low Vision Activities of Daily Living (ADL) Index. RESULTS: Among the 51 participants, eSight introduction immediately improved distance acuity (0.74 ± 0.28 logMAR), contrast sensitivity (0.57 ± 0.53 log units), and critical print size (0.52 ± 0.43 logMAR), all P < .001, without any further change after 3 months; reading acuity improved at fitting (0.56 ± 0.35 logMAR) and by one additional line after 3 months, whereas reading speed only slightly increased across all three time points. The Melbourne ADL score and face recognition improved at fitting (P < .01) with trends toward further improvement at 3 months. After 3 months of use, Veterans Affairs Low Vision Visual Functioning Questionnaire 48 person measures (in logits) improved: overall, 0.84, P < .001; reading, 2.75, P < .001; mobility, 0.04, not statistically significant; visual information, 1.08, P < .001; and visual motor, 0.48, P = .02. CONCLUSIONS: eSight introduction yields immediate improvements in visual ability, with face recognition and ADLs showing a tentative benefit of further use. Overall, visual ability, reading, and visual information showed greatest benefit with device use. Further studies need to examine benefits of practice and training and possible differential effects of underlying pathology or baseline vision.

Calibrating the Impact of Vision Impairment (IVI): Creation of a Sample-Independent Visual Function Measure for Patient-Centered Outcomes Research.

PURPOSE: Provide item calibrations estimated for the Impact of Vision Impairment (IVI) questionnaire by pooling data from several studies of people with vision impairment (VI) representing a variety of countries and causes of VI. METHODS: Eight data sets from six principal investigators representing responses to IVI items from 2867 VI patients were pooled for analysis. Eligible patients were 18 years or older and from Australia, India, and the United States. Rasch analysis, using the Andrich Rating Scale Model (Winsteps version 3.65), was performed on preintervention IVI responses to estimate item and person measures, reliability coefficients, and response category thresholds. Differential item functioning (DIF) analysis and analysis of variance (ANOVA) were used to examine the effects different data sets and covariates on item estimates. RESULTS: Patient age range was 18 to 103 years (median 62 years); 55% were male. Visual acuity ranged from 20/20 to no light perception and primary diagnosis was macular degeneration in 29% of patients. Item measure estimates showed good separation reliability (R 2 = 0.99). DIF magnitude did not preclude use of all IVI-28 data. ANOVA showed VA (P < 0.001) and gender (P < 0.002) were predictors of visual ability. CONCLUSIONS: Analysis from pooled data support the provision of calibrated IVI item measures for researchers and clinicians to use, thus better enabling direct comparisons of patients with VI. TRANSLATIONAL RELEVANCE: Validity testing of the IVI show that we can combine disparate data sets of patient responses to calibrate item measures and response category thresholds, and provide to others for use in comparing patients across clinical trials and on an individual basis.

Multivariable Regression Model of the EuroQol 5-Dimension Questionnaire in Patients Seeking Outpatient Low Vision Rehabilitation.

PURPOSE: To understand the source of between-person variance in baseline health utilities estimated from EuroQol 5-dimension questionnaire (EQ-5D) responses of a representative sample of the US low vision outpatient population prior to rehabilitation. METHODS: A prospective, observational study of 779 new low vision patients at 28 clinic centers in the US. The EQ-5D, Activity Inventory (AI), Telephone Interview for Cognitive Status (TICS), Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) physical functioning component, and Geriatric Depression Scale (GDS) were administered by telephone interview prior to rehabilitation. EQ-5D responses were transformed into health utilities, which served as the dependent variable in all analyses. Data were then analyzed to determine how much overall visual ability, functional domains of visual ability, and comorbidities (e.g. physical functioning, depression, cognition) independently contribute to the EQ-5D-based health utility index. RESULTS: Multivariable regression analyses showed that the GDS and SF-36 physical account for nearly 40% of the variance observed in health utilities estimated from EQ-5D responses of low vision patients. Age was also a significant predictor of health utilities, but accounted for very little variance. None of the other variables were significant predictors. CONCLUSIONS: Health utilities of low vision patients estimated from the EQ-5D primarily are associated with comorbid factors that are not likely to be responsive to low vision rehabilitation, thereby rendering the EQ-5D an unsuitable outcome measure for this population. However, because the EQ-5D is responsive to comorbid states, it could be a useful tool for evaluating the impact of comorbidities on low vision patient quality of life.

Equating Visual Function Scales to Facilitate Reporting of Medicare Functional G-Code Severity/Complexity Modifiers for Low-Vision Patients.

OBJECTIVE: To present a method of estimating and equating scales across functional assessment instruments that appropriately represents changes in a patient's functional ability and can be meaningfully mapped to changes in Medicare G-code severity modifiers. DESIGN: Previously published measures of patients' overall visual ability, estimated from low-vision patient responses to 7 different visual function rating scale questionnaires, are equated and mapped onto Medicare G-code severity modifiers. SETTING: Outpatient low-vision rehabilitation clinics. PARTICIPANTS: The analyses presented in this article were performed on raw or summarized low-vision patient ratings of visual function questionnaire (VFQ) items obtained from previously published research studies. INTERVENTIONS: Previously published visual ability measures from Rasch analysis of low-vision patient ratings of items in different VFQs (National Eye Institute Visual Functioning Questionnaire, Index of Visual Functioning, Activities of Daily Vision Scale, Visual Activities Questionnaire) were equated with the Activity Inventory (AI) scale. The 39 items in the Self-Report Assessment of Functional Visual Performance (SRAFVP) and the 48 items in the Veterans Affairs Low Vision Visual Functioning Questionnaire (VA LV VFQ) were paired with similar items in the AI in order to equate the scales. MAIN OUTCOME MEASURES: Tests using different observation methods and indicators cannot be directly compared on the same scale. All test results would have to be transformed to measures of the same functional ability variable on a common scale as described here, before a single measure could be estimated from the multiple measures. RESULTS: Bivariate regression analysis was performed to linearly transform the SRAFVP and VA LV VFQ item measures to the AI item measure scale. The nonlinear relationship between person measures of visual ability on a logit scale and item response raw scores was approximated with a logistic function, and the 2 regression coefficients were estimated for each of the 7 VFQs. These coefficients can be used with the logistic function to estimate functional ability on the same interval scale for each VFQ and for transforming raw VFQ responses to Medicare's G-code severity modifier categories. CONCLUSIONS: The principle of using equated interval scales allows for comparison across measurement instruments of low-vision functional status and outcomes, but can be applied to any area of rehabilitation.

Clinically Meaningful Rehabilitation Outcomes of Low Vision Patients Served by Outpatient Clinical Centers.

IMPORTANCE: To facilitate comparative clinical outcome research in low vision rehabilitation, we must use patient-centered measurements that reflect clinically meaningful changes in visual ability. OBJECTIVE: To quantify the effects of currently provided low vision rehabilitation (LVR) on patients who present for outpatient LVR services in the United States. DESIGN, SETTING, AND PARTICIPANTS: Prospective, observational study of new patients seeking outpatient LVR services. From April 2008 through May 2011, 779 patients from 28 clinical centers in the United States were enrolled in the Low Vision Rehabilitation Outcomes Study. The Activity Inventory, a visual function questionnaire, was administered to measure overall visual ability and visual ability in 4 functional domains (reading, mobility, visual motor function, and visual information processing) at baseline and 6 to 9 months after usual LVR care. The Geriatric Depression Scale, Telephone Interview for Cognitive Status, and Medical Outcomes Study 36-Item Short-Form Health Survey physical functioning questionnaires were also administered to measure patients' psychological, cognitive, and physical health states, respectively, and clinical findings of patients were provided by study centers. MAIN OUTCOMES AND MEASURES: Mean changes in the study population and minimum clinically important differences in the individual in overall visual ability and in visual ability in 4 functional domains as measured by the Activity Inventory. RESULTS: Baseline and post-rehabilitation measures were obtained for 468 patients. Minimum clinically important differences (95% CIs) were observed in nearly half (47% [95% CI, 44%-50%]) of patients in overall visual ability. The prevalence rates of patients with minimum clinically important differences in visual ability in functional domains were reading (44% [95% CI, 42%-48%]), visual motor function (38% [95% CI, 36%-42%]), visual information processing (33% [95% CI, 31%-37%]), and mobility (27% [95% CI, 25%-31%]). The largest average effect size (Cohen d = 0.87) for the population was observed in overall visual ability. Age (P = .006) was an independent predictor of changes in overall visual ability, and logMAR visual acuity (P = .002) was predictive of changes in visual information processing. CONCLUSIONS AND RELEVANCE: Forty-four to fifty percent of patients presenting for outpatient LVR show clinically meaningful differences in overall visual ability after LVR, and the average effect sizes in overall visual ability are large, close to 1 SD.

Visual ability of patients seeking outpatient low vision services in the United States.

IMPORTANCE: Most patients with low vision are elderly and have functional limitations from other health problems that could add to the functional limitations caused by their visual impairments. OBJECTIVE: To identify factors that contribute to visual ability measures in patients who present for outpatient low vision rehabilitation (LVR) services. DESIGN, SETTING, AND PARTICIPANTS: As part of a prospective, observational study of new patients seeking outpatient LVR, 779 patients from 28 clinical centers in the United States were enrolled in the Low Vision Rehabilitation Outcomes Study (LVROS) from April 25, 2008, through May 2, 2011. The Activity Inventory (AI), an adaptive visual function questionnaire, was administered to measure overall visual ability and visual ability in 4 functional domains (reading, mobility, visual motor function, and visual information processing) at baseline before LVR. The Geriatric Depression Scale, Telephone Interview for Cognitive Status, and Medical Outcomes Study 36-Item Short-Form Health Survey physical functioning questionnaires were also administered to measure patients' psychological, cognitive, and physical health states, respectively. MAIN OUTCOMES AND MEASURES: Predictors of visual ability and functional domains as measured by the AI. RESULTS: Among the 779 patients in the LVROS sample, the mean age was 76.4 years, 33% were male, and the median logMAR visual acuity score was 0.60 (0.40-0.90 interquartile range). Correlations were observed between logMAR visual acuity and baseline visual ability overall (r = -0.42) and for all functional domains. Visual acuity was the strongest predictor of visual ability (P < .001) and reading ability (P < .001) and had a significant independent effect on the other functional domains. Physical ability was independently associated with (P < .001) overall visual ability as well as mobility and visual motor function. Depression had a consistent independent effect (P < .001) on overall visual ability and on all functional domains, whereas cognition had an effect on only reading and mobility (P < .001). CONCLUSIONS AND RELEVANCE: Visual ability is a multidimensional construct, with visual acuity, depression, physical ability, and cognition explaining more than one-third of the variance in visual ability as measured by the AI. The significant contributions of the nonvisual factors to visual ability measures and the rehabilitation potential (ie, ceiling) effects they may impose on LVR are important considerations when measuring baseline visual ability and ultimately LVR outcomes in ongoing clinical research.

Characterizing functional complaints in patients seeking outpatient low-vision services in the United States.

PURPOSE: To characterize functional complaints of new low-vision rehabilitation patients. DESIGN: Prospective observational study. PARTICIPANTS: The Low Vision Rehabilitation Outcomes Study recruited 819 patients between 2008 and 2011 from 28 clinical centers in the United States. METHODS: New patients referred for low-vision rehabilitation were asked, "What are your chief complaints about your vision?" before their appointment. Full patient statements were transcribed as free text. Two methods assessed whether statements indicated difficulty in each of 13 functional categories: (1) assessment by 2 masked clinicians reading the statement, and (2) a computerized search of the text for specific words or word fragments. Logistic regression models were used to predict the influence of age, gender, and visual acuity on the likelihood of reporting a complaint in each functional category. MAIN OUTCOME MEASURES: Prevalence and risk factors for patient concerns within various functional categories. RESULTS: Reading was the most common functional complaint (66.4% of patients). Other functional difficulties expressed by at least 10% of patients included driving (27.8%), using visual assistive equipment (17.5%), mobility (16.3%), performing in-home activities (15.1%), lighting and glare (11.7%), and facial recognition and social interactions (10.3%). Good agreement was noted between the masked clinician graders and the computerized algorithm for categorization of functional complaints (median κ of 0.84 across the 13 categories). Multivariate logistic regression models demonstrated that the likelihood of reading difficulties increased mildly with age (odds ratio, 1.4 per 10-year increment in age; 95% confidence interval, 1.3-1.6), but did not differ with visual acuity (P = 0.09). Additionally, men were more likely to report driving difficulties and difficulties related to lighting, whereas women were more likely to report difficulty with either in-home activities or facial recognition or social interaction (P<0.05 for all). Mobility concerns, defined as walking difficulty and out-of-home activities, showed no relationship to gender, age, or visual acuity. CONCLUSIONS: Reading was the most commonly reported difficulty, regardless of the patient's diagnosis. Neither visual acuity nor gender were predictive of reading concerns, although, age showed a small effect. Addressing reading rehabilitation should be a cornerstone of low-vision therapy.

Responsiveness of the EQ-5D to the effects of low vision rehabilitation.

PURPOSE: This study is an evaluation of the responsiveness of preference-based outcome measures to the effects of low vision rehabilitation (LVR). It assesses LVR-related changes in EQ-5D utilities in patients who exhibit changes in Activity Inventory (AI) measures of visual ability. METHODS: Telephone interviews were conducted on 77 low-vision patients out of a total of 764 patients in the parent study of "usual care" in LVR. Activity Inventory results were filtered for each patient to include only goals and tasks that would be targeted by LVR. RESULTS: The EQ-5D utilities have weak correlations with all AI measures but correlate best with AI goal scores at baseline (r = 0.48). Baseline goal scores are approximately normally distributed for the AI, but EQ-5D utilities at baseline are skewed toward the ceiling (median, 0.77). Effect size for EQ-5D utility change scores from pre- to post-LVR was not significantly different from zero. The AI visual function ability change scores corresponded to a moderate effect size for all functional domains and a large effect size for visual ability measures estimated from AI goal ratings. CONCLUSIONS: This study found that the EQ-5D is unresponsive as an outcome measure for LVR and has poor sensitivity for discriminating low vision patients with different levels of ability.

Comparison of clinician-predicted to measured low vision outcomes.

PURPOSE: To compare low-vision rehabilitation (LVR) clinicians' predictions of the probability of success of LVR with patients' self-reported outcomes after provision of usual outpatient LVR services and to determine if patients' traits influence clinician ratings. METHODS: The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre-and post-LVR to 316 low-vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression, and cognitive status. After patient evaluation, 38 LVR clinicians estimated the probability of outcome success (POS) using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients' baseline traits on predicted outcomes. RESULTS: A regression analysis with a hierarchical random-effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates that the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed-effects regression models show that POS ratings are associated with information about the patient's cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. CONCLUSIONS: Clinicians' predictions of LVR outcomes seem to be influenced by knowledge of patients' cognitive functioning and the combination of visual acuity and functional ability-information clinicians acquire from the patient's history and examination. However, clinicians' predictions do not agree with observed changes in functional ability from the patient's perspective; they are no better than chance.

Baseline traits of low vision patients served by private outpatient clinical centers in the United States.

OBJECTIVE: To characterize the traits of low vision patients who seek outpatient low vision rehabilitation (LVR) services in the United States. METHODS: In a prospective observational study, we enrolled 764 new low vision patients seeking outpatient LVR services from 28 clinical centers in the United States. Before their initial appointment, multiple questionnaires assessing daily living and vision, physical, psychological, and cognitive health states were administered by telephone. Baseline clinical visual impairment measures and disorder diagnoses were recorded. RESULTS: Patients had a median age of 77 years, were primarily female (66%), and had macular disease (55%), most of which was nonneovascular age-related macular degeneration. More than one-third of the patients (37%) had mild vision impairment with habitual visual acuity (VA) of 20/60 or greater. The VA correlated well with contrast sensitivity (r = -0.52) but poorly with self-reported vision quality. The intake survey revealed self-reported physical health limitations, including decreased endurance (68%) and mobility problems (52%). Many patients reported increased levels of frustration (42%) and depressed mood (22%); memory and cognitive impairment (11%) were less frequently endorsed. Patients relied on others for daily living support (87%), but many (31%) still drove. CONCLUSIONS: Most patients seeking LVR are geriatric and have macular disease with relatively preserved VA. The disparity between VA and subjective quality of vision suggests that LVR referrals are based on symptoms rather than on VA alone. Patients seen for LVR services have significant physical, psychological, and cognitive disorders that can amplify vision disabilities and decrease rehabilitation potential.