213 research outputs found

    Tele-Neuro-Ophthalmology: Vision for 20/20 and Beyond

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    Background: Telehealth provides health care to a patient from a provider at a distant location. Prior to the COVID-19 pandemic adoption of telehealth modalities was increasing slowly but steadily. During the public health emergency rapid widespread telehealth implementation has been encouraged to promote patient and provider safety and preserve access to health care. Evidence acquisition: Evidence was acquired from English language Internet-searches of medical and business literature and following breaking news on the COVID-19 pandemic and responses from health care stakeholders including policy makers, payers, physicians and health care organizations, and patients. We also had extensive discussions with colleagues who are developing telehealth techniques relevant to neuro-ophthalmology. Results: Regulatory, legal, reimbursement and cultural barriers impeded the widespread adoption of telehealth prior to the COVID-19 pandemic. With the increased use of telehealth in response to the public health emergency, we are rapidly accumulating experience and an evidence base identifying opportunities and challenges related to the widespread adoption of tele-neuro-ophthalmology. One of the major challenges is the current inability to adequately perform funduscopy remotely. Conclusions: Telehealth is an increasingly recognized means of healthcare delivery. Tele-neuro-ophthalmology adoption is necessary for the sake of our patients, the survival of our subspecialty, and the education of our trainees and students. Telehealth does not supplant but supplements and complements in-person neuro-ophthalmologic care. Innovations in digital optical fundus photography, mobile vision testing applications, artificial intelligence and principles of channel management will facilitate further adoption of tele-neuro-ophthalmology and bring the specialty to the leading edge of healthcare delivery

    Characterization of Errors in Retinopathy of Prematurity Diagnosis by Ophthalmologists-in-Training in the United States and Canada

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    PURPOSE: To identify the prominent factors that lead to misdiagnosis of retinopathy of prematurity (ROP) by ophthalmologists-in-training in the United States and Canada. METHODS: This prospective cohort study included 32 ophthalmologists-in-training at six ophthalmology training programs in the United States and Canada. Twenty web-based cases of ROP using wide-field retinal images were presented, and ophthalmologists-in-training were asked to diagnose plus disease, zone, stage, and category for each eye. Responses were compared to a consensus reference standard diagnosis for accuracy, which was established by combining the clinical diagnosis and the image-based diagnosis by multiple experts. The types of diagnostic errors that occurred were analyzed with descriptive and chi-squared analysis. Main outcome measures were frequency of types (category, zone, stage, plus disease) of diagnostic errors; association of errors in zone, stage, and plus disease diagnosis with incorrectly identified category; and performance of ophthalmologists-in-training across postgraduate years. RESULTS: Category of ROP was misdiagnosed at a rate of 48%. Errors in classification of plus disease were most commonly associated with misdiagnosis of treatment-requiring (plus error rate = 16% when treatment-requiring was correctly diagnosed vs 81% when underdiagnosed as type 2 or pre-plus; mean difference: 64.3; 95% CI: 51.9 to 76.7; CONCLUSIONS: Ophthalmologists-in-training in the United States and Canada misdiagnosed ROP nearly half of the time, with incorrect identification of plus disease as a leading cause. Integration of structured learning for ROP in residency education may improve diagnostic competency

    The Effectiveness of Teleglaucoma versus In-patient Examination. Assessment: Systematic Review, Meta-Analysis, and Cost-Effectiveness Analysis

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    Teleglaucoma is a screening device that remotely detects glaucoma cases at earlier stages using electronically-transferred stereoscopic digital imaging. Thus, patient wait and travel times are reduced, as well as, patient load in ophthalmic clinics. The purpose is to synthesize literature to evaluate teleglaucoma: its diagnostic accuracy, the healthcare system benefits, and its cost-effectiveness. A systematic review was conducted with published and unpublished studies. A meta-analysis was conducted to provide estimates of diagnostic accuracy, diagnostic odds ratio, and the relative percentage of glaucoma cases detected. Using Markov Modelling, a cost-effectiveness analysis was conducted. Of 11237 studies reviewed, 45 were included. Teleglaucoma was more specific and less sensitive than in-person examination. The pooled estimates of sensitivity was 0.832 [95% CI 0.770, 0.881] and specificity was 0.790 [95% CI 0.668, 0.876]. The ICER calculated for teleglaucoma was $27,460/QALY. In conclusion, teleglaucoma was found to be more cost-effective than in-person examination in rural areas

    Telemedicine

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    Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

    How e-Health Has Influenced Patient Care and Medical Education: Lessons Learned from the COVID-19 Pandemic

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    The concept of e-Health involves the application of information and communication technologies from off-site locations to various domains of healthcare ranging from patient care, public health, and administration to health education. It refers to health informatics, telemedicine, electronic health records, and clinical decision support systems. The e-health initiatives aim to improve health outcomes in terms of quality, access, affordability, and efficient monitoring. The application of e-health interventions has particularly expanded in recent times because of the restrictions imposed by the pandemic. It has been proven to be nearly as effective as in-person care along with high patient and provider satisfaction and at decreased costs. We present our experience from the use of various e-health interventions during the COVID-19 pandemic along with a review of related literature. This ranged from Internet-based services, interactive TV or Polycom’s, kiosks, online monitoring of patient’s vital signs, and remote consultations with experts. Our success and experience with various e-health interventions during the pandemic allow us to provide a more hybrid form of healthcare in the future both for patient care and medical education and training

    “The graduates of the Postgraduate Diploma in Community Eye Health: how do they manage?”

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    The Postgraduate Diploma in Community Eye Health (PgDCEH) has been offered at the University of Cape Town, South Africa since 2009 to develop management capacity in support of the delivery of effective and efficient eye care services in sub-Saharan Africa. We investigated how graduates applied the PgDCEH-acquired management competencies and the factors that enabled or constrained them to apply these competencies. A multiple case study design was used, employing mixed methods of data collection and analysis. Data collection comprised of a questionnaire survey, in-depth interviews and review of various supporting documents, including assignments submitted by students. Twenty-six of the 34 students who graduated from 2009 to 2014 submitted completed questionnaires. Of these, 15 purposively selected graduates and their secondary key informants participated in in-depth interviews. We found that the PgDCEH elicited some positive effects on the graduates, especially in their ability to perform management tasks and the level of confidence they have in their abilities. There were some personal achievements, but no significant programme improvements were observed. This study provided evidence that the PgDCEH as a health system strengthening intervention struggled to generate the anticipated response of improved eye care programme performance. Personal motivation, suitability of the training and opportunity to apply were the main factors determining how graduates apply management competencies. The utilization of the project management approach, a greater focus on health system maintenance and attention to the dynamic of change in people's lives are critical determinants of success in eye health programmes. The research also highlighted the importance of health care workers' personal motives and motivations as drivers of success and achievement on programme level, and that line management support, supervision and proper performance management are required to attain this. This research broadened understanding of how PgDCEH graduates interact with their work environment and uncovered ways to improve the design and delivery of management training for eye health workers in the future. Revision of the criteria for selection, strengthening focus on leadership, project and relationship management topics, and integrating the training into health professions' education programmes may substantially improve the impact of health management education. The study concluded that the constituent elements of the health system are not inanimate objects, as commonly portrayed, but people, who are connected in intimate, complex and multi-dimensional ways through communication, relationships and team dynamics to deliver health outcomes

    Artificial intelligence and deep learning in ophthalmology

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    Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to impact on healthcare. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and visual fields, achieving robust classification performance in the detection of diabetic retinopathy and retinopathy of prematurity, the glaucoma-like disc, macular oedema and age-related macular degeneration. DL in ocular imaging may be used in conjunction with telemedicine as a possible solution to screen, diagnose and monitor major eye diseases for patients in primary care and community settings. Nonetheless, there are also potential challenges with DL application in ophthalmology, including clinical and technical challenges, explainability of the algorithm results, medicolegal issues, and physician and patient acceptance of the AI 'black-box' algorithms. DL could potentially revolutionise how ophthalmology is practised in the future. This review provides a summary of the state-of-the-art DL systems described for ophthalmic applications, potential challenges in clinical deployment and the path forward

    The simulated ocular surgery (SOS) trials: randomised-controlled trials comparing intense simulation-based surgical edication for cataract and glaucoma surgery to conventional training alone in East and Southern Africa

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    Cataract remains the most common cause of blindness globally, and glaucoma is the third after uncorrected refractive error. Surgical management remains a priority, yet surgical training of ophthalmologists continues in the outdated apprentice model. Simulation-based surgical education is yet to be tested to the level of a randomised-controlled trial in ophthalmology. We designed two separate and independent multi-centre multi-country investigator-masked randomised controlled educational-intervention parallel group efficacy trials. Post-graduate doctors in ophthalmology training programmes at collaborating institutions in five East and Southern African countries were assessed for eligibility for inclusion (not having performed the procedure as primary surgeon) into either the OLIMPICS (ophthalmic learning and improvement initiative in cataract surgery) or GLASS (glaucoma simulated surgery) trials. Fifty-one surgical trainees were recruited into the GLASS trial, and 50 into the OLIMPICS trial. Surgical competency was assessed by video recordings, which were double marked by independent experts who were masked to group assignment and timing of the assessment. The intervention was an intense simulation-based cataract or glaucoma surgical training course over 5 days. Primary outcome measure was surgical competency at three-months assessed with validated simulated surgical competency assessment rubrics, the Sim-OSSCARs (ophthalmic simulation surgical competency assessment rubric), for both trials. The trials were registered in March 2017 on the Pan-African Clinical Trial Registry (PACTR201803002159198) and are currently closed to recruitment. Baseline characteristics of age, sex, year of training, baseline knowledge and competency scores were balanced between both arms, for both trials. In total 1,361 surgical videos from across different time-points were independently graded by two separate graders in both trials. In the OLIMPICS trial, 50 participants were recruited between November 2017 and May 2018 and 49 included in the final intention-to-treat analysis with one dropout from the control group. Intervention group participants increased mean simulated surgical competence scores from a baseline of 10.8 of 40 points (27.0%) to 33.7 (84.2%) at 3-months after the training intervention, an increase of 212%. Control group participants’ mean baseline scores were 12.8 (31.9%) and 3-month scores 17.9 (44.7%). We found strong evidence (linear regression p<0.0001) that those in the intervention arm were estimated to have higher scores at three months than those in the control arm, after adjusting for baseline score. Among individuals with the same baseline score, those who received the training were estimated to have scores 16.6 points higher (95%CI 14.5 to 18.8) at three months, compared to those who had not received the training. Intervention participants performed a mean of 22 cataract surgeries as primary surgeon in the one year following the training intervention, compared to 9 by control participants (Poisson regression p<0.0001). Surgical complications were reported for the one year period, and posterior capsule rupture (PCR) rates were 7.4% for the intervention group compared to 26.2% for controls (p<0.0001). Confidence rating scores were assessed using a ten-point Likert scale anchored at 1=’not confident at all’, and 10=’very confident’. Confidence as cataract surgeons increased from 2.2 (of 10) to 6.3 at three-months in the intervention group, compared to 3.4 at baseline to 4.2 for the control group. Among individuals with the same baseline confidence score, those receiving the training were estimated to have scores 2.7 points higher (95%CI 1.6 to 3.7) (p<0.001). In the GLASS trial, 53 trainee ophthalmologists were assessed for eligibility, and 51 were enrolled and randomised. Forty-nine participants were included in the final intention-to-treat analysis: 23 intervention and 26 control, following two drop outs from the intervention group. Baseline surgical competency scores for intervention were a mean of 9.1/40 (22.6%) [median 7.3, IQR 5.4-12.1]; and for control: 8.7/40 (21.8%) [median 8.2, IQR 6.3-12.0] participants. Mean Sim-OSSCAR scores at three-months were 30.4 (76.1%) [median 30.3 IQR 27.8-33.5] and 9.8 (24.4%) [median 9.2 IQR 7.5-11.7] for intervention and control groups respectively. We found strong evidence (linear regression p<0.0001) that those in the intervention arm were estimated to have higher scores at three months than those in the control arm, after adjusting for baseline score as a fixed effect. Among individuals with the same baseline score, those who received the training were estimated to have scores 20.5 points (of 40) higher (95%CI 18.4 to 22.6) at three months, compared to those who had not received the training (linear regression p<0.0001). Baseline mean self-reported confidence in glaucoma surgical skills was 3.0/10 for intervention and 3.2 for control participants. This increased to mean 6.4 and 3.7 at three months respectively (p=0.002). Trainee participants in the intervention group performed a mean of 3.1 live surgical trabeculectomies as primary surgeon over one year following training (median 2, range 0-15, IQR 0-4). Over the same period (and before their simulation training) the control group performed a mean of 0.15 (only one of the 26 control participants performed any glaucoma surgery, compared to 14 of the 23 intervention participants). These are the first multi-centre ophthalmic simulation surgery educational-intervention randomised controlled trials ever conducted. Intense simulation training affords a rapid and sustained increase in surgical competence, confidence as a surgeon, and impacts the number of live surgeries performed. Simulation education in cataract surgery affords a striking benefit in terms of patient safety

    Development and validation of a deep learning system to detect glaucomatous optic neuropathy using fundus photographs

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    Importance A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON. Objective To establish a DLS for detection of GON using retinal fundus images and glaucoma diagnosis with convoluted neural networks (GD-CNN) that has the ability to be generalized across populations. Design, Setting, and Participants In this cross-sectional study, a DLS for the classification of GON was developed for automated classification of GON using retinal fundus images obtained from the Chinese Glaucoma Study Alliance, the Handan Eye Study, and online databases. The researchers selected 241 032 images were selected as the training dataset. The images were entered into the databases on June 9, 2009, obtained on July 11, 2018, and analyses were performed on December 15, 2018. The generalization of the DLS was tested in several validation datasets, which allowed assessment of the DLS in a clinical setting without exclusions, testing against variable image quality based on fundus photographs obtained from websites, evaluation in a population-based study that reflects a natural distribution of patients with glaucoma within the cohort and an additive dataset that has a diverse ethnic distribution. An online learning system was established to transfer the trained and validated DLS to generalize the results with fundus images from new sources. To better understand the DLS decision-making process, a prediction visualization test was performed that identified regions of the fundus images utilized by the DLS for diagnosis. Exposures Use of a deep learning system. Main Outcomes and Measures Area under the receiver operating characteristics curve (AUC), sensitivity and specificity for DLS with reference to professional graders. Results From a total of 274 413 fundus images initially obtained from CGSA, 269 601 images passed initial image quality review and were graded for GON. A total of 241 032 images (definite GON 29 865 [12.4%], probable GON 11 046 [4.6%], unlikely GON 200 121 [83%]) from 68 013 patients were selected using random sampling to train the GD-CNN model. Validation and evaluation of the GD-CNN model was assessed using the remaining 28 569 images from CGSA. The AUC of the GD-CNN model in primary local validation datasets was 0.996 (95% CI, 0.995-0.998), with sensitivity of 96.2% and specificity of 97.7%. The most common reason for both false-negative and false-positive grading by GD-CNN (51 of 119 [46.3%] and 191 of 588 [32.3%]) and manual grading (50 of 113 [44.2%] and 183 of 538 [34.0%]) was pathologic or high myopia. Conclusions and Relevance Application of GD-CNN to fundus images from different settings and varying image quality demonstrated a high sensitivity, specificity, and generalizability for detecting GON. These findings suggest that automated DLS could enhance current screening programs in a cost-effective and time-efficient manner
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