Abstract: Ophthalmology residency training programs need authentic methods of assessment to show that trainees have learned and can do what is expected upon graduation. Written and oral examinations are necessary to assess knowledge but other methods are needed to assess skill. Workplace-based assessments (WPBAs) should be utilized to observe resident skill in the clinic and during surgery. Several such assessment tools have been published and validated. These tools have the additional benefit of facilitating specific formative feedback and thus can be used for both teaching and assessing.
Abstract: The outcomes of modern ophthalmic surgery, especially cataract surgery, continue to improve and patients now realistically expect an excellent and speedy outcome with good vision and few complications. Social and regulatory demands for greater transparency and accountability in medicine have increased, highlighting a fundamental ethical tension in medical education—balancing the needs of trainees (who have not yet mastered the technique) to gain experience by performing surgery, with patient safety and the needs of the public to be protected from risk. Patient safety and well-being are the paramount considerations in any training program and must be the first consideration in program design. A variety of different educational strategies, each implemented with the aim of improving operative skills assessment and teaching, has recently been described in the literature. Effective use of these educational tools, combined with a structured approach to teaching and providing meaningful feedback, could improve outcomes, decrease complications and improve the quality and efficiency of surgical training in ophthalmology. Supervisors must assess their teaching style and communication, as being a good surgeon does not necessarily make a good trainer. Open disclosure must be given to patients about who will be performing the surgery, and communication during surgery between supervisors and trainees must be clear, respectful and appropriate.
Abstract: Congenital ptosis is an abnormally low position of the upper eyelid, with respect to the visual axis in the primary gaze. It can be present at birth or manifest itself during the first year of life and can be bilateral or unilateral. Additionally, it may be an isolated finding or part of a constellation of signs of a specific syndrome or systemic associations. Depending on how much it interferes with the visual axis, it may be considered as a functional or a cosmetic condition. In childhood, functional ptosis can lead to deprivation amblyopia and astigmatism and needs to be treated. However, even mild ptosis with normal vision can lead to psychosocial problems and correction is also advised, albeit on a less urgent basis. Although, patching and glasses can be prescribed to treat the amblyopia, the mainstay of management is surgical. There are several types of surgical procedure available depending on the severity and etiology of the droopy eyelid. The first part of this paper will review the different categories of congenital ptosis, including more common associated syndromes. The latter part will briefly cover the different surgical approaches, with emphasis on how to choose the correct condition. In spite of many complex factors inherent to the treatment of congenital ptosis, the overall outcomes are quite satisfactory, and most surgeons feel that ptosis management can be both challenging and rewarding at the same time.
Abstract: Artificial intelligence (AI) methods have become a focus of intense interest within the eye care community. This parallels a wider interest in AI, which has started impacting many facets of society. However, understanding across the community has not kept pace with technical developments. What is AI, and how does it relate to other terms like machine learning or deep learning? How is AI currently used within eye care, and how might it be used in the future? This review paper provides an overview of these concepts for eye care specialists. We explain core concepts in AI, describe how these methods have been applied in ophthalmology, and consider future directions and challenges. We walk through the steps needed to develop an AI system for eye disease, and discuss the challenges in validating and deploying such technology. We argue that among medical fields, ophthalmology may be uniquely positioned to benefit from the thoughtful deployment of AI to improve patient care.
Background: To study the application of management tools such as Plan-Do-Check-Action (PDCA) cycle and fishbone diagram in optimizing surgical procedures to improve the satisfaction of doctor-nurse-patient.
Methods: The fundus surgery nursing team of our hospital began to implement the PDCA cycle management mode to optimize the surgical procedure from July 2017, set up a project activity improvement team, unified the surgical labeling processing plan, and made the fundus surgery procedure, and established the preoperative health education for surgical patients, and standardized the training content of post-rotating doctors and interns.
Results: The satisfaction degree to surgical procedure after implementation of doctors and nurses was higher than that before implementation.
Conclusions: Using PDCA cycle and fishbone diagram analysis tools to manage the surgical procedure optimization can better integrate doctor-nurse medical care, improve the efficiency and accuracy of the surgical procedure delivery and operation, and optimize the satisfaction of the three parties of doctor-nurse-patient.
Abstract: Several factors drive the need for increased efficiency in telemedicine screening programs directed toward diabetic retinopathy: continually increasing prevalence of diabetes worldwide, growing awareness among physicians and patients of the importance of early detection of retinal damage, and emerging technology in artificial intelligence that enables rapid identification of vision-threatening fundus features. In this context, optimizing workflows in teleretinopathy programs becomes a priority. Recent work has revealed opportunities for improvement in areas of logistics, in particular in finding the best way to get diabetic patients in front of screening cameras as conveniently as possible, as this improves compliance and, ultimately, achieves the widest reach for detection programs. The present review discusses particular aspects of mobile screening programs in which specialized retinal cameras are deployed in a van or similar type of vehicle so that they can reach patients anywhere in order to reduce barriers to access. The rationale for implementing such programs and practical considerations are presented, along with a view toward future expansion of screening and integration with artificial intelligence platforms. Lacking standardization of format and quality control among smartphone-linked approaches at present, translation of eye clinic-based photographic techniques to community-based screening offers a means of expanding the scope of impactful screening programs without the need for adoption of significantly new technology.
Abstract: The objective of the paper is to provide a general view for automatic cup to disc ratio (CDR) assessment in fundus images. As for the cause of blindness, glaucoma ranks as the second in ocular diseases. Vision loss caused by glaucoma cannot be reversed, but the loss may be avoided if screened in the early stage of glaucoma. Thus, early screening of glaucoma is very requisite to preserve vision and maintain quality of life. Optic nerve head (ONH) assessment is a useful and practical technique among current glaucoma screening methods. Vertical CDR as one of the clinical indicators for ONH assessment, has been well-used by clinicians and professionals for the analysis and diagnosis of glaucoma. The key for automatic calculation of vertical CDR in fundus images is the segmentation of optic cup (OC) and optic disc (OD). We take a brief description of methodologies about the OC and disc optic segmentation and comprehensively presented these methods as two aspects: hand-craft feature and deep learning feature. Sliding window regression, super-pixel level, image reconstruction, super-pixel level low-rank representation (LRR), deep learning methodologies for segmentation of OD and OC have been shown. It is hoped that this paper can provide guidance and bring inspiration to other researchers. Every mentioned method has its advantages and limitations. Appropriate method should be selected or explored according to the actual situation. For automatic glaucoma screening, CDR is just the reflection for a small part of the disc, while utilizing comprehensive factors or multimodal images is the promising future direction to furthermore enhance the performance.
