Authors: Lea Holtrup, Prof. Dr. med. Nicole Eter
The University Eye Hospital Münster has already been digitally positioned in many areas for several years. In addition to the general hospital information system Orbis, which is used at Münster University Hospital (UKM), FIDUS was introduced in 2013 as a subsystem for ophthalmology for digital treatment documentation under the direction of Univ.-Prof. Dr. med. Nicole Eter. From the recording of patients upon entry into the clinic, to the documentation of diagnoses and treatments, to appointment scheduling, all steps can be recorded in the system and the patient's entire stay in the clinic can be tracked. Data from imaging examination procedures is also automatically transmitted to servers, enabling complete viewing of patient data from virtually any workstation. The digital recording of treatment data simplifies workflows and also makes it possible to evaluate the data for research purposes and process optimization.
In addition to the FIDUS subsystem for documenting examinations, UKM EyeNet was programmed on this basis. The online platform for clinics and practices enables a data protection compliant exchange of current patient data as well as online appointment scheduling via a dedicated VPN line. When a patient is referred to the University Eye Hospital, the sending clinic or practice can transmit relevant patient data in advance and receive findings and image material after the patient's presentation. It is also possible to make appointment requests and send encrypted messages.
Advances in digitization have not only been made in hospital operations, but also through numerous research projects related to digitization. In cooperation projects, among others with Univ.-Prof. Dr. med. Julian Varghese from the Institute for Medical Informatics of the Westphalian Wilhelms-University (WWU) Münster, Jun.-Prof. Dr. Benjamin Risse from the Institute for Informatics of the WWU Münster and Prof. Dr. Arnim Malcherek from the Department of Informatics of the University of Applied Sciences Darmstadt, image analyses by means of artificial intelligence are the main focus of the joint research. The existence of large amounts of image data in ophthalmology and the expertise of the computer science experts in analyzing the data using machine learning form a perfect synergy. In the existing collaborations, clinically relevant issues are addressed and solved with the respective partners in the context of master's theses or term papers.
Telemedical networking is also the focus of a large collaborative project with Münster University Eye Hospital as the consortium leader. In the SALUS innovation fund project, the treatment of glaucoma patients is to be improved through self-tonometry and telemedical networking of clinics, practices and patients. In contrast to standard care, where an inpatient hospital stay is required for a daily tensio profile to check intraocular pressure values, the new, outpatient form of care investigated in the study allows patients to measure intraocular pressure independently and in their home environment. In addition, an electronic case file was designed in which all data of the study are included and can be viewed by the involved parties. For quality assurance of the data, there is also a reading center team consisting of several physicians who analyze the clinical data in a standardized process.
Such a reading center for standardized and systematic analysis of digital imaging for scientific ophthalmological studies already existed at the University Eye Hospital before the SALUS project. The Chair of Medical Informatics and the IT department of the Faculty of Medicine at the WWU played a leading role in the conception of the IT platform. A team of physicians and scientists from the Department of Ophthalmology, with a wealth of experience in clinical trials and in the application of numerous ophthalmic imaging techniques, is available to evaluate the data. Acquisition and analysis of image data are performed according to international study-specific protocols. The "Standard Operating Procedures" have been established according to the guidelines of the EVICR network and "Good Clinical Practice". The UKM Reading Center has additionally been certified according to DIN ISO 9001-2015 since 2017.
In collaboration with the German Ophthalmological Society, the pilot phase of oregis started in 2018. Oregis is the project of a nationwide digital registry for ophthalmology, which enables the possibility of sound health care research (Fig. 1). By connecting practices and clinics to oregis, anonymized treatment case data are centrally compiled in a database and made available for research purposes. The aim is to connect as many facilities in Germany as possible to the registry in order to be able to make valid statements about real care in Germany. There are various ways of transmitting data to the registry. The simplest variant is the transmission via connector modules, which automatically transfer the data from the practice or clinic information systems to oregis. It is also possible to feed the registry by uploading common file formats such as CSV files or even by manual input. The latter is especially relevant in clinics with still existing paper files. To ensure data security, a detailed data protection concept was developed for the registry in coordination with the Technology and Methodology Platform for Networked Medical Research (TMF) e.V., which complies with the principle of separation of informational powers.
Figure 1: Internet presence of the oregis registry of the German Ophthalmological Society.
In addition to digitization in patient care and research, the teaching concept of the University Eye Hospital has also been revised in recent years and supplemented with online learning content. The "Flipped Classroom" concept was already developed before the Corona pandemic in collaboration with the Institute for Training and Studies (IfAS) of the Medical Faculty of the University of Münster, thereby significantly facilitating the transition to distance learning. The teaching concept consists of a self-study component, which is completed online, and an attendance component, which builds on the teaching content of the self-study. The advantages of this concept are the uniform knowledge base created by the self-study, which can then be applied and deepened in the joint practical exercises.
In addition, since the Corona pandemic, the eye clinic has been conducting its continuing education events virtually and plans to hold events in hybrid form in the future. The nationwide accessibility through the online training courses is to be maintained and a combination with a face-to-face event will enable a personal exchange in the future.
Contact and further information:
Clinic for Ophthalmology, Münster University Hospital
WG Big Data, Health Services Research, Artificial Intelligence
Further reading:
UKM EyeNet:
Czapski, P et al. “FIDUSweb in der Version 2.0 : Möglichkeiten einer elektronischen Plattform zur Etablierung eines kooperativen, universitären Augennetzwerks” [FIDUSweb version 2.0 : An electronic platform to establish a cooperative university eye network]. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft vol. 117,7 (2020): 677-686. doi:10.1007/s00347-019-00993-7
Research Projects Artificial Intelligence:
Diener, R et al. “Diagnostik von Erkrankungen des Sehnervenkopfes in Zeiten von künstlicher Intelligenz und Big Data” [Diagnostics of diseases of the optic nerve head in times of artificial intelligence and big data]. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft, 1–6. 22 Apr. 2021, doi:10.1007/s00347-021-01385-6
Treder, M et al. “Künstliche Intelligenz zum Management von Makulaödemen : Chancen und Herausforderungen” [Artificial intelligence in management of macular edema : Opportunities and challenges]. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft vol. 117,10 (2020): 989-992. doi:10.1007/s00347-020-01110-9
Treder, Maximilian et al. “Using Deep Learning in Automated Detection of Graft Detachment in Descemet Membrane Endothelial Keratoplasty: A Pilot Study.” Cornea vol. 38,2 (2019): 157-161. doi:10.1097/ICO.0000000000001776
Treder, Maximilian et al. “Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier.” Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie vol. 256,11 (2018): 2053-2060. doi:10.1007/s00417-018-4098-2
Treder, Maximilian et al. “Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning.” Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie vol. 256,2 (2018): 259-265. doi:10.1007/s00417-017-3850-3
Reading Center:
Bruland, Philipp et al. “Integrating x4T-EDC into an Image-Portal to Establish an Ophthalmic Reading Center.” Studies in health technology and informatics vol. 245 (2017): 1254.
Flipped Classroom:
Lauermann, J L et al. „Flipped classroom“ – Ein Zukunftskonzept für die studentische Lehre in der Augenheilkunde?” ["Flipped classroom"-A future concept for student teaching in ophthalmology?]. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft vol. 118,7 (2021): 691-696. doi:10.1007/s00347-020-01225-z
Grabowski, E et al. “Analyse des Stellenwertes von „eLearning“ in der Augenheilkunde und Evaluierung einer „eLearning-App“” [Analysis of the importance of e-learning in ophthalmology and evaluation of an e-learning app]. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft vol. 117,12 (2020): 1218-1224. doi:10.1007/s00347-020-01100-x