Expansion of patient eligibility for virtual glaucoma clinics: a long-term strategy to increase the capacity of high-quality glaucoma care.

AIMS: The virtual glaucoma clinic (VGC) is a well-established diagnostic pathway for delivery of glaucoma care. Current UK national guidance recommends VGCs for patients with ocular hypertension, glaucoma suspects or early glaucoma. This study evaluates whether expanded eligibility criteria, including other glaucoma phenotypes and disease stages, can deliver safe and effective care with a positive patient experience. METHODS: Records of over 8000 patients were reviewed in order to determine suitability for VGC attendance using expanded eligibility criteria. Patients with three prior consecutive visits within the glaucoma service were included. Follow-up interval, clinic type, visual acuity (VA), intraocular pressure (IOP) and visual field performance were recorded. Patient satisfaction was recorded for a sample of 118 patients. RESULTS: 2017 patients over 31 months were included. Two-thirds of eyes had ocular comorbidities, a fifth of eyes had undergone prior cataract surgery and 10% of eyes had undergone a prior laser treatment for glaucoma. After three visits, 32% of patients remained in the VGC, 42% were seen in face-to-face clinics and 25% were discharged. There were no clinically significant changes in VA, IOP and visual field performance during follow-up. 72% of patients expressed a preference to continue their care within VGCs. CONCLUSIONS: This study demonstrates that VGCs with expanded patient eligibility criteria can deliver high-quality glaucoma care that is safe, effective and with high levels of patient satisfaction. This approach provides a long-term solution to adapt delivery of glaucoma care to our expanding and ageing population.

Smartphone-Based Data Collection in Ophthalmology. / Smartphone-basierte Datenerhebung in der Augenheilkunde.

Due to their widespread use among the population and their wide range of functions and sensors, smartphones are suitable for data collection for medical purposes. App-supported input masks, patient diaries, and patient information systems, mobile access to the patient file as well as telemedical services will continue to find their way into our field of expertise in the future. In addition, the use of smartphone sensors (GPS and motion sensors, touch display, microphone) and coupling possibilities with biosensors (for example with Continuous Glucose Monitoring [CGM] systems), advanced camera technology, the possibility of regular and appointment independent checking of the visual system (visual acuity/contrast vision) as well as real-time data transfer offer interesting possibilities for patient treatment and clinical research. The present review deals with the current status and future perspectives of smartphone-based data collection and possible applications in ophthalmology.

[Artificial intelligence in ophthalmology : Guidelines for physicians for the critical evaluation of studies]. / Künstliche Intelligenz in der Augenheilkunde : Leitfaden für Ärzte zur kritischen Bewertung von Studien.

BACKGROUND: Empirical models have been an integral part of everyday clinical practice in ophthalmology since the introduction of the Sanders-Retzlaff-Kraff (SRK) formula. Recent developments in the field of statistical learning (artificial intelligence, AI) now enable an empirical approach to a wide range of ophthalmological questions with an unprecedented precision. OBJECTIVE: Which criteria must be considered for the evaluation of AI-related studies in ophthalmology? MATERIAL AND METHODS: Exemplary prediction of visual acuity (continuous outcome) and classification of healthy and diseased eyes (discrete outcome) using retrospectively compiled optical coherence tomography data (50 eyes of 50 patients, 50 healthy eyes of 50 subjects). The data were analyzed with nested cross-validation (for learning algorithm selection and hyperparameter optimization). RESULTS: Based on nested cross-validation for training, visual acuity could be predicted in the separate test data-set with a mean absolute error (MAE, 95% confidence interval, CI of 0.142 LogMAR [0.077; 0.207]). Healthy versus diseased eyes could be classified in the test data-set with an agreement of 0.92 (Cohen's kappa). The exemplary incorrect learning algorithm and variable selection resulted in an MAE for visual acuity prediction of 0.229 LogMAR [0.150; 0.309] for the test data-set. The drastic overfitting became obvious on comparison of the MAE with the null model MAE (0.235 LogMAR [0.148; 0.322]). CONCLUSION: Selection of an unsuitable measure of the goodness-of-fit, inadequate validation, or withholding of a null or reference model can obscure the actual goodness-of-fit of AI models. The illustrated pitfalls can help clinicians to identify such shortcomings.

[Medial retina clinics in 2030 : A peek into the future]. / Netzhautsprechstunde im Jahr 2030 : Ein Ausblick in die Zukunft.

Ophthalmology is subject to constant change. Almost two decades ago the OCT (optical coherence tomography) technology was introduced into ophthalmological practice. Nowadays, artificial intelligence and telemedicine are talked about everywhere. This article gives an overview of the tools currently available in both fields. As an outlook into the year 2030, the working day of an ophthalmologist is described. All innovations discussed in this article will be available in clinical practice by then.

Long-term database analysis of conventional and accelerated crosslinked keratoconic mid-European eyes.

PURPOSE: To investigate the long-term efficacy of accelerated corneal collagen cross-linking (CXL) in a large mid-European cohort with progressive keratoconus. METHODS: Four hundred thirteen eyes of 316 patients with progressive keratoconus were enrolled and treated with conventional (group A) or accelerated (group B) CXL. Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), slit lamp, and Pentacam® examinations were performed before and 12, 24, and 36 months after surgery. Maximum and mean anterior keratometry (Kmax, Kmf), corneal topography indices, and corneal pachymetry (TCT) were examined within each group and between groups. Further subgroup analysis of mild and moderate keratoconic eyes was performed. RESULTS: One hundred thirty-one eyes of 101 patients were treated in group A, 282 eyes of 215 patients in group B. (UDVA, CDVA) and Kmax improved within each group, but not statistically significantly between groups after 36 months (p = 0.081, p = 0.344, p = 0.113, respectively). Kmf remained stable in both groups. TCT decreased significantly in group A (p = 0.014), but remained stable in group B (p = 0.063). Subgroup analysis showed similar results with improvement in visual acuity and keratometry and decrease of TCT. Corneal topography indices showed no differences between the groups after 36 months, but developed differently in the subgroup analysis. No correlation was detected between the change of corneal topography indices and TCT with regard to preoperative Kmax. CONCLUSION: In a large mid-European study population including subgroup analysis of mild and moderate keratoconus, accelerated CXL showed similar results to conventional CXL regarding keratometry, corneal topography indices, and CDVA, but further improvement of UDVA. Preoperative Kmax did not affect the postoperative course of corneal topography indices and TCT.

[Required Framework for the Collection of Real-life Data: An Example from University Eye Hospital Munich]. / Rahmenbedingungen zur Sammlung von "Real-Life"-Daten am Beispiel der Augenklinik der Universität München.

Background The importance of evaluating real-life data is constantly increasing. Currently available computer systems better allow for analyses of data, as more and more data is available in a digital form. Before a project for real-life data analyses is started, technical considerations and staff, legal, and data protection procedures need to be addressed. In this manuscript, experiences made at the University Eye Hospital in Munich will be shared. Materials and Methods Legal requirements, as found in laws and guidelines governing documentation and data privacy, are highlighted. Technical requirements for information technology infrastructure and software are defined. A survey conducted by the German Ophthalmological Society, among German eye hospitals investigating the current state of digitalization, was conducted. Also, staff requirements are outlined. Results A database comprising results of 330,801 patients was set up. It includes all diagnoses, procedures, clinical findings and results from diagnostic devices. This database was approved by the local data protection officer. In less than half of German eye hospitals (n = 21) that participated in the survey (n = 54), a complete electronic documentation is done. Fourteen institutions are completely paper-based, and the remainder of the hospitals used a mixed system. Conclusion In this work, we examined the framework that is required to develop a comprehensive database containing real-life data from clinics. In future, these databases will become increasingly important as more and more innovation are made in decision support systems. The base for this is comprehensive and well-curated databases.

Using Electronic Health Records to Build an Ophthalmologic Data Warehouse and Visualize Patients' Data.

PURPOSE: To develop a near-real-time data warehouse (DW) in an academic ophthalmologic center to gain scientific use of increasing digital data from electronic medical records (EMR) and diagnostic devices. DESIGN: Database development. METHODS: Specific macular clinic user interfaces within the institutional hospital information system were created. Orders for imaging modalities were sent by an EMR-linked picture-archiving and communications system to the respective devices. All data of 325 767 patients since 2002 were gathered in a DW running on an SQL database. A data discovery tool was developed. An exemplary search for patients with age-related macular degeneration, performed cataract surgery, and at least 10 intravitreal (excluding bevacizumab) injections was conducted. RESULTS: Data related to those patients (3 142 204 diagnoses [including diagnoses from other fields of medicine], 720 721 procedures [eg, surgery], and 45 416 intravitreal injections) were stored, including 81 274 optical coherence tomography measurements. A web-based browsing tool was successfully developed for data visualization and filtering data by several linked criteria, for example, minimum number of intravitreal injections of a specific drug and visual acuity interval. The exemplary search identified 450 patients with 516 eyes meeting all criteria. CONCLUSIONS: A DW was successfully implemented in an ophthalmologic academic environment to support and facilitate research by using increasing EMR and measurement data. The identification of eligible patients for studies was simplified. In future, software for decision support can be developed based on the DW and its structured data. The improved classification of diseases and semiautomatic validation of data via machine learning are warranted.

Incidence of secondary glaucoma after treatment of uveal melanoma with robotic radiosurgery versus brachytherapy.

PURPOSE: Different modalities of radiation therapy nowadays allow for effective treatment of uveal melanoma combined with the advantage of eye preservation. However, this advantage can secondarily be impaired by radiation-related side effects. After local recurrence, secondary glaucoma (SG) has been described as second most frequent complication leading to need of enucleation. This study compares the incidence of SG after conventional Ruthenium (Ru)-106 brachytherapy (BT) versus CyberKnife robotic radiosurgery (RRS) which has been gaining importance lately as an efficient treatment option offering improved patient comfort. METHODS: Medical records of all patients diagnosed with uveal melanoma in the Eye Clinic of the Ludwig-Maximilians-University Munich between 2007 and 2013 were reviewed. A total of 268 eyes of 268 patients treated with Ru-106 BT or CyberKnife-RRS as monotherapy were entered in this retrospective cohort study. Incidence of SG was correlated with treatment modality and baseline tumour characteristics. RESULTS: Fifty-three patients (19.8%) developed SG. At 5 years, SG was significantly more frequent after RRS (46.7%) than BT (11.1%); however, tumour thickness (maximum apical height) as a marker of tumour progress was more pronounced in the RRS group. Subgroup analysis of 178 patients for tumours amenable to both BT and RRS (thickness ≤6 mm) revealed comparable results at 3 years (RRS: 13.8 versus BT: 11.2%), but a trend towards increased incidence after RRS beyond year three. However, this difference was not significant at 5 years (28.2% versus 11.2%, p = 0.138). Tumour thickness was significantly associated with incidence of SG. CONCLUSION: In tumours ≤6 mm thickness, RRS and BT seem to offer a comparable safety profile in terms of SG. Beyond year three, SG was tendentially, but not significantly more frequent after RRS. Increasing tumour thickness is associated with risk of SG.

Correlation between weather and incidence of selected ophthalmological diagnoses: a database analysis.

PURPOSE: Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. PATIENTS AND METHODS: For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of "conjunctivitis", "foreign body", "acute iridocyclitis", and "corneal abrasion". A Spearman's correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. RESULTS: We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. CONCLUSION: The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation.

The influence of a specific ophthalmological electronic health record on ICD-10 coding.

BACKGROUND: A specific Electronic Health Record (EHR) for ophthalmology was introduced in an academic center in Germany. As diagnoses coding corresponding to the International Classification of Diseases Version 10 (ICD-10) is mandatory for billing reasons in Germany, we analyzed whether a change occurred in the diversity and number of diagnoses after the EHR introduction. The number of patients was also analyzed. Proper diagnoses coding is of the utmost importance for further data analysis or billing. METHODS: Graphical User Interfaces (GUIs) were created by using Advanced Business Application Programming language in EHR "i.s.h.med." Development of an EHR was conducted in close collaboration between physicians and software engineers. ICD-10 coding was implemented by using a "hit list" and a search engine for diagnoses. An observational analysis of a 6-month period prior to and after the introduction of an ophthalmological specific EHR was conducted by investigating the diversity and number of diagnoses in various ophthalmological disease categories and the number of patient consultations. RESULTS: During the introduction of a specific ophthalmological EHR, we observed a significant increase in the emergency department cases (323.9 vs. 359.9 cases per week), possibly related to documentation requirements. The number of scheduled outpatients didn't change significantly (355.12 vs. 360.24 cases per week). The variety of diagnoses also changed: on average, 156.2 different diagnoses were made per week throughout our hospital before the EHR launch, compared to 186.8 different diagnoses per week thereafter (p < 0.05). Additionally, a significantly higher number of diagnoses per case and per week were observed in both emergency and subspecialty outpatient clinics (1.15 vs. 1.22 and 1.10 vs. 1.47, respectively). CONCLUSIONS: An optimized EHR was created for ophthalmological needs and for simplified ICD-10 coding. The implementation of digital patient recording increased the diversity of the diagnoses used per case as well as the number of diagnoses coded per case. A general limitation to date is the suboptimal precision of ICD-10 coding in ophthalmology. Correct coding is of utmost importance for future data analysis.