[OPTINOFA-Intelligent assistance service for structured assessment in the emergency department]. / OPTINOFA ­ Intelligenter Assistenzdienst zur strukturierten Ersteinschätzung in der Notaufnahme.

BACKGROUND: Case numbers in central emergency departments (EDs) have risen during the past decade in Germany, leading to recurrent overcrowding, increased risks in emergency care, and elevated costs. Particularly the fraction of outpatient emergency treatments has increased disproportionately. Within the framework of the Optimization of emergency care by structured triage with intelligent assistant service (OPTINOFA, Förderkennzeichen [FKZ] 01NVF17035) project, an intelligent assistance service was developed. PATIENTS AND METHODS: New triage algorithms were developed for the 20 most frequent leading symptoms on the basis of established triage systems (emergency severity index, ESI; Manchester triage system, MTS) and provided as web-based intelligent assistance services on mobile devices. To evaluate the validity, reliability, and safety of the new OPTINOFA triage instrument, a pilot study was conducted in three EDs after ethics committee approval. RESULTS: In the pilot study, n = 718 ED patients were included (age 59.1 ± 22 years; 349 male, 369 female). With respect to disposition (out-/inpatient), a sensitivity of 91.1% and a specificity of 40.7%, and a good correlation with the OPTINOFA triage levels were detected (Spearman's rank correlation ρ = 0.41). Furthermore, the area under the curve (AUC) for prediction of disposition according to the OPTINOFA triage level was 0.73. The in-hospital mortality rate of OPTINOFA triage levels 4 and 5 was 0%. The association between the length of ED stay and the OPTINOFA triage level was shown to be significant (p < 0.001). CONCLUSION: The results of the pilot study demonstrate the safety and validity of the new triage system OPTINOFA. By definition of both urgency and emergency care level, new customized perspectives for load reduction in German EDs via a closer cooperation between out- and inpatient sectors of emergency care could be established.

Development of a Clinical Decision Support System for Smart Algorithms in Emergency Medicine.

The development of clinical decision support systems (CDSS) is complex and requires user-centered planning of assistive interventions. Especially in the setting of emergency care requiring time-critical decisions and interventions, it is important to adapt a CDSS to the needs of the user in terms of acceptance, usability and utility. In the so-called ENSURE project, a user-centered approach was applied to develop the CDSS intervention. In the context of this paper, we present a path to the first mockup development for a CDSS interface by addressing Campbell's Five Rights within the CDSS workflow.

Automated Size Recognition in Pediatric Emergencies Using Machine Learning and Augmented Reality: Within-Group Comparative Study.

BACKGROUND: Pediatric emergencies involving children are rare events, and the experience of emergency physicians and the results of such emergencies are accordingly poor. Anatomical peculiarities and individual adjustments make treatment during pediatric emergency susceptible to error. Critical mistakes especially occur in the calculation of weight-based drug doses. Accordingly, the need for a ubiquitous assistance service that can, for example, automate dose calculation is high. However, few approaches exist due to the complexity of the problem. OBJECTIVE: Technically, an assistance service is possible, among other approaches, with an app that uses a depth camera that is integrated in smartphones or head-mounted displays to provide a 3D understanding of the environment. The goal of this study was to automate this technology as much as possible to develop and statistically evaluate an assistance service that does not have significantly worse measurement performance than an emergency ruler (the state of the art). METHODS: An assistance service was developed that uses machine learning to recognize patients and then automatically determines their size. Based on the size, the weight is automatically derived, and the dosages are calculated and presented to the physician. To evaluate the app, a small within-group design study was conducted with 17 children, who were each measured with the app installed on a smartphone with a built-in depth camera and a state-of-the-art emergency ruler. RESULTS: According to the statistical results (one-sample t test; P=.42; α=.05), there is no significant difference between the measurement performance of the app and an emergency ruler under the test conditions (indoor, daylight). The newly developed measurement method is thus not technically inferior to the established one in terms of accuracy. CONCLUSIONS: An assistance service with an integrated augmented reality emergency ruler is technically possible, although some groundwork is still needed. The results of this study clear the way for further research, for example, usability testing.

Towards a Ubiquitous Child Emergency App - Ideas to Simplify and Ensure the Machine-2-Machine Communication.

Medical emergencies involving children are rare events. The experience of emergency physicians is therefore low and the results are correspondingly poor. Assistance services to help in emergencies are regularly requested. The use case is thus very complicated, a complex system consisting of multiple devices is necessary to provide the most efficient and effective service. This short paper presents prototypically tested ideas on how such a ubiquitous approach can be designed and how communication between devices can be simplified and ensured.

Mobile Robotic Telepresence Between Hospital and School: Lessons Learned.

If a pupil falls seriously ill, it is not only a shock for the pupil himself or herself, but also for his or her family and classmates. The project "Virtual Classroom" of the Heilbronn University in cooperation with the foundation "Big Help for Little Heroes" therefore tries to maintain the daily school routine and thus the contact with friends as far as possible with the help of mobile telepresence robots in the classroom from home or from the hospital. Here there are both technical and human factors that contribute to success or failure. Based on a systematic literature research and practical experience, these factors are identified, discussed and weighted in this paper. If the mobile telepresence robot is used successfully, this pays off twice for the pupils affected: It has been shown that pupils can progress socially as well as in school, even if attendance at school is not possible for a long time.

Speech Recognition Evaluation of a State-Of-The-Art Smartglass in the Use Case Pediatric Resuscitation.

Emergencies involving children are rare events. Due to the associated lack of routine and special features in pediatric resuscitation, it is prone to errors and the results are unsatisfactory. One way of tackling this problem is to use assistance services. However, due to the process, these services cannot be easily integrated. One possibility is the use of Head Mounted Displays. These are often controlled via voice commands. With medical terms, the voice control implemented as standard can quickly become unusable. A wearable app was therefore developed for this paper and evaluated according to ISO/IEC 30122-2:2017 to determine the extent to which the voice control of a state-of-the-art smartglass works in quiet and noisy conditions for use during a resuscitation. Since the commands were well understood and the app could be reliably controlled, the use of voice control in an assistance service is conceivable.

Evaluation of Depth Cameras for Use as an Augmented Reality Emergency Ruler.

Children are rarely affected by medical emergencies. The experience of doctors or paramedics with child emergencies is correspondingly poor. The anatomical features and individual calculations make such an emergency much more error-prone than a comparable adult emergency. Particularly in dose calculations, critical errors occur time and again. Since these calculations are based on the child's weight, which is preclinically often derived from the size of the child, the number of errors can be minimized with an assistance service that performs all calculations based on the size. Technically, it is possible to detect the size with a depth camera, which is occasionally installed in smartphones or head-mounted displays. In order to investigate to what extent these cameras provide precise results, a study with 33 children was carried out. The children were measured with both an emergency ruler and an augmented reality app with associated smartphone with depth camera. The result is that the depth camera does not provide significantly different results than an emergency ruler. This allows further research, e.g. the automatic recognition of patients with the help of machine learning or usability studies, to be tackled.

Wearable Technology in Medicine: Machine-to-Machine (M2M) Communication in Distributed Systems.

Smart wearables are capable of supporting physicians during various processes in medical emergencies. Nevertheless, it is almost impossible to operate several computers without neglecting a patient's treatment. Thus, it is necessary to set up a distributed network consisting of two or more computers to exchange data or initiate remote procedure calls (RPC). If it is not possible to create flawless connections between those devices, it is not possible to transfer medically relevant data to the most suitable device, as well as to control a device with another one. This paper shows how wearables can be paired and what problems occur when trying to pair several wearables. Furthermore, it is described as to what interesting scenarios are possible in the context of emergency medicine/paramedicine.

Development of an accommodative smartphone app for medical guidelines in pediatric emergencies.

One of the outcomes of a training concept for physicians and nurses concerning pediatric emergencies at the Heidelberg University Hospital was that the work and procedures in childhood emergencies could be simplified by replacing the existing paper-based guidelines with a smartphone app. Since the project funds for this were already used up, a group of students from the master program "Medical Informatics" of Heidelberg and Heilbronn Universities took over the development of the app. Particular attention was given to the need for compatibility with the variety of devices (device size and screen resolution) and platform independence. The guidelines themselves were scripted in HTML5, JavaScript and CSS (responsive web design); managed by a container programmed in Sencha Touch. Even though the app is not yet available in the App-Store due to the limited timeframe, the students gained a great deal of valuable experience in developing platform independent software for mobile devices.