Günter Schreier

• Austrian Institute of Technology

Background: Efficient appointment management is crucial in daycare units for eating disorders, where multidisciplinary teams coordinate various therapeutic sessions. Objectives: Establishing FHIR appointment management enhances scheduling efficiency, ensuring seamless communication between healthcare providers while enabling real-time updates fo...

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detection is essential for timely intervention; however, traditional diagnostic methods often lack scalability and accessibility. This project explores the use of photoplethysmography (PPG) signals recorde...

Efficient secondary use of real-world data (RWD) is a cornerstone for advancing data-driven medical research and personalised healthcare. However, significant challenges persist, including data fragmentation in silos, the lack of record linkage, and legal constraints that often hinder data utilisation. Especially Electronic Health Records (EHRs) re...

In refractory epilepsy and inherited metabolic disorders, Ketogenic Dietary Therapies (KDT) are established non-pharmacological treatments. Telemedicine might contribute to tackle various challenges related to KDT complexity and the respective target diseases. A questionnaire on the current use and future requirements was provided for health care p...

Background Telehealth has been effective in managing cardiovascular diseases like stroke and heart failure and has shown promising results in managing patients with peripheral arterial disease. However, more work is needed to fully understand the effect of telehealth-based predictive modeling on the physical fitness of patients with peripheral arte...

BACKGROUND Telehealth has been effective in managing cardiovascular diseases like stroke and heart failure and has shown promising results in managing patients with peripheral arterial disease (PAD). However, more work is needed to fully understand the effect of telehealth based predictive modelling on the physical fitness of PAD patients. OBJECTI...

Access to healthcare data for secondary use in clinical research is often restricted due to privacy concerns or business interests, hindering comprehensive analysis across patient pathways. The Smart FOX project seeks to address this challenge by developing concepts, methods, and tools to facilitate citizen/patient-driven donations of health data f...

The Survivorship Passport (SurPass) for childhood cancer survivors provides a personalized treatment summary together with a care plan for long-term screening of possible late effects. HL7 FHIR connectivity of Electronic Health Record (EHR) systems with the SurPass has been proposed to reduce the burden of collecting and organizing the relevant inf...

Secondary use of data for research purposes is especially important in rare diseases (RD), since, per definition, data are sparse. The European Joint Programme on Rare Diseases (EJP RD) aims at developing an RD infrastructure which supports the secondary use of data. Significant amounts of RD data are a) distributed and b) available only in pseudon...

Innovation in cancer therapy has increased childhood cancer survival rates. However, survivors are still at risk of developing late effects. In the digital transformation of the health sector, the Survivorship Passport (SurPass) can support long-term follow-up care plans. Gaps in seamless connectivity among hospital departments, primary care, combi...

Background: The recent rise of large language models has triggered renewed interest in medical free text data, which holds critical information about patients and diseases. However, medical free text is also highly sensitive. Therefore, de-identification is typically required but is complicated since medical free text is mostly unstructured. With t...

Simple Summary Large datasets concerning childhood cancers are rare. Therefore, it is important to fully exploit all available data, which are distributed over several resources, including biomaterials, images, clinical trials, and registries. With privacy-preserving record linkage (PPRL), datasets can be merged, without disclosing the patients’ id...

BACKGROUND The rapid increase in the number of health Apps and their volatility in (Austrian) App stores for Android and Apple are evidence of a flourishing business sector in the wellness industry. OBJECTIVE In this report, a checklist for informed decision-making by users was developed and evaluated using health Apps in the categories "Nutrition...

Background: Guidelines recommend walking trainings for peripheral arterial disease (PAD) management. Supervised walking training is superior to walking advise to improve the walking distance. Telehealth service with nurse support may close this gap. Patients and methods: This study introduces a telehealth service, “Keep pace!”, which has been devel...

Background To overcome knowledge gaps and optimize long-term follow-up (LTFU) care for childhood cancer survivors, the concept of the Survivorship Passport (SurPass) has been invented. Within the European PanCareSurPass project, the semiautomated and interoperable SurPass (version 2.0) will be optimized, implemented, and evaluated at 6 LTFU care ce...

Chronic wounds present a significant healthcare challenge in Austria as well as in other countries. The interdisciplinary approach to wound treatment involving various caregivers, doctors, and relatives, poses challenges in documentation and information exchange. To overcome these barriers and promote patient-centered care, a new telehealth-support...

The burgeoning domain of telehealth has witnessed substantial transformation through the advent of advanced technologies such as Large Language Models (LLMs). This study examines the integration of LLMs in heart failure management, with a focus on HerzMobil as a pioneering telehealth program. The technical underpinnings of LLMs, their current appli...

Background: Approximately 40% of all recorded deaths in Austria are due to behavioral risks. These risks could be avoided with appropriate measures. Objectives: Extension of the concept of EHR and EMR to an electronic prevention record, focusing on primary and secondary prevention. Methods: The concept of a structured prevention pathway, based...

Background: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, physical activity, and both device-measured and self-reported sleep quality. Objectives: The primar...

Ketogenic dietary therapies (KDT) are diets that induce a metabolic condition comparable to fasting. All types of KDT comprise a reduction in carbohydrates whilst dietary fat is increased up to 90% of daily energy expenditure. The amount of protein is normal or slightly increased. KDT are effective, well studied and established as non-pharmacologic...

Introduction The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health data is largely kept in isolated data silos and key infrastructure to aggregate these silos into standardized bodies of knowledge is underdeveloped. We describe the development, implementation, and evaluation of a federated inf...

BACKGROUND Home and telehealth-based interventions are increasingly used in cardiac rehabilitation (CR), a multidisciplinary model of health care. Digital tools such as wearables or digital training diaries are expected to support patients to adhere to recommended lifestyle changes, including physical exercise programmes. As previously published, t...

Background Home and telehealth-based interventions are increasingly used in cardiac rehabilitation, a multidisciplinary model of health care. Digital tools such as wearables or digital training diaries are expected to support patients to adhere to recommended lifestyle changes, including physical exercise programs. As previously published, the EPIC...

Telehealth services are becoming more and more popular, leading to an increasing amount of data to be monitored by health professionals. Machine learning can support them in managing these data. Therefore, the right machine learning algorithms need to be applied to the right data. We have implemented and validated different algorithms for selecting...

Artificial intelligence and machine learning have led to prominent and spectacular innovations in various scenarios. Application in medicine, however, can be challenging due to privacy concerns and strict legal regulations. Methods that centralize knowledge instead of data could address this issue. In this work, 6 different decentralized machine le...

BACKGROUND To overcome knowledge gaps and optimize long-term follow-up (LTFU) care for childhood cancer survivors, the concept of the Survivorship Passport (SurPass) has been invented. Within the European PanCareSurPass project, the semiautomated and interoperable SurPass (version 2.0) will be optimized, implemented, and evaluated at 6 LTFU care ce...

Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally,...

Background: The aging population's need for treatment of chronic diseases is exhibiting a marked increase in urgency, with heart failure being one of the most severe diseases in this regard. To improve outpatient care of these patients and reduce hospitalization rates, the telemedical disease management program HerzMobil was developed in the past....

Background: The daily increasing amount of health data from different sources like electronic medical records and telehealth systems go hand in hand with the ongoing development of novel digital and data-driven analytics. Unifying this in a privacy-preserving data aggregation infrastructure can enable services for clinical decision support in pers...

Purpose: Long-term follow-up (LTFU) care for childhood cancer survivors (CCSs) is essential to improve and maintain their quality of life. The Survivorship Passport (SurPass) is a digital tool which can aid in the delivery of adequate LTFU care. During the European PanCareSurPass (PCSP) project, the SurPass v2.0 will be implemented and evaluated a...

Heart failure (HF) is a chronic disease with high hospitalizations rates and increased mortality. The six-minute walk test (6MWT) is a standardized method to assess the functional health of HF patients by measuring the distance walked in six minutes [1]. The improved 6MWT with new filter algorithms, based on the development of smartphone applicatio...

Purpose: Artificial intelligence and machine learning have led to prominent and spectacular innovations in various scenarios. Application in medicine, however, can be challenging due to privacy concerns and strict legal regulations. Methods that centralize knowledge instead of data could address this issue. Methods: In this work, 6 different decent...

Background: Clinical notes provide valuable data in telemonitoring systems for disease management. Such data must be converted into structured information to be effective in automated analysis. One way to achieve this is by classification (e.g. into categories). However, to conform with privacy regulations and concerns, text is usually de-identifi...

The demand for extended care for people suffering from heart failure is omnipresent. Wearables providing continuous heart rate measurement through optical sensors are of great interest due to their ease of use without the need for medical staff and their low cost. In this study, seven wearables were tested in fifteen measurement runs, with a durati...

Background: Python and MATLAB both are common tools used for predictive modelling applications, not only in healthcare. In our predictive modelling group, both tools are widely used. None of the two tools is optimal for all tasks along the value chain of predictive modelling in healthcare. Objectives: The aim of this study was to explore differe...

Background: Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission.

Frailty is one of the major problems associated with an aging society. Therefore, frailty assessment tools which support early detection and autonomous monitoring of the frailty status are heavily needed. One of the most used tests for functional assessment of the elderly is the “Timed Up-and-Go” test. In previous projects, we have developed an ult...

Background: Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission. Objective: This study aims to investigate the feasibil...

BACKGROUND Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission. OBJECTIVE This study aims to investigate the feasibility,...

Telehealth services for long-term monitoring of chronically ill patients are becoming more and more common, leading to huge amounts of data collected by patients and healthcare professionals each day. While most of these data are structured, some information, especially concerning the communication between the stakeholders, is typically stored as u...

Introduction: Mobile phone-based interventions in cardiovascular disease are growing in popularity. A randomised control trial (RCT) for a novel smartphone app-based model of care, named TeleClinical Care - Cardiac (TCC-Cardiac), commenced in February 2019, targeted at patients being discharged after care for an acute coronary syndrome or episode o...

Background There is rising concern on the impact of new strategies, such as high-dose chemotherapy (HDC) and immunotherapy, on the pattern of relapse in high-risk neuroblastoma (HR-NBL). Our aim is to evaluate the incidence and identify risk factors for first recurrence in the central nervous system (CNS) in HR-NBL. Patients and methods Data from...

Objective: A third of people over 65 years experiences at least one fall a year. The Timed Up-and-Go test is commonly used to assess gait and balance and to evaluate an individual's risk of falling. Approach: We conducted a clinical study with 46 older participants for evaluating the fall risk assessment capabilities of an ultra-sound based Time...

Machine Learning research and its application have gained enormous relevance in recent years. Their usage in medical settings could support patients, increase patient safety and assist health professionals in various tasks. However, medical data is often sparse, which renders big data analytics methods like deep learning ineffective. Data synthesis...

Background: Privacy-preserving record linkage (PPRL) is the process of detecting dataset entries that refer to the same individual within two independent datasets, without disclosing any personal information. While applied in different fields, it particularly attained importance in the medical sector. One popular PPRL method are Bloom filters. How...

Background: Heart failure is a chronic disease that affects around 26 million people worldwide. Projections assume a substantial increase in prevalence over the next years. To improve the survival rate and quality of life in patients suffering from heart failure, the European Society of Cardiology published guidelines for diagnosis and treatment....

Heart Failure is a severe chronic disease of the heart. Telehealth networks implement closed-loop healthcare paradigms for optimal treatment of the patients. For comprehensive documentation of medication treatment, health professionals create free text collaboration notes in addition to structured information. To make this valuable source of inform...

With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machine-learning techniques demonstrated their applications in healthcare to answer several questions, there is still room for improvement in every aspect. In this paper, we are demonstrating a method that...

Life expectancy is rising in most parts of the world as is the prevalence of chronic diseases. Suboptimal adherence to long‐term medications is still rather the norm than the exception, although it is well known that suboptimal adherence compromises the therapeutic effectiveness. Information and communications technology provides new concepts for i...

Versorgungsnetzwerke mit Telegesundheitsdiensten als kollaboratives virtuelles Netzwerk mit einem interdisziplinären Betreuungsteam werden zukünftig für die ambulante als auch mobile Rehabilitation zur Überwindung der Barrieren in Raum, Zeit und über Institutionen hinweg von Bedeutung sein. Quantifizierbares, kontrolliertes Training als Therapiefor...

Background: Huge amounts of data are collected by healthcare providers and other institutions. However, there are data protection regulations, which limit their utilisation for secondary use, e.g. Research: In scenarios, where several data sources are obtained without universal identifiers, record linkage methods need to be applied to obtain a c...

Background: Predictive modelling is becoming increasingly important in the healthcare sector. A comprehensive understanding of obtained models and their predictions is indispensable for the development and later acceptance of such systems. Objectives: A general concept of a toolset that supports data scientists in the development of predictive m...

Adoption of electronic medical records in hospitals generates a large amount of data. Health care professionals can easily lose their sight on the important insights of the patients' clinical and medical history. Although machine learning algorithms have already proved their significance in healthcare research, remains a challenge translation and d...

Background: In a database of electronic health records, the amount of available information varies widely between patients. In a real-time prediction scenario, a machine learning model may receive limited information for some patients. Objectives: Our aim was to evaluate the influence of missing data on real-time prediction of delirium, and dete...

Background: Immunotherapy with the chimeric anti-GD2 monoclonal antibody dinutuximab, combined with alternating granulocyte-macrophage colony-stimulating factor and intravenous interleukin-2 (IL-2), improves survival in patients with high-risk neuroblastoma. We aimed to assess event-free survival after treatment with ch14.18/CHO (dinutuximab beta)...

Objective: Recent advantages in mHealth-enabled ECG recorders boosted the demand for algorithms, which are able to automatically detect cardiac anomalies with high accuracy. Approach: We present a combined method of classical signal analysis and machine learning which has been developed during the Computing in Cardiology Challenge (CinC) 2017. A...

Due to an ever-increasing amount of data generated in healthcare each day, healthcare professionals are more and more challenged with information. Predictive models based on machine learning algorithms can help to quickly identify patterns in clinical data. Requirements for data driven decision support systems for health and care ( DS4H ) are simil...

Background: Under the ExPO-r-NeT project (European Expert Paediatric Oncology Reference Network for Diagnostics and Treatment), we aimed to identify paediatric oncology tumour boards in Europe to investigate the kind of technologies and logistics that are in place in different countries and to explore current differences between regions. Methods:...

Delirium is an acute neuropsychiatric syndrome which is common in elderly patients during their hospitalisation and is associated with an increased mortality and morbidity. Since delirium is a) often underdiagnosed and b) preventable if early signs are detected,igh expectations are set in delirium risk assessment during hospital admission. In our l...

E-Bikes in telerehabilitation programs could be a new intervention for more sustainable rehabilitation results. The aim is to design and build a prototype of an E-Bike usable for rehabilitation - a HEALTHeBIKE. It should avoid over-exercising, work independently of the environment and it should enable cycling in a group despite different reference...

Digitalisation of health care for the purpose of medical documentation lead to huge amounts of data, hence having an opportunity to derive knowledge and associations of different attributes recorded. Many health care events can be prevented when identified. Machine learning algorithms could identify such events but there is ambiguity in understandi...

Hospital readmissions receive increasing interest, since they are burdensome for patients and costly for healthcare providers. For the calculation of reimbursement fees, in Germany there is the German-Diagnosis Related Groups (G-DRG) system. For every hospital stay, data are collected as a so-called "case", as the basis for the subsequent reimburse...

Systematic reviews are widely used as a tool for decision making to establish new clinical guidelines. Reviews can be time-consuming, potentially leaving authors with thousands of citations to screen. Software tools for assisting reviewers in this process are available, however, only few use text mining techniques to reduce screening time. In this...

Unplanned hospital readmissions are a burden to the healthcare system and to the patients. To lower the readmission rates, machine learning approaches can be used to create predictive models, with the intention to provide actionable information for caregivers. According to the German Diagnosis Related Groups (G-DRG) system, for every stay in a Germ...

A pilot study was conducted to determine if a smartphone-based adjunct to standard care could increase the completion rate of a cardiac rehabilitation program (CRP). Based on historical completion rates, sixty-six participants who were about to commence a hospital-based CRP were randomized so that half received three devices embedded with near-fiel...

Background: Blood transfusion is a highly prevalent procedure in hospitalized patients and in some clinical scenarios it has lifesaving potential. However, in most cases transfusion is administered to hemodynamically stable patients with no benefit, but increased odds of adverse patient outcomes and substantial direct and indirect cost. Therefore,...

Objectives: In the context of the present meta-analysis, key cost indicators from the perspective of healthcare providers are to be identified, described, analyzed and quantified. This review helps narrowing down the cost indicators, which have the most significant economic impact on the total treatment costs of HF patients. Telemedical services a...

Background: High-dose chemotherapy with haemopoietic stem-cell rescue improves event-free survival in patients with high-risk neuroblastoma; however, which regimen has the greatest patient benefit has not been established. We aimed to assess event-free survival after high-dose chemotherapy with busulfan and melphalan compared with carboplatin, eto...

Delirium is an acute confusion condition, which is common in elderly and often misdiagnosed in hospitalized patients. Early identification and prevention of delirium could reduce morbidity and mortality rates in those affected and reduce hospitalization costs. We have developed and validated a multivariate prediction model that predicts delirium an...

The policies that address health information exchanges for research purposes in Australia, Austria, Finland, Switzerland, and the USA apply accountability and/or adequacy to protect privacy. Specific requirements complicate the exchanges: inform data subjects of data use purposes; assure that the subjects are no longer identifiable; destroy the dat...

Background: Automatic event detection is used in telemedicine based heart failure disease management programs supporting physicians and nurses in monitoring of patients' health data. Objectives: Analysis of the performance of automatic event detection algorithms for prediction of HF related hospitalisations or diuretic dose increases. Methods:...

Background: Machine learning algorithms are a promising approach to help physicians to deal with the ever increasing amount of data collected in healthcare each day. However, interpretation of suggestions derived from predictive models can be difficult. Objectives: The aim of this work was to quantify the influence of a specific feature on an in...

Functional evaluation of elderly patients is one key component in a comprehensive Geriatric Assessment. The increased workload and high costs associated to close and continuous monitoring in clinical settings may be counterbalanced by the application of ICT-supported remote follow-up. Although clinical parameters and questionnaires can be supported...

Capabilities to exchange health information are critical to accelerate discovery and its diffusion to healthcare practice. However, the same ethical and legal policies that protect privacy hinder these data exchanges, and the issues accumulate if moving data across geographical or organizational borders. This can be seen as one of the reasons why m...

Objectives A post hoc gender comparison of transfusion-related modifiable risk factors among patients undergoing elective surgery. Settings 23 Austrian centres randomly selected and stratified by region and level of care. Participants We consecutively enrolled in total 6530 patients (3465 women and 3065 men); 1491 underwent coronary artery bypass...

Objectives: As wearable sensors take the consumer market by storm, and medical device manufacturers move to make their devices wireless and appropriate for ambulatory use, this revolution brings with it some unintended consequences, which we aim to discuss in this paper. Methods: We discuss some important unintended consequences, both beneficial...

Non-adherence to a drug therapy is often the reason for not achieving the therapeutic goals in patients. Thus, measuring and monitoring drug adherence is an important aspect to understand patients’ adherence patterns and behavior as well as to provide supportive measures to enhance or reestablish adherence to a prescribed regimen. A variety of diff...

Introduction: This was a pilot study to examine the effects of home telemonitoring (TM) of patients with severe chronic obstructive pulmonary disease (COPD). Methods: A randomised controlled 12-month trial of 42 patients with severe COPD was conducted. Home TM of oximetry, temperature, pulse, electrocardiogram, blood pressure, spirometry, and we...

Health insurers maintain large databases containing information on medical services utilized by claimants, often spanning several healthcare services and providers. Proper use of these databases could facilitate better clinical and administrative decisions. In these data sets, there exists many unequally spaced events, such as hospital visits. Howe...

With the Directive 2011/24/EU on patients' rights in cross-border healthcare and the related delegated decisions, the European Commission defined a legal framework on how healthcare shall be organised by European Union (EU) member states (MS) where patients can move beyond the borders of their home country. Among other aspects, Article 12 of the di...

Data from two contexts, i.e. the European Unresectable Neuroblastoma (EUNB) clinical trial and results from comparative genomic hybridisation (CGH) analyses from corresponding tumour samples shall be provided to existing repositories for secondary use. Utilizing the European Unified Patient IDentity Management (EUPID) as developed in the course of...

Research in blood transfusions mainly focuses on Donor Blood Management, including donation, screening, storage and transport. However, the last years saw an increasing interest in recipient related optimizations, i.e. Patient Blood Management (PBM). Although PBM already aims at reducing transfusion rates by pre- and intra-surgical optimization, th...

Opsoclonus Myoclonus Syndrome (OMS) is a rare disease in children which is often associated with neuroblastoma and, therefore, requires treatment by pediatric neurologists and oncologists. The ongoing OMS trial investigates questions related to OMS and potentially underlying neuroblastomas. To support this trial with an adequate IT infrastructure,...

Continual monitoring of patients utilizing mHealth-based telemonitoring applications are more and more used for individual management of patients. A new approach in risk assessment called Rolling Score Concept uses standardized questionnaires for continual scoring of individuals' health state through electronic patient reported outcome (ePRO). Usin...

Background: Electronic Patient Reported Outcomes (ePRO) gathered using telemonitoring solutions might be a valuable source of information in rare cancer research. Objectives: The objective of this paper was to develop a concept and implement a prototype for introducing ePRO into the existing neuroblastoma research network by applying Near Field...