Hypertension (HTN) is the leading global risk factor for premature death and disability. In Austria, as in many countries, treatment and blood pressure (BP) control rates are suboptimal. Previous studies have revealed low target achievement rates, emphasizing the need for innovative care models. Disease management programs (DMPs), particularly when supported by telemedicine, offer structured, coordinated approaches that can enhance care, adherence, and outcomes. This position paper outlines the rationale, structure, and implementation considerations for a telemedicine-supported DMP for hypertensive patients in Austria. It aims to define inclusion criteria, technological infrastructure, creation of a health professional network, recruitment strategies, and expected outcomes to guide future deployment. The paper synthesizes existing epidemiological data from Austrian and international sources, reviews evidence from comparable telemedical interventions (e.g., the HERB system in Japan, HerzMobil in Austria), and integrates perspectives from healthcare providers and social security organizations. It proposes a model combining home-based BP monitoring, digital tools, and interdisciplinary support through a centralized coordination center. Existing Austrian telehealth platforms have successfully implemented similar models in heart failure and diabetes care. A pilot in Tyrol (HerzMobil HTN) showed improved control of hypertension. A nationwide DMP for HTN in Austria leveraging telemedical tools is both feasible and urgently needed. Key success factors include clear inclusion criteria, technology access, comprehensive training, multidisciplinary collaboration, and patient recruitment strategies. Such a program promises improved BP control, reduced cardiovascular events, and long-term healthcare cost savings.

Background:Guideline-directed medical therapy (GDMT) is very effective in the early, vulnerable phase after discharge following an acute heart failure (HF) event, but its widespread implementation in everyday clinical practice is limited.AMPEL is a guideline-based decision support software service for physicians to improve adherence with GDMT. The four drug classes that make up the GDMT and the percentage of each prescribed dose in relation to the target dose according to the current ESC guidelines are displayed graphically. A daily update considers the current therapy as well as absolute or relative contraindications. Methods and results:We present the rationale and protocol of the AMPEL trial, a multicenter randomized trial with a parallel-group design to investigate the effectiveness of the AMPEL service on GDMT implementation and patient clinical outcomes in a total of 260 patients. Salient features of the AMPEL study are that it is being conducted as part of the established disease management program (DMP) for HF, HerzMobil, and that participating physicians are given randomised access to the AMPEL service compared to the standard of care in the control group. The primary endpoint includes an implementation endpoint for assessment of the quality of indication- and dose-adjusted GDMT at 90 days and a clinical endpoint assessed with a stratified win ratio. Conclusions:The AMPEL trial is a prospective, randomized trial investigating the effectiveness of a guideline-based decision support software service for physicians to improve adherence with GDMT in a telemedicine-assisted disease management program for patients with heart failure.

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 arterial disease. Objective:For this work, data from the Keep Pace study were analyzed in depth to gain insights on temporal developments of patients' conditions and to develop models to predict the patients' total walking distance at the study end. This could help to determine patients who are likely to benefit from the telehealth program and to continuously provide estimations to the patients as a motivating factor. Methods:This work analyzes continuous patient-reported telehealth data, in combination with in-clinic data from 19 Fontaine stage II patients with peripheral arterial disease who underwent a 12-week telehealth-based walking program. This analysis granted insights into the increase of the total walking distance of the 6-minute walk tests (6MWT) as a measure for physical fitness, the steady decrease in the patients' pain, and the positive correlation between well-being and the total walking distance measured by the 6MWT. Results:This work analyzed trends of and correlations between continuous patient-generated data. Findings of this study include a significant decrease of the patients' pain sensation over time (P=.006), a low but highly significant correlation between pain sensation and steps taken on the same day (r=-0.11; P<.001) and the walking distance of the independently performed 6MWTs (r=-0.39; P<.001). Despite the reported pain, adherence to the 6MWT measurement protocol was high (85.53%). Additionally, patients significantly improved their timed-up-and-go test times during the study (P=.002). Predicting the total walking distance at the study end measured by the 6MWT worked well at study baseline (root mean squared error of 30 meters; 7.04% of the mean total walking distance at the study end of 425 meters) and continuously improved by adding further telehealth data. Future work should validate these findings in a larger cohort and in a prospective setting based on a clinical outcome. Conclusions:We conclude that the prototypical trend estimation has great potential for an integration in the telehealth system to be used in future work to provide tailored patient-specific advice based on these predictions. Continuous data from the telehealth system grant a deeper insight and a better understanding of the patients' status concerning well-being and level of pain as well as their current physical fitness level and the progress toward reaching set goals.

Objective This study aimed to assess the cost-effectiveness of the telemedically assisted post-discharge management program (DMP) HerzMobil Tirol (HMT) for heart failure (HF) patients in clinical practice in Austria. Methods We conducted a cost-effectiveness analysis along a retrospective cohort study (2016–2019) of HMT with a propensity score matched cohort of 251 individuals in the HMT and 257 in the usual care (UC) group and a 1-year follow-up. We calculated the effectiveness (hospital-free survival, hospital-free life-years gained, and number of avoided rehospitalizations), costs (HMT, rehospitalizations), and the incremental cost-effectiveness ratio (ICER). We performed a nonparametric sensitivity analysis with bootstrap sampling and sensitivity analyses on costs of HF rehospitalizations and on costs per disease-related diagnosis (DRG) score for rehospitalizations. Results Base-case analysis showed that HMT resulted in an average of 42 additional hospital-free days, 40 additional days alive, and 0.12 avoided hospitalizations per patient-year compared with UC during follow-up. The average HMT costs were EUR 1916 per person. Mean rehospitalization costs were EUR 5551 in HMT and EUR 6943 in UC. The ICER of HMT compared to UC was EUR 4773 per life-year gained outside the hospital. In a sensitivity analysis, HMT was cost-saving when “non-HF related costs” related to the DMP were replaced with average costs. Conclusions The economic evaluation along the cohort study showed that the HerzMobil Tirol is very cost-effective compared to UC and cost-saving in a sensitivity analysis correcting for “non-HF related costs.” These findings promote a widespread adoption of telemedicine-assisted DMP for HF. Graphical abstract

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 on the principles of P4 Medicine, was developed for a multidisciplinary prevention network. An IT infrastructure based on HL7 FHIR and the OHDSI OMOP common data model was designed. Results: An IT solution supporting a structured and modular prevention pathway was conceptualized. It contained a personalized management of prevention, risk assessment, diagnostic and preventive measures supported by a modular, interoperable IT infrastructure including a health app, prevention record web-service, decision support modules and a smart prevention registry, separating primary and secondary use of data. Conclusion: A concept was created on how an electronic health prevention record based on HL7 FHIR and the OMOP common data model can be implemented.

Peripheral artery disease (PAD) is a widespread condition affecting over 200 million people worldwide. PAD leads to a restricted blood flow to the extremities, causing painful limitations and the risk of amputation in advanced stages. Among medical and surgical interventions, the therapy of PAD involves walking training. Two commonly used standardized tests to measure walking performance and general mobility are the 6-minute walk test (6MWT) and the timed-up-and-go (TUG) test. Since a 6MWT takes more time and effort to complete than a TUG test, assessing the correlation between these two tests is crucial to determine the viability of the TUG test as a practical alternative to the 6MWT. The comparison of 36 TUG tests and 6MWTs revealed a significant inverse correlation across all parameters of both tests, with Pearson’s correlation coefficients up to R = -0.69 between the total TUG time and the total 6MWT distance. Future work should explore the potential substitution of the 6MWT with the TUG test and assess the impact of incorporating routine TUG tests in clinical practice.

Summary: 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 developed for patients with symptomatic PAD (Fontaine stage IIa and IIb), enabling a structured home-based walking training while monitoring progress via an app collecting unblinded account of steps and walking distance in self-paced 6-minute-walking-tests by geolocation tracking to enhance intrinsic motivation. Supervision by nurses via telephone calls was provided for 8 weeks, followed by 4 weeks of independent walking training. Patient satisfaction, walking distance and health-related quality of life were assessed. Results: 19 patients completed the study. The analysis revealed an overall high satisfaction with the telehealth service (95.4%), including system quality (95.1%), information quality (94.4%), service quality (95.6%), intention to use (92.8%), general satisfaction with the program (98.4%) and health benefits (95.8%). 78.9% asserted that the telehealth service lacking nurse calls would be less efficacious. Pain-free walking distance (76.3±36.8m to 188.4±81.2m, +112.2%, p<0.001) as well as total distance in 6-minute-walking test (308.8±82.6m to 425.9±107.1m, +117.2%, p<0.001) improved significantly. The telehealth service significantly reduced discomfort by better pain control (+15.5%, p=0.015) and social participation (+10.5%, p=0.042). Conclusions: In conclusion, patients were highly satisfied with the telehealth service. The physical well-being of the PAD patients improved significantly post vs. prior the telehealth program.

IntroductionThe 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 infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes.Materials and methodsOur proposed nodes are self-contained units that digest data through an extract-transform-load framework that pseudonymizes and links data with privacy-preserving record linkage and harmonizes into a common data model (OMOP CDM). To support collaborative analyses a multi-level feature store is also implemented. A feasibility experiment was conducted to test the infrastructures potential for machine learning operations and deployment of other apps (e.g., visualization). Nodes can be operated in a network at different levels of sharing according to the level of trust within the network.ResultsIn a proof-of-concept study, a privacy-preserving registry for heart failure patients has been implemented as a real-world showcase for Health Data Space nodes at the highest trust level, linking multiple data sources including (a) electronical medical records from hospitals, (b) patient data from a telemonitoring system, and (c) data from Austria’s national register of deaths. The registry is deployed at the tirol kliniken, a hospital carrier in the Austrian state of Tyrol, and currently includes 5,004 patients, with over 2.9 million measurements, over 574,000 observations, more than 63,000 clinical free text notes, and in total over 5.2 million data points. Data curation and harmonization processes are executed semi-automatically at each individual node according to data sharing policies to ensure data sovereignty, scalability, and privacy. As a feasibility test, a natural language processing model for classification of clinical notes was deployed and tested.DiscussionThe presented Health Data Space node infrastructure has proven to be practicable in a real-world implementation in a live and productive registry for heart failure. The present work was inspired by the European Health Data Space initiative and its spirit to interconnect health data silos for versatile secondary use of health data.

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 personalized patient therapy.OBJECTIVES:The goal of this work was to consider such an infrastructure, implemented in a smart registry for heart failure, as a comparative method for the analysis of health data.METHODS:We analyzed to what extent the dataset of a study on the telehealth program HerzMobil Tirol (HMT) can be reproduced with the data from the smart registry.RESULTS:A table with 96 variables for 251 patients of the HMT publication could theoretically be replicated from the smart registry for 248 patients with 80 variables. The smart registry contained the tables to reproduce a large part of the information, especially the core statements of the HMT publication.CONCLUSION:Our results show how such an infrastructure can enable efficient analysis of health data, and thus take a further step towards personalized health care.

It remains unclear whether transitional care management outside of a clinical trial setting provides benefits for patients with acute heart failure (AHF) after hospitalization. We evaluated the feasibility and effectiveness of a multidimensional post-discharge disease management programme using a telemedical monitoring system incorporated in a comprehensive network of heart failure nurses, resident physicians, and secondary and tertiary referral centres (HerzMobil Tirol, HMT), The non-randomized study included 508 AHF patients that were managed in HMT (n = 251) or contemporaneously in usual care (UC, n = 257) after discharge from hospital from 2016 to 2019. Groups were retrospectively matched for age and sex. The primary endpoint was time to HF readmission and all-cause mortality within 6 months. Multivariable Cox proportional hazard models were used to assess the effectiveness. The primary endpoint occurred in 48 patients (19.1%) in HMT and 89 (34.6%) in UC. Compared with UC, management by HMT was associated with a 46%-reduction in the primary endpoint (adjusted HR 0.54; 95% CI 0.37–0.77; P < 0.001). Subgroup analyses revealed consistent effectiveness. The composite of recurrent HF hospitalization and death within 6 months per 100 patient-years was 64.2 in HMT and 108.2 in UC (adjusted HR 0.41; 95% CI 0.29–0.55; P < 0.001 with death considered as a competing risk). After 1 year, 25 (10%) patients died in HMT compared with 66 (25.7%) in UC (HR 0.38; 95% CI 0.23–0.61, P < 0.001). A multidimensional post-discharge disease management programme, comprising a telemedical monitoring system incorporated in a comprehensive network of specialized heart failure nurses and resident physicians, is feasible and effective in clinical practice.

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. Adherence of healthcare professionals' medication prescriptions with regard to these guidelines is critical for optimal outcomes.METHODS:Data from the conceptional phase of the existing disease management network 'HerzMobil Tirol' were analysed. Prescriptions and patient- reported intake data of the four major substances of recommended heart failure medication were used to calculate the relative prescribed doses as a percentage of the recommended target doses. A concept for visualisation of the prescription status was developed in cooperation with health professionals.RESULTS:The documented prescriptions were analysed and used to develop a mock-up in order to visualise the prescription status for the individual patient.CONCLUSION:Analysis and visualisation can be managed by displaying the calculated daily relative dose per substance group in a traffic light system.

BACKGROUND Antitachycardial pacing (ATP) is a painless method for terminating ventricular tachycardias (VT) which would otherwise be treated using a painful high energy shock. However, it is well known that not each VT can be successfully terminated by ATP. Furthermore, ATP can be parametrized in several ways using scan, ramp or scan ramp approaches and can be applied in the right ventricle or in both ventricles (biventricular). In this work, we investigate the therapeutically most convenient ATP protocol based on a computer simulation using a patient individual model. METHODS A patient individual model generated from a 3D/4D data set and a hybrid automaton was used for modeling and simulation of different VT scenarios. On the different VTs (from cycle length 288 ms up to 408 ms) different ATP approaches derived from the ADVANCE-CRT trial were applied in order to determine the effectiveness of these approaches. RESULTS In this computer simulation study we were able to verify and validate the results from the ADVANCE-CRT trial. Biventricular ATP does not prove to be more effective than RV ATP but has a slight advantage in terminating fast VTs. CONCLUSIONS The availability of a patient individual model and knowledge about the ischemic area and the underlying mechanism of the VTs will allow the use of these models to optimize ATP management.

Introduction: The Heart Rate Performance Curve (HRPC) is neither linear nor uniform and related to ß1-adrenoceptor sensitivity. As aging and exercise influence ß1-adrenoceptors we suggested age, sex and performance effects on the HRPC. Aim of the study was to examine the effects of aging on the deflection of the HRPC in maximal incremental cycle ergometer exercise (CE) in a large cohort of healthy subjects.Methods: Heart rate (HR) data of 2,980 men (51 ± 15 years) and 1,944 women (52 ± 14 years) were classified into age groups (≤20 up to >80 years). We analyzed age and performance (Plow 25%-quartile and Phigh 75%-quartile of age predicted power) effects on HRmax and on the degree (k) and the type (regular downward deflection k > 0.1, linear −0.1 ≤ k ≤ 0.1 and atypical upward deflection k < −0.1) of the HRPC.Results:k-values decreased significantly with age in men and women and were significantly higher in women. Atypical HRPC's increased by a linear trend from ≤20 to 70 years (m) respectively 80 years (w) from 10 to 43% (m) and 9 to 30% (w). HRmax of all age groups was lower in Plow and overall number of atypical HRPC's was 21% (m) and 16% (w) higher compared to Phigh.Conclusion: Aging increased the number of atypical HRPC's with upward deflection in CE tests, which influences exercise intensity prescription especially when using fixed percentages of HRmax. Changes in HRPC's were affected by sex and performance, where women generally and subjects with higher performance presented less atypical HRPC's even at older age.

Digitalized healthcare services offer remote and cost-effective treatment of diabetes patients. Thus, the present online study analyzed the readiness to use telemonitoring among Austrian diabetes patients. We developed and validated a German version of the patient telehealth readiness assessment tool and performed quantitative context analysis of free-text comments on perceived barriers and benefits of telemonitoring. Participants (n = 41, 42.6% females) achieved a medium average readiness level for telemonitoring. The three top benefits were intensified care, shorter travel and waiting times, and better therapy adjustment. The top three barriers were data privacy issues, loss of personal communication and focus on blood sugar, and teledoctor competence. Diabetes patients represent a suitable target group for remote treatment opportunities. However, a shift from traditional face-to-face medical care to exclusive telemonitoring treatment from diagnosis to consultation and treatment requires fundamental new legal framework conditions.

BACKGROUNDHuge 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.RESEARCHIn scenarios, where several data sources are obtained without universal identifiers, record linkage methods need to be applied to obtain a comprehensive dataset.OBJECTIVESIn this study, we had the objective to link two datasets comprising data from ergometric performance tests in order to have reference values to free text annotations for assessing their data quality.METHODSWe applied an iterative, distance-based time series record linkage algorithm to find corresponding entries in the two given datasets. Subsequently, we assessed the resulting matching rate. The implementation was done in Matlab.RESULTSThe matching rate of our record linkage algorithm was 74.5% for matching patients' records with their ergometry records. The highest rate of appropriate free text annotations was 87.9%.CONCLUSIONFor the given scenario, our algorithm matched 74.5% of the patients. However, we had no gold standard for validating our results. Most of the free text annotations contained the expected values.

Telemonitoring services could dramatically improve the care of diabetes patients by enhancing their quality of life while decreasing healthcare expenditures. However, the potential for implementing innovative treatment options in the Austrian public and private health system is not known yet. Thus, we analyzed the readiness to use telemonitoring in diabetes care among Austrian practitioners.