Cost-effectiveness of a multidimensional post-discharge disease management program for heart failure patients-economic evaluation along a one-year observation period.

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.

Feasibility and effectiveness of a multidimensional post-discharge disease management programme for heart failure patients in clinical practice: the HerzMobil Tirol programme.

AIMS: 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), METHODS AND RESULTS: 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). CONCLUSIONS: 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.

DMSP--Database for Modeling Signaling Pathways. Combining biological and mathematical modeling knowledge for pathways.

OBJECTIVES: Presently, the protein interaction information concerning different signaling pathways is available in a qualitative manner in different online protein interaction databases. The challenge here is to derive a quantitative way of modeling signaling pathways from qualitative way of modeling signaling pathways from a qualitative level. To address this issue we developed a database that includes mathematical modeling knowledge and biological knowledge about different signaling pathways. METHODS: The database is part of an integrative environment that includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning pathways. The system is designed as a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. RESULTS: DMSP--Database for Modeling Signaling Pathways incorporates biological datasets from online databases like BIND, DIP, PIP, and SPiD. The modeling knowledge that has been incorporated is based on a literature study. Pathway models can be designed, visualized and simulated based on the knowledge stored in the DMSP. The user can download the whole dataset and build pathway models using the knowledge stored in our database. As an example, the TNFalpha pathway model was implemented and tested using this approach. CONCLUSION: DMSP is an initial step towards the aim of combining modeling and biological knowledge concerning signaling pathways. It helps in understanding pathways in a qualitative manner from a qualitative level. Simulation results enable the interpretation of a biological system from a quantitative and system-theoretic point of view.

AAM-based segmentation for imaging cardiac electrophysiology.

OBJECTIVES: Activation time (AT) imaging from electrocardiographic (ECG) mapping data has been developing for several years. By coupling 4-dimensional volume data (3D + time) the electrical sequence can be computed non-invasively. In this paper an approach for extracting the ventricular and atrial blood masses for structurally normal hearts by using cine-gated short-axis data obtained via magnetic resonance imaging (MRI) is introduced. METHODS: The blood masses are extracted by employing Active Appearance Models (AAMs). The ventricular blood masses are segmented, applying the AAMs after providing apex cordis and base of the heart in the volume data, whereas the more complex geometry of the atria requires a more specific attempt. On account of this the atrium was divided into three divisions of appearance, where the images of the volume data in the related divisions have a maximum affinity. The first division reaches from the base of the heart to initial visibility of the upper and left lower pulmonary vein. The second division up from there to the last occurrence and the third division from there to the end of the visibility of the right upper and lower pulmonary vein. After extracting the cardiac blood masses the result gets triangulated and remeshed for activation time imaging. RESULTS: With this method the cardiac models of eight patients were extracted and the AT imaging approach was applied to single-beat ECG data of atrial and ventricular depolarization. CONCLUSION: The advantage of the proposed AAM approach is that only a few initial parameters have to be set. Therefore, the approach can be integrated into a processing pipeline that works semi-automatically. The extracted models can be used for further investigations.

Atrial and ventricular myocardium extraction using model-based techniques.

OBJECTIVES: This paper presents an efficient approach for extracting myocardial structures from given atrial and ventricular blood masses to enable non-invasive estimation of electrical excitation in human atria and ventricles. METHODS: Based on given segmented atrial and ventricular blood masses, the approach constructs the myocardial structure directly, in the case that the myocardium can be detected in the volume data, or by using mean model information, in the case that the myocardium cannot be seen in the volume data due to image modalities or artefacts. The approach employs mathematical and gray-value morphology operations. Regulated by the spatial visibility of the myocardial structure in the medical image data especially the atrial myocardium needs to be estimated repeatedly using the a-priori knowledge given by the anatomy. RESULTS: The approach was tested using eight patient data sets. The reconstruction process yielded satisfying results with respect to an efficient generation of a volume conductor model which is essential when trying to implement the estimation of electrical excitation in clinical application. CONCLUSION: The approach yields ventricular and atrial models that qualify for cardiac source imaging in a clinical setting.

Evaluation of an Integrated Telemonitoring Surveillance System in Patients with Coronary Heart Disease.

OBJECTIVES: Cardiovascular diseases are the most frequent cause of death in industrialized countries. Non-adherence with prescribed medication and recommended lifestyle changes significantly increases the risk of major cardiovascular events. The telemonitoring programme MyCor (Myokardinfarkt und Koronarstent Programm in Tirol) is a multi-modal intervention programme to improve lifestyle and medication management of patients with coronary heart disease (CHD). It includes patient education, self-monitoring with goal-setting and feedback, and regular clinical visits. We evaluated the MyCor telemonitoring programme regarding technical feasibility, user acceptance, patient adherence, change in health status, and change in quality of life. METHODS: A 4½-month study was conducted with two telemonitoring phases and one interim phase. The study comprised patient surveys, standardized assessment of quality of life using the MacNew questionnaire at study entry and after 4 and 18 weeks, analysis of adherence to medication and physical activity during the two telemonitoring phases, and analysis of reached goals regarding health conditions during the telemonitoring phases. RESULTS: Twenty-five patients (mean age: 63 years) participated in the study. Patients showed a high acceptance of the MyCor telemonitoring programme. Patients reported feelings of self-control, motivation for lifestyle changes, and improved quality of life. Adherence to daily measurements was high with 86% and 77% in the two telemonitoring phases. Adherence to medication was also high with up to 87% and 80%. Pre-defined goals for physical activity were reached in up to 86% and 73% of days, respectively. Quality of life improved from 5.5 at study entry to 6.3 at the end (p< 0.01; MacNew questionnaire). Reductions in blood pressure and heart rate or an improvement in reaching defined goals could not be observed. CONCLUSIONS: The MyCor telemonitoring programme Tirol for CHD patients has a high rate of acceptance among included patients. Critical evaluation revealed subjective benefits regarding quality of life and health status as well as high adherence rates to medication and lifestyle changes. Achieving long-term adherence and verifying clinical outcomes, however, remains an open issue. Our findings will promote further studies, addressing different strategies for an optimal mix of patient education, telemonitoring, feedback, and clinical follow-ups.

An epidemiological modeling and data integration framework.

OBJECTIVES: In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria. METHODS: The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3). RESULTS: The obtained simulation results were used for generating prediction models for all nine federal states of Austria. CONCLUSION: The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.

Patient-specific volume conductor modeling for non-invasive imaging of cardiac electrophysiology.

We propose a general workflow to numerically estimate the spread of electrical excitation in the patients' hearts. To this end, a semi-automatic segmentation pipeline for extracting the volume conductor model of structurally normal hearts is presented. The cardiac electrical source imaging technique aims to provide information about the spread of electrical excitation in order to assist the cardiologist in developing strategies for the treatment of cardiac arrhythmias. The volume conductor models of eight patients were extracted from cine-gated short-axis magnetic resonance imaging (MRI) data. The non-invasive estimation of electrical excitation was compared with the CARTO maps. The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.