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

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.

Usability of a telehealth-nurse supported home-based walking training for peripheral arterial disease - The Keep Pace! pilot study

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.

Health data space nodes for privacy-preserving linkage of medical data to support collaborative secondary analyses

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 infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes.

Materials and methods

Our 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.

Results

In 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.

Discussion

The 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.

In Search of Clinical Impact: Advanced Monitoring Technologies in Daily Heart Failure Care

Despite significant advances in the management of heart failure (HF), further improvement in the outcome of this chronic and progressive disease is still considered a major unmet need. Recurrent hospitalizations due to decompensated HF frequently occur, resulting in increased morbidity and mortality rates. Past attempts at early detection of clinical deterioration were mainly based on monitoring of signs and symptoms of HF exacerbation, which have mostly given disappointing results. Extensive research of the pathophysiology of HF decompensation has indicated that hemodynamic alterations start days prior to clinical manifestation. Novel technologies aim to monitor these minute hemodynamic changes, allowing time for therapeutic interventions to prevent hemodynamic derangement and HF exacerbation. The latest noticeable advancements include assessment of lung fluid volume, wearable devices with integrated sensors, and microelectromechanical systems-based implantable devices for continuous measurement of cardiac filling pressures. This manuscript will review the rationale for monitoring HF patients and discuss previous and ongoing attempts to develop clinically meaningful monitoring devices to improve daily HF health care, with particular emphasis on the recent advances and clinical trials relevant to this evolving field.