CareNet Tyrol - Information System Success Assessment for Case & Care Management Service.

BACKGROUND: CareNet is the IT-based tool for Case and Care Management (CCM) in Tyrol, which facilitates standardised documentation of CCM activities. OBJECTIVES: Analysing the pilot usage of CareNet Tyrol. METHODS: Evaluation of the success and user experience of CareNet, expert interviews and a questionnaire-based assessment. RESULTS: Feedback from users in both phases indicated that the CareNet platform provides general benefits, but falls short of fully supporting the daily work of CCM experts and avoiding the need for parallel use of different documentation tools. CONCLUSION: This paper provides an insight into the ongoing transition to digital documentation for CCM at LIV Tyrol. While user feedback highlights areas for improvement, digital documentation is proved to be beneficial for the CCM team.

A Standardized Treatment Pathway for Telehealth-Based Care of Chronic Wounds in Austria.

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-supported treatment pathway for chronic wounds has been developed. The primary focus was to regularly update the status of the chronic wound by responding to predefined questions and transmitted images of the chronic wound. This was achieved by an interdisciplinary team of experts in chronic wound care, providing a new perspective for digital implementation in the healthcare system.

Identifying Accuracy-related Outliers in a 6-Minute Walk Test Application for Monitoring Cardiovascular Disease Patients.

The 6-Minute Walk Test (6-MWT) is frequently used to evaluate functional physical capacity of patients with cardiovascular diseases. To determine reliability in remote care, outlier classification of a mobile Global Navigation Satellite System (GNSS) based 6-MWT App had to be investigated. The raw data of 53 measurements were Kalman filtered and afterwards layered with a Butterworth high-pass filter to find correlation between the resulting Root Mean Square value (RMS) outliers to relative walking distance errors using the test. The analysis indicated better performance in noise detection using all 3 GNSS dimensions with a high Pearson correlation of r = 0.77, than sole usage of elevation data with r = 0.62. This approach helps with the identification between accurate and unreliable measurements and opens a path that allows usage of the 6-MWT in remote disease management settings.Clinical Relevance- The 6-MWT is an important assessment tool of walking performance for patients with cardiovascular diseases. Using a sufficiently accurate application would enable unsupervised and easy remote usage, which could potentially reduce the demand for in-clinic visits and facilitate a more convenient and reliable monitoring method in telehealth settings.

Integrated Telehealth Infrastructure for Ambulatory Stroke Pathway Tyrol.

BACKGROUND: The Integrated Treatment Pathway Stroke Tyrol was introduced for the care of people after an acute stroke event and includes four phases: acute prehospital care, inpatient treatment, inpatient rehabilitation and ambulatory, outpatient rehabilitation. For the 4th phase, the ambulatory rehabilitation of patients after discharge, the ICT platform "StrokeNet Tyrol" was established. METHODS: Requirements and processes along the pathway and between the interdisciplinary team were taken into account for implementation based on a modular software architecture. Flexible rights and role concept was developed to support efficient collaboration of the heterogenic professions. RESULTS: The routine usage of 342 users with 8 different roles, 2,219 registered patient cases within the last 4 years and first results of the integrated benchmarking solution give a positive impression regarding feasibility and effectiveness. CONCLUSION: To this point, a comprehensive infrastructure for the Ambulatory Tyrolean Stroke Pathway has been established. Results from outcome analyses and comparative studies could help to further improve usability and to expand the area of application for other indications.

Investigation of the time shift between wearable photoplethysmography sensors used for continuous heart rate monitoring.

In this study, we investigated the effect of time shift in heartrate measurement by wearables, which might to be used in telehealth applications for patients suffering from heart failure. Six wearables commercially available on the market were tested in a 14-hour measurement. Each wearable was tested three times by five different test persons. A reference sensor was used to test the accuracy of the wearables. We found that different types of time shifts are common in the sensors we tested: time shifts of full days, time shifts of full hours (most probably due to incorrect or unspecified time zones) and time shifts in the range of seconds to minutes (most likely stemming from averaging, data transmission, etc.). We conclude that time shifts of all manufacturers need to be corrected prior comparison of a photoplethysmography signal with other signals. However, even after correction of the time shift, the reliability of the sensors seems to be too low for application in telehealth settings. Clinical relevance- This study shows that signals from state-of-the-art wearable photoplethysmography heart rate measurements show significant time shifts and marked differences even if time shifts were corrected. This limits their utility for clinical applications.

Accuracy of Wearable Photoplethysmography Sensors for Continuous Heart Rate Monitoring in Telehealth Applications.

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 duration of fourteen-hour each, and compared to a reference sensor. By calculating the Pearson correlation and the root mean square error, as well as the graphical representation by a Bland Altman plot, it was found that these wearables lack sufficient accuracy and may not be suitable for medical purposes.

mHealth 6-minute walk test - accuracy for detecting clinically relevant differences in heart failure patients.

Heart failure is a serious disease which increases mortality as well as hospital admission rates for affected patients. Disease management programs supported by telehealth solutions are cost-effective approaches for reducing all-cause mortality and heart failure hospitalizations. A 6-minute walk test (6MWT) app could help heart failure patients to self-monitor their functional capacity. We have developed such an application capable of tracking the geolocation, guiding users through a 6MWT and providing the walked distance after six minutes. Besides common global navigation satellite system (GNSS) filtering methods like a Kalman filter, we have investigated the impact of positioning the device (tablet) and GNSS reception on the accuracy of the test. In a field experiment, we gathered 166 6MWT recordings with the developed mobile application. Applying the Kalman filter reduced the overall relative error from 35.5 % to 3.7 %. Wearing the tablet on the body led to significantly better results than holding it in the hand (p < .001). The average accuracy of 2.2 % of body-worn measurements was below previously defined thresholds for reliable results. It thus allows to define a procedure on how to perform and integrate an accurate 6MWT in telehealth settings for clinical decision support in heart failure patients.

Rasch Model of the COVID-19 Symptom Checklist-A Psychometric Validation Study.

While self-reported Coronavirus Disease 2019 (COVID-19) symptom checklists have been extensively used during the pandemic, they have not been sufficiently validated from a psychometric perspective. We, therefore, used advanced psychometric modelling to explore the construct validity and internal consistency of an online self-reported COVID-19 symptom checklist and suggested adaptations where necessary. Fit to the Rasch model was examined in a sample of 1638 Austrian citizens who completed the checklist on up to 20 days during a lockdown. The items' fatigue', 'headache' and 'sneezing' had the highest likelihood to be affirmed. The longitudinal application of the symptom checklist increased the fit to the Rasch model. The item 'cough' showed a significant misfit to the fundamental measurement model and an additional dependency to 'dry cough/no sputum production'. Several personal factors, such as gender, age group, educational status, COVID-19 test status, comorbidities, immunosuppressive medication, pregnancy and pollen allergy led to systematic differences in the patterns of how symptoms were affirmed. Raw scores' adjustments ranged from ±0.01 to ±0.25 on the metric scales (0 to 10). Except for some basic adaptations that increases the scale's construct validity and internal consistency, the present analysis supports the combination of items. More accurate item wordings co-created with laypersons would lead to a common understanding of what is meant by a specific symptom. Adjustments for personal factors and comorbidities would allow for better clinical interpretations of self-reported symptom data.

Development of Multivariable Models to Predict and Benchmark Transfusion in Elective Surgery Supporting Patient Blood Management.

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, the concept of Patient Blood Management has increasingly gained importance to pre-empt and reduce transfusion and to identify the optimal transfusion volume for an individual patient when transfusion is indicated. OBJECTIVES: It was our aim to describe, how predictive modeling and machine learning tools applied on pre-operative data can be used to predict the amount of red blood cells to be transfused during surgery and to prospectively optimize blood ordering schedules. In addition, the data derived from the predictive models should be used to benchmark different hospitals concerning their blood transfusion patterns. METHODS: 6,530 case records obtained for elective surgeries from 16 centers taking part in two studies conducted in 2004-2005 and 2009-2010 were analyzed. Transfused red blood cell volume was predicted using random forests. Separate models were trained for overall data, for each center and for each of the two studies. Important characteristics of different models were compared with one another. RESULTS: Our results indicate that predictive modeling applied prior surgery can predict the transfused volume of red blood cells more accurately (correlation coefficient cc = 0.61) than state of the art algorithms (cc = 0.39). We found significantly different patterns of feature importance a) in different hospitals and b) between study 1 and study 2. CONCLUSION: We conclude that predictive modeling can be used to benchmark the importance of different features on the models derived with data from different hospitals. This might help to optimize crucial processes in a specific hospital, even in other scenarios beyond Patient Blood Management.

Assistive Solutions in Practice: Experiences from AAL Pilot Regions in Austria.

Since 2012 six AAL pilot regions were launched in Austria. The main goal of these pilot regions is to evaluate the impact of AAL technologies in daily use considering the entire value chain. Additionally, go-to market strategies for assistive technologies based on an involvement of all relevant stakeholders are developed. Within this paper an overview of the specific objectives, approaches and the status of all Austrian AAL pilot regions is given. Taking into account the different experiences of the different pilot regions, specific challenges in establishing, implementing and sustaining pilot region projects are discussed and lessons-learned are presented. Results show that a careful planning of all project phases taking into account available resources is crucial for the successful implementation of an AAL pilot region. In particular, this applies to all activities related to the active involvement of end-users.