Roadmap for Aligning Cardiovascular Digital Health in Austria with the European Health Data Space (EHDS) Ecosystem.

Translating the proposed European Health Data Space (EHDS) regulations and requirements into reality is a challenging task. In this work, we provide a roadmap for aligning the EHDS requirement into the cardiovascular (CV) digital health domain in Austria. To achieve that, we first examined the current eHealth infrastructure and initiatives in Austria. Then, we created a CV-connected health model and addressed the challenges facing cardiac telerehabilitation in Austria. Finally, we mapped the European CV strategies to the Austrian context for EHDS implementation. Accordingly, we were able to provide an Enterprise Architecture (EA) framework for aligning CV digital health with the Austrian EHDS context. The created EA model can be also used as a guiding framework for aligning other medical domains in Austria with EHDS.

Health Data Democratization in Austria: Patients' Perspective.

Health data democratization requires a transparent, protected, and interoperable data-sharing environment. We conducted a co-creation workshop with patients living with chronic diseases and relevant stakeholders to explore their opinion on health data democratization, ownership, and sharing in Austria. Participants showed their willingness to share their health data for clinical and research purposes; provided that appropriate transparency and data protection measures are provided.

Patient-Generated Health Data Interoperability Through Master Patient Index: The DH-Convener Approach.

Patient-Generated Health Data (PGHD), such as data provided by wearable devices, hold promise to improve health outcomes. However, to improve clinical decision-making, PGHD should be integrated or linked with Electronic Health Records (EHRs). Typically, PGHD data are collected and stored as Personal Health Records (PHRs), outside EHR systems. To address this challenge, we created a conceptual framework for PGHD/EHR interoperability through the Master Patient Index (MPI) and DH-Convener platform. Then, we identified the corresponding Minimum Clinical Data Set (MCDS) of PGHD to be exchanged with EHR. This generic approach can be used as a blueprint in different countries.

Wearable Device Health Data Mapping to Open mHealth and FHIR Data Formats.

Health data collected by wearables and apps can be useful as part of patient-generated health data (PGHD) or personal health data for medical diagnosis or general health monitoring. Mobile health apps are more and more accepted, generate evidence and might be increasingly used in personal medicine. Data retrieved from wearables and apps are mostly not following a medical data standard and cannot be retrieved from the vendors in a straightforward way. The present work started the implementation of a Digital Health Convener and described the process to collect data from several wearables - starting with Fitbit data - and transforms this data to standardized JSON files following the Open mHealth (OmH) IEEE and the HL7 FHIR standard. The project achieved is provided as open source and can be extended and used in future projects to generate OmH and FHIR conform PGHD.

Converting HL7 CDA Based Nationwide Austrian Medication Data to OMOP CDM.

Austria's national Electronic Health Record (EHR) system holds information on medication prescriptions and dispenses in highly structured HL7 Clinical Document Architecture (CDA) documents. Making these data accessible for research is desirable due to their volume and completeness. This work describes our approach of transforming the HL7 CDA data into Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and highlights a key challenge, namely mapping the Austrian drug terminology to OMOP standard concepts.

Can Patient Contributed Data (PCD) Leverage Connected Health Technology for Cardiac Rehabilitation in Austria?

New technologies such as devices, apps, smartphones, and sensors not only enable people to self-monitor their health but also share their health data with healthcare professionals. Data collection and dissemination occur across a wide variety of environments and settings, tracking everything from biometric data to mood and behavior, which has been termed Patient Contributed Data (PCD). In this work, we created a patient journey, enabled by PCD, to shape a connected health model for Cardiac Rehabilitation (CR) in Austria. Consequently, we highlighted the potential PCD benefit, which is a postulated increasing uptake of CR and improved patient outcomes through apps in a home-based setting. Finally, we addressed the related challenges and policy barriers that hinder the implementation of CR-connected health in Austria and identified actions to be taken.

Defining and Scoping Participatory Health Informatics: An eDelphi Study.

BACKGROUND: Health care has evolved to support the involvement of individuals in decision making by, for example, using mobile apps and wearables that may help empower people to actively participate in their treatment and health monitoring. While the term "participatory health informatics" (PHI) has emerged in literature to describe these activities, along with the use of social media for health purposes, the scope of the research field of PHI is not yet well defined. OBJECTIVE: This article proposes a preliminary definition of PHI and defines the scope of the field. METHODS: We used an adapted Delphi study design to gain consensus from participants on a definition developed from a previous review of literature. From the literature we derived a set of attributes describing PHI as comprising 18 characteristics, 14 aims, and 4 relations. We invited researchers, health professionals, and health informaticians to score these characteristics and aims of PHI and their relations to other fields over three survey rounds. In the first round participants were able to offer additional attributes for voting. RESULTS: The first round had 44 participants, with 28 participants participating in all three rounds. These 28 participants were gender-balanced and comprised participants from industry, academia, and health sectors from all continents. Consensus was reached on 16 characteristics, 9 aims, and 6 related fields. DISCUSSION: The consensus reached on attributes of PHI describe PHI as a multidisciplinary field that uses information technology and delivers tools with a focus on individual-centered care. It studies various effects of the use of such tools and technology. Its aims address the individuals in the role of patients, but also the health of a society as a whole. There are relationships to the fields of health informatics, digital health, medical informatics, and consumer health informatics. CONCLUSION: We have proposed a preliminary definition, aims, and relationships of PHI based on literature and expert consensus. These can begin to be used to support development of research priorities and outcomes measurements.

Towards the European Health Data Space (EHDS) ecosystem: A survey research on future health data scenarios.

OBJECTIVE: The European Health Data Space (EHDS) aims to provide better exchange and expand access to health data across Europe. In this way, the EHDS will support healthcare delivery (known as the "primary use of data") and facilitate access to health data for research and policy-making purposes (known as the "secondary use of data"). To achieve this goal, we need to build the required ecosystem of the EHDS with all healthcare stakeholders. MATERIALS AND METHODS: We conducted a survey research study to explore the health informaticians' recommendations on future health data scenarios shaping the EHDS ecosystem. We created an anonymous- online questionnaire and disseminated it through wide international networks of health informaticians. In addition, we conducted a workshop during the Medical Informatics Europe Conference (MIE2022) and invited the attendees to complete the questionnaire during the workshop. RESULTS: We received 43 responses to our questionnaire from 15 European Union (EU) countries and 7 non-EU countries. Most respondents described the current health data scenario in their countries as a traditional healthcare system with moderate growth (25.6 %, n = 11). The second selected scenario was the reinventing healthcare scenario in a data-driven one-world framework (23.3 %, n = 10). DISCUSSION: The results of this work are matched with the findings of the recently published study on digital health implementation in the EU (conducted by the French government in April 2022). This also reflects the current ongoing efforts in the EU countries to deploy national infrastructure for health data management, exchange, and sharing. CONCLUSIONS: Upon the respondents' recommendations, there is a strong need to support the health democratization scenarios in Europe, as the main driver for building the EHDS ecosystem.

A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs).

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation.

Overview of Existing Tools for Extracting Health and Fitness Data from mHealth Apps.

Wearable sensors and mHealth apps collect fitness and health data outside of clinical settings. These data are essential for precision medicine. This paper addresses and analyzes the available tools for extracting health and fitness data from wearables and mHealth apps. We focus on the most common tools used for research, namely, the Open mHealth-Shimmer application and Fitrockr research platform.

General Data Protection Regulation (GDPR) Toolkit for Digital Health.

The General Data Protection Regulation (GDPR) entered into force on May 25, 2018. Compliance with GDPR is especially relevant to the Digital Health (DH) domain, as it is common to process highly sensitive personal data regarding a person's health. However, GDPR compliance is a very challenging process since it requires implementing several technical and organizational measures to maintain compliance. With the aim to facilitate this process, we reviewed the published best practices in GDPR compliance. Then, we customized the findings to fit into the DH domain and created a toolkit for GDPR implementation and compliance. The Activity Planning Tool (APT) is provided as an example of how this toolkit could be utilized in new application development in mobile health in Austria. In the case of our APT, the toolkit was very helpful in integrating the GDPR technical requirements in addition to creating the corresponding compliance impact assessment, processing agreements, privacy policy, data flowcharts, and compliance checklists.

The Development of a Digital Tool for Planning Physical Exercise Training During Cardiac Rehabilitation.

In this work, we describe the conceptualization and development of a digital tool to support patients in adhering to prescription of physical exercise training during cardiac rehabilitation. To meet the need for an individual and trackable heart-healthy training plan - which became even more evident during the Coronavirus pandemic - the Activity Planning Tool was developed within a user-centered design process. Tackling the relationship between rehabilitation professional and patient, it allows to jointly set up, monitor, and regularly review a personalized physical activity plan.

Extending the Austrian National EHR System with Patient-Reported Outcome Data.

The Austrian national Electronic Health Record system ELGA is a population-based infrastructure for health data. However, to date, it does not include patient-reported outcomes. In this paper, we describe on-going work on extending ELGA with patient-reported outcome data. This will be done by linking ELGA with the infrastructure of the Health Outcomes Observatory (H2O) initiative. The focus will be on using ELGA's identifier registry for H2O patients and making H2O outcome data accessible in ELGA via an existing ELGA document type for telemonitoring.

PSMA PET predicts metastasis-free survival in the setting of salvage radiotherapy after radical prostatectomy.

INTRODUCTION: To evaluate the impact of PSMA PET (prostate specific membrane antigen positron emission tomography) findings prior to salvage radiotherapy (SRT) in recurrent prostate cancer (PCa) after radical prostatectomy (RP) on metastasis-free survival (MFS). PATIENTS AND METHODS: Between 01/2012 and 12/2018, 1,599 patients received SRT for biochemical recurrence after RP at our institution. Five-year MFS of "positive PSMA PET" (n = 49) vs. "negative PSMA PET" (n = 106) vs. "no PSMA PET" (n = 1,599) prior to SRT was determined. For all time to event analyses, uni- and multivariable Cox's proportional hazards models and univariable Kaplan-Meier analyses were applied, with a significance threshold of P < 0.05. Further 4:1 propensity score matching for patient, cancer and treatment characteristics was performed to account for residual differences between groups. RESULTS: Of PSMA PET patients, 106 patients exhibited "negative PSMA PET" (68.4%) and 49 exhibited "positive PSMA PET" (31.6%). Median PSA at recurrence did not differ between groups (0.2 ng/ml; P= 0.4). After 4:1 propensity score matching, 5-year MFS between "no PSMA PET" and "negative PSMA PET" was 94.4 vs. 93.0%, respectively (P = 0.8). For "no PSMA PET" versus "positive PSMA PET", 5-year MFS was significantly lower in "positive PSMA PET" (92.3 vs. 48.5%, respectively P < 0.0001). Finally, "positive PSMA PET" was independently associated with worse MFS compared to "no PSMA PET" after multivariable adjustment in the overall cohort (HR 13.8, CI 7.5-25.2, P < 0.001). CONCLUSIONS: Locoregional positive PSMA PET findings in recurrent patients after RP are highly predictive of worse MFS in the setting of SRT.

Patient-Generated Health Data (PGHD) Interoperability: An Integrative Perspective.

With advances in Digital Health (DH) tools, it has become much easier to collect, use, and share patient-generated health data (PGHD). This wealth of data could be efficiently used in monitoring and controlling chronic illnesses as well as predicting health outcome. Although integrating PGHD into clinical practice is currently in a promising stage, there are several technical challenges and usage barriers that hinder the full utilization of the PGHD potential in clinical care and research. This paper aims to address PGHD opportunities and challenges while developing the DH-Convener project to integrate PGHD into the Electronic Health Record in Austria (ELGA). Accordingly, it provides an integrative technical-clinical-user approach for developing a fully functional health ecosystem for exchanging integrated data among patients, healthcare providers, and researchers.

Physical Activity in Cardiac Rehabilitation: Towards Citizen-Centered Digital Evidence-Based Interventions.

Physical activity is a vital part of cardiac rehabilitation (CR). However, heart-healthy physical activity levels in people with cardiovascular disease drop significantly after CR. This exploratory study employs qualitative and survey methods within a co-creation approach. The aim is to understand the mechanisms of healthy behavior and habit formation in order to create a novel evidence-based (post-)rehabilitation approach that employs digital means to sustain long-term physical activity levels in people with cardiovascular disease.

Medical Informatics in the Digital Personalized Health and Medicine Era: A SWOT Analysis and Actionable Strategies.

With the rapid proliferation of digital health technologies, the role of medical informatics in advancing personalized healthcare and wellbeing is emphasized. To examine the readiness of medical informatics for fostering digital health moving forward, a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis was performed. As a result, actionable strategies have been identified to maximize the benefits of medical informatics and overcoming the faced challenges in the digital health era.

A Review of Realizing the Universal Health Coverage (UHC) Goals by 2030: Part 1- Status quo, Requirements, and Challenges.

This paper is the first part of a review of how to realize the Universal Health Coverage (UHC) goals by 2030. The objective of this review is to investigate the role of eHealth and technology in achieving UHC, focusing on four aspects: 1) identifying the importance of UHC and highlighting how UHC is influenced by health systems and eHealth, 2) investigating the current status of UHC worldwide and indicating the current challenges facing the realization of UHC, 3) reviewing the current research activities in the UHC domain and emphasizing the role of eHealth and technology in achieving UHC, and 4) discussing the results of the review to identify the current gaps in UHC implantation and the corresponding research lines for future investigation.This part covers the first two aspects through: providing the required background on UHC, highlighting the potential benefits of eHealth utilization in UHC, addressing the current status quo of UHC implementation worldwide, and finally concluding the lessons learned in terms of the UHC challenges and requirements.This part also described the used search methodology and selection criteria to synthesize this review. It also indicates the limitations of conducting a systematic review in this early stage of deploying UHC-oriented eHealth solutions.