Digital Health

Overview

What is Digital Health?

Digital health has established itself as a central axis of transformation for contemporary health systems, driven by rapid advances in information and communication technologies (ICT), artificial intelligence (AI), and data infrastructures. Current digital health ecosystems are increasingly data-driven, AI-enabled, and systemically embedded in clinical, research, and governance contexts.

The recent acceleration of innovation — particularly following the widespread availability of large language models and advanced pattern recognition systems — has significantly expanded the scope of digital health. Applications now range from protein folding and basic biomedical research to AI-assisted diagnostics that outperform human specialists, and from robotics in elderly care to fully automated diagnostic environments in remote and underserved areas.

As a result, digital health is no longer a standalone sector but has become an integrative field encompassing healthcare delivery, research, public health, and system governance. AIM's approach adds a critical question: are we forgetting the human in digital health?

"Are we forgetting the human in digital health? AIM exists to ensure the answer is no."

— AIM Research Framework

WHO Definition

"Digital health refers to the use of digital technologies to improve health outcomes, health services, and system efficiency in prevention, diagnosis, treatment, monitoring and management."

— World Health Organisation, 2020

AIM's Approach

AIM investigates the useful and detrimental qualities of digital technologies through the lens of its four-dimensional health framework: ontological, level, causal, and teleological. This non-reductive approach ensures that human flourishing — not just efficiency — remains the ultimate criterion.

People

Academic Programme Committee - Digital Health

AIM coordinates and amplifies AAU's distributed expertise in Digital Health across faculties. The following researchers represent their faculties in the Academic Programme Committee of the Digital Health flagship area.

Univ.-Prof. Dr. Heather Foran

Institut für Psychologie / Gesundheitspsychologie

Health Psychology · Digital Health Interventions · Epidemiological Studies · Mental Health

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Assoc.-Prof. Mag. Dr. Agnes Turner

Institut für Unterrichts- und Schulentwicklung

Digitalisation & Digital Teaching · Educational Research · Educational Sciences

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Assoc.Prof. Dr. Klaus Schöffmann

Institut für Informationstechnologie

Computer Science · Medical Video Analysis · AI in Healthcare

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Univ.-Prof. Dr. Ralf Terlutter

Department of Management

Health Communication · Health Marketing · Consumer Behavior · Health Sciences

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Univ.-Prof. Dr. Andrej Zwitter

AIM / Humanwissenschaft des Digitalen

Digital Humanities · AI Ethics · Cybernetic Governance · Digital Health Policy

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Explore the full directory of AAU researchers contributing to the Digital Health flagship area.

View All Researchers → (forthcoming)

Technology Landscape

Core Technology Areas

Digital health operates at the intersection of multiple technological domains. AIM's research addresses all four of these pillars, with particular attention to their social, ethical, and governance implications.

AI & Machine Learning

Pattern recognition & diagnostics
Predictive modelling
NLP for clinical text
Computer vision
Generative AI in healthcare

Infrastructure & Data

Sensors & IoT wearables
Cloud & edge computing
EHR interoperability (HL7 FHIR)
Health data spaces
Robotics & automation

Research & Innovation

Clinical trials (large n)
Real-world evidence
Simulation & digital twins
AI-assisted discovery
Protein structure prediction

Healthcare Delivery

Telemedicine & telecare
Remote patient monitoring
Elderly care robotics
Workflow automation
AI-powered health kiosks

Research Domains

Application Areas

AIM's Digital Health research agenda spans four major application domains, each connecting technological capability with human-centered values and governance considerations.

Domain 01

Clinical Diagnostics & Decision Support

One of the most mature application areas — AI systems that reach or exceed expert-level performance in imaging, triage, and pathological classification.

AI-driven analysis of multimodal data — combining lab values, clinical notes, genomics, and sensor data — enables personalised and predictive diagnostic pathways. AIM's research emphasises the need for robust quality metrics, transparency, and validation to ensure clinical applicability and trustworthiness, especially for generative or self-learning models.

AI ImagingCDSSGenomicsDigital BiomarkersValidation

Domain 02

Patient-Centered & Elderly Care

Telemedicine, remote monitoring, and AI-driven robotics that extend access to care and support independent living — with dignity and human connection at their core.

Telehealth extends access across geographic and mobility barriers, while remote patient monitoring enables early detection of deterioration and supports ageing-in-place strategies. AIM highlights that such technologies are most effective when embedded in socio-technical care models that prioritise usability, dignity, and trust alongside technical performance.

TelemedicineWearablesCare RoboticsAgeingMobile Health

Domain 03

Medical Research & Innovation

Large-scale AI models transforming biomedical research — from protein structure prediction to digital twin simulations and real-world evidence generation.

Digital tools increasingly support real-world evidence generation, integrating wearable data, mobile health applications, and routine clinical data into observational and hybrid clinical trials. Digital twins — virtual representations of biological systems or individual patients — are emerging as powerful tools for simulation, hypothesis testing, and personalised treatment planning.

Digital TwinsAlphaFoldClinical TrialsReal-world Evidence

Domain 04

Public Health & System Management

Population-level data analytics, disease surveillance, and epidemiological modelling for evidence-based policy and system efficiency.

Data analytics platforms enable real-time monitoring of disease outbreaks, resource allocation, and system performance. The COVID-19 pandemic demonstrated both the transformative potential and the governance challenges of digital tools in public health — highlighting issues of equity, data privacy, and rapid policy response. AIM studies these trade-offs systematically.

EpidemiologySurveillanceHealth PolicyEquityGovernance

EU Regulatory Context

European Health Data Space

AIM monitors and analyses the evolving EU regulatory landscape for digital health, including the European Health Data Space (EHDS) and the broader framework of EU data law.

European Health Data Space (EHDS)

The EHDS is a landmark EU regulation establishing a framework for the access, use, and exchange of electronic health data across the EU — both for primary use (care delivery) and secondary use (research, innovation, policy).

It defines common rules, standards, governance structures, interoperability requirements, and infrastructures for secure, cross-border use of health data. EHDS establishes National Health Data Access Bodies (HDABs) to manage controlled access for secondary use, and sets legal obligations for Electronic Health Record (EHR) systems.

EHDS is a lex specialis to GDPR — adding health-specific rules while operating in parallel with general EU data protection law. The regulation is closely intertwined with eIDAS and the emerging European Digital Identity Wallet, which will allow citizens to authenticate and authorise access to their health data at EU scale.

GDPR

General Data Protection Regulation

The foundation of health data governance in the EU. Health data is treated as a special category requiring heightened protection.

DGA

Data Governance Act

Establishes frameworks for data sharing and reuse across the EU economy, including trusted data intermediaries for sensitive data.

Data Act

Promotes fair access and use of data across sectors; supports secondary use and interoperability in health applications.

AI Act

EU Artificial Intelligence Act

Classifies and regulates AI systems by risk level; high-risk medical AI applications face stringent requirements for transparency and validation.

eIDAS

eIDAS & European Digital Identity Wallet

Provides the trust infrastructure for secure authentication and authorisation in cross-border health data transactions.

Primary Use Cases

Healthcare delivery — enabling patients and professionals to access and share electronic health records across EU member states, supporting continuity of care.

Secondary Use Cases

Research, innovation, and public health policy — enabling approved researchers and public bodies to access pseudonymised health data for scientific purposes under controlled conditions.

AIM's Contribution

AIM examines the governance gaps, convergence effects, and unintended consequences arising from this complex multi-layer regulatory landscape — applying the concept of cybernetic governance to identify where institutions, technologies, and norms are co-shaping each other.

Regional Initiative

Southern Austrian Health Data Space

AIM is involved in developing regional health data infrastructure as a concrete application of the EHDS framework at the sub-national level.

Southern Austrian Health Data Space

Building on the principles of the European Health Data Space, AIM is contributing to the development of a Southern Austrian Health Data Space — a regional initiative to create trusted, interoperable health data infrastructure that connects research institutions, healthcare providers, and policy actors in the Carinthia region and beyond.

Initiative Status

In Development

More details forthcoming

Critical Perspectives

Challenges & Opportunities

AIM engages critically with both the transformative potential and the systemic risks of digital health — taking seriously the question of what it means to put the human at the center of digitalisation.

Key Challenges

Data Governance & Privacy

Consent, control, anonymisation, standards & interoperability, secondary use governance, and regulatory compliance across multiple overlapping frameworks.

Digital Divides & Equity

Unequal access to digital health technologies across regions, age groups, and socioeconomic backgrounds — risk of amplifying existing health inequalities.

Governance Convergence

As technologies and regulations co-evolve, governance structures converge in ways that can create unintended gaps and overlaps — a core concern for AIM's cybernetic governance research.

Trust & Transparency

AI systems used in clinical settings require explainability, validated performance metrics, and robust accountability frameworks to maintain public trust.

The Human Question

The risk of optimising for efficiency, throughput, and data quality at the expense of human dignity, autonomy, and the irreducible value of human relationships in care.

Key Opportunities

Improved Diagnostic Accuracy

AI-assisted diagnostics are demonstrating performance at or above expert level in imaging, pathology, and genomics — with potential to dramatically reduce diagnostic errors.

Expanded Access & Reduced Costs

Telemedicine, mobile health, and AI kiosks have the potential to bring high-quality care to underserved populations, reducing both geographic and economic barriers.

Patient Empowerment

Wearable devices, personal health records, and self-management apps give individuals greater agency over their own health data and care pathways.

Accelerated Research

Digital twins, large language models, and AI-assisted discovery are compressing research cycles — from drug development to population health modelling.

Societal Resilience

Evidence-based, data-informed approaches to public health governance strengthen societal resilience — a core goal of AIM's mission.

Research Portfolio

Featured Projects and Initiatives

AIM and its affiliated researchers are involved in a range of active, funded, and upcoming projects and initiatives in Digital Health and related areas. We also share here internal funding opportunities for AAU researchers.

Seed Funding

Digital Health Seed Funding

The AAU in collaboration with external funders is developing a seed fund for proof of concept projects in the domain of digital health. The seed funding is open to all faculties. A first round funded by KABEG will be organized in a workshop and matchmaking format in June/July 2026. Please contact your faculty's APC member for more information.

KABEGAll FacultiesJune/July 2026