Finnish Journal of eHealth and eWelfare

Lectio praecursoria, Shared decision-making: Towards patient-centred care

2025-03-07T10:31:24+02:00

Lectio praecursoria, The Digi-HTA, a new health technology assessment model for digital health technologies

2025-01-29T10:22:09+02:00

Professionals – developers of digital social and health care

2025-03-31T23:58:06+03:00

Person-centered data model: Key to system-level impact information in social and health care

2025-01-02T17:19:47+02:00

The costs of social and healthcare services are estimated to be around 30% of the state's expenses in 2025. The aging population is expected to weaken the dependency ratio, which increases the pressure for a reform. The success of the reform requires that the operations of the wellbeing services counties are based on effectiveness.
Effectiveness-based social and healthcare services require efficient data management and system integration. Many wellbeing services counties have adopted data lake solutions and developed data models for managing and processing large amounts of data. The person-centered data model combines social and healthcare service events, health and service needs, customer experiences, and cost data over time. This model challenges traditional organization-based models and can be used for various purposes: primary use in digital customer services, secondary use in effectiveness studies as well as in national and international comparative analyses.
In the Wellbeing Services County of Kanta-Häme “System-Level Effectiveness Evaluation in Wellbeing Services County” sub-study, the person-centered data model is utilized to study the effectiveness of digital services and cost-effectiveness of services, and to create a handbook for effectiveness-based data management. The project is part of the broader Impact Data Management in the Inland Finland Collaborative Area research project, funded by the Sustainable Growth Program for Finland (RRP), and it will last until the end of 2025.
The person-centered data model plays a key role in improving system-level effectiveness data in social and healthcare services. It ensures that customer data is available in a comparable form and supports management, development, and research. This is crucial in order to meet the growing challenges and improve the quality and effectiveness of the services.

Leveraging digital twin technology for healthcare: Mapping potential benefits and impacts through a hypertrophic cardiomyopathy case study

2025-01-20T07:39:45+02:00

Recognized as a strategic innovation trend, Digital Twin (DT) technology has successfully been applied across various sectors and are now also emerging in healthcare. The HEU project SMASH-HCM explores the potential of DTs to enhance personalized healthcare, focusing on hypertrophic cardiomyopathy (HCM). HCM is the most common inherited cardiac disorder, leading to variety of symptoms, and potentially sudden cardiac death.
SMASH-HCM is formed by 8 research partners, 3 hospitals, 3 SMEs, and a global health-technology corporation in collaboration with patients. The project will develop a DT platform to dramatically improve HCM stratification by integrating multilevel and multiorgan dynamic biophysical and data-driven models into a three-level deep phenotyping approach. SMASH-HCM advances the state of the art in human DTs by utilising in-vitro tools, in-silico models from the molecular to systemic levels, structured and unstructured data analysis, and explainable artificial intelligence - all integrated into a decision support solution for both healthcare professionals and patients.
Early results include identification of clinical needs elicited from HCM specialists and turned into functional requirements for the platform. We have also made progress towards developing in-vitro models including HCM patient cell lines and in-vitro cardiac tissue models, as well as the first line of HCM in-silico models of the cellular electrophysiology, biomechanics and energetics from the cell level to patient whole heart and vascular responses. The application of DT in HCM supports transition to P4 (predictive, preventive, personalized, participatory) medicine.

The relationship between attitudes, emotions and the intention to use the digital rehabilitation solution: Insights from Rwandan rehabilitation professionals

2025-02-02T11:52:54+02:00

Limited access to rehabilitation is a major challenge in low- and middle-income countries (LMIC). Digital rehabilitation (DR) has the potential to decrease this gap by offering effective and safe rehabilitation services for clients. This study aimed to investigate the relationship between rehabilitation professionals’ emotions and attitudes and intention to use the DR solution. Data was collected during two time periods in Rwanda: from July to November 2022, and from October 2023 to January 2024. A total of 58 rehabilitation professionals (67% men) completed the online survey at the beginning of the implementation of the DR solution and out of those, 23 (40%) responded to the follow-up survey. Attitudes were explored using Information Technology Attitude Scales for Health (ITASH), divided into three categories: 1) negative, 2) neutral, and 3) positive. Emotions were explored using an emotional scale with two factors “distress” and “positive arousal”. The intention to use the DR solution was assessed using a seven-point Likert scale, divided into three categories: 1) will not continue (points 1 to 3), 2) neutral (point 4), and 3) will continue (points 5 to 7). Crosstabs and Chi-Square were used to evaluate dependence between attitude and intention to use the DR solution. Binary logistic regression was used to assess the relationship between distress and positive arousal and intention to use the DR solution. Initially 91% of respondents had a positive attitude toward DR (M = 64, SD = 6.3). and positive attitude remained (M = 57, SD = 7.3, p = .860) at follow-up. A significant relationship between positive attitude and intention to use the DR solution (ꭓ2 = 18.33, p < 0.001) was found. Positive arousal was significantly related to a higher intention to use the DR solution (OR = 1.29, p = .008), while distress was not (OR = .89, p = .22). Distress decreased significantly (M = 9.7, SD = 3.0, p = .02) during the follow-up. The results do not definitively determine a relationship between attitudes, emotions, and the use of the DR solutions. However, positive emotions and attitudes appear to be linked to a higher intention to use the DR solution. Further research with a larger population is needed to confirm the relationship between emotions, attitudes, and use of the DR solutions in LMIC context.

Skull fracture detection for point-of-care diagnostics using microwave technique

2025-02-20T19:26:05+02:00

The possibility to detect severity of skull fractures outside the hospital already in the accident location would be a promising eHealth application. Such a point-of-care type of device would smoothen the patients’ path to the treatment after the accident. Additionally, frequent and safe monitoring of the healing process of skull fractures in smaller healthcare centers, as a new telemedicine solution, would enable early detection of potential problems. Microwave technique has shown significant potential for portable monitoring devices since it enables safe, low-cost, and high accuracy detectors. This paper has three research objectives: (1) to investigate the potential of microwave techniques for detecting common skull fracture types using antennas embedded in a small, portable monitoring device, (2) to evaluate optimal frequency ranges for skull fracture detection, and (3) to examine the impact of scalp thickness on fracture detectability. The research is carried out using electromagnetic simulation software with human head models resembling different scalp thicknesses and flexible antennas operating at 2.5–10 GHz. In the evaluations, scattering parameters are analyzed with the head models both with and without the fractures. The evaluation results show that different types of skull fractures can be detected with microwave technique. Fractures cause differences in scattering parameters ranging from 2 dB to 12 dB, depending on the type of fracture. The most optimal frequency ranges for detection are 3–5 GHz and 9 GHz. The thickness of the scalp impacts the detectability of skull fractures, yet fractures remain detectable even with the model with thicker scalp. These findings support the potential of microwave technique for developing portable, point-of-care devices for timely and precise skull fracture pre-diagnosis and frequent monitoring of the healing process. This approach particularly benefits young children, for whom conventional screening methods may pose more significant challenges.

Defining functional requirements for a self-management solution for Hypertrophic Cardiomyopathy patients – a multi-stakeholder multi-framework approach

2025-01-18T09:13:33+02:00

The SMASH-HCM project seeks to advance the management of hypertrophic cardiomyopathy (HCM) through the creation of a human digital-twin-based platform. The aim of the work described in this paper is to carry out the first step of developing the platform: the collection of design and functional requirements together with the end-users. This study focuses on defining the functional requirements for a digital health solution aimed at enhancing HCM patient self-management within this project. Drawing on Requirements Engineering principles, the work integrates key concepts such as health literacy, personalisation, behaviour change frameworks, and gamification to ensure the platform aligns with patient and clinical needs.
The methodology included a literature review, development of user personas through AI-assisted techniques, and structured user story mapping. Engagement with clinicians and patient advocates provided critical insights, and frameworks such as the Behaviour Change Wheel and Octalysis were applied to inform the design process and improve user engagement.
The analysis resulted in 19 design requirements for overall usability and usefulness of an HCM platform designed from a patient perspective and 19 functional requirements that address core aspects of HCM management and the patient’s preferences and needs. These include the development of interactive educational tools, features for monitoring health and lifestyle data, risk assessment visualisation, and improved communication channels between patients and clinicians. The findings emphasise the importance of intuitive, accessible, and effective tools to encourage sustained engagement and empower patients to manage their condition. By incorporating user-centred design principles and aligning with clinical objectives, the proposed solution aims to facilitate better health outcomes and long-term patient engagement.

Requirements elicitation for a health monitoring mobile application: a participatory design approach with clinicians and researchers

2025-01-05T17:02:11+02:00

Participatory methods have been introduced in healthcare to increase the adoption and acceptance of digital solutions for disease management and health promotion. However, there is not much evidence-based knowledge on how to integrate participatory methods into cohort studies effectively and efficiently. This study reports the results of a health monitoring application requirements elicitation by using a participatory design approach with clinicians and researchers.
An electronic survey containing open-ended questions was developed ad hoc in the research group to address requirements and use(r) purposes of the application. Minor amendments were made after piloting the survey with two researchers. A link to the survey was distributed to clinicians and researchers affiliated with the Faculty of Medicine at University of Oulu. All in all, 28 responses were received between April and June 2024. The responses have been analysed with deductive content analysis.
The analysis identified 25 themes under the four major themes relating to functional, content and ethical requirements of the application and the use(r) purposes of the application. The contents of the application should consider the physical, mental, social and environmental aspects to address the monitoring of holistic wellbeing. The application was preferred to contain diverse functionalities to track and monitor the user’s health in an automated manner and through user self-reporting. Extensive measures should be made prior and during the application usage to consider ethical requirements of the application. Purposes of use have been identified to include research, health promotion, personalised health management, diagnostics and policy and decision-making aid.
The mobile application should be developed to entail a comprehensive outlook on the individual’s current health status by focusing on automated functions, straightforward interface and ease of use to induce attraction. In the future, participatory design activities will be broadened by involving patient and public representatives to the next steps of mobile application development and implementation to further increase the inclusivity and relevance of the application.

Artificial intelligence in wellbeing services counties: management and experts’ perspectives on opportunities, challenges and AI readiness

2025-01-02T16:20:00+02:00

Artificial intelligence (AI) can be used to enhance healthcare efficiency and quality. New generative AI (GenAI) and large language models (LLM) offer novel opportunities for AI applications. This study examines management and expert perceptions of AI implementation opportunities and challenges in wellbeing services counties (WSCs), which are the responsible providers of healthcare and social welfare services in their region in Finland.
A qualitative interview study was conducted in two phases from Nov 2023 to Feb 2024. First, 28 participants were interviewed semi-structurally. Thematic analysis was used to identify potential AI use cases, main use contexts, and related benefits and challenges. Second, 16 participants (14 new persons and two already interviewed) validated the results in four group interviews and prioritised the use contexts by their potential for WSCs. The framework of Roppelt and colleagues was used to analyse the AI readiness of WSCs.
Six AI use contexts were identified and prioritised: 1. Clinical healthcare, 2. Patient interaction and self-care, 3. Support services, 4. Management, 5. Preventive healthcare, 6. Social welfare services. AI readiness should be increased by the government by supporting organisational collaboration, experience sharing and regulatory interpretation. Healthcare organisations need to improve AI competence and skills at all levels. Regulation and WSC culture not supporting experimentation were identified as main challenges for broader AI implementation.
AI particularly GenAI, is seen as a promising technology to address workload, financial, and service demand challenges in WSCs. Challenges can be mitigated through focused collaboration and actions within and between stakeholder organisations. AI implementation research in healthcare should consider the rapid development of AI, including increasingly human-like behaviour and integration into physical robots.

Perceptions of AI competence in social and healthcare services: Readiness, reliance and realism

2025-01-12T08:29:51+02:00

Artificial intelligence (AI) is transforming the health and social service environment through increasingly advanced and autonomous digital solutions. AI competence is recognized as an emerging dimension of digital competence, leading to a growing demand for AI-related skills among health and social service professionals (HSPs). In this study, AI competence is viewed as an orientation towards understanding and learning about AI in different professional contexts, including AI ethics, the ability to apply AI, and the perceived AI self-efficacy. The research questions were as follows: 1) How do HSPs evaluate the level of their AI competence? and 2) Does qualitative and quantitative work experience correlate with the perceived AI competence? The study used survey data collected in 2024 by the Ministry of Social Affairs and Health in Finland. The sample comprised 735 HSPs, approximately one-fifth of whom had supervisory duties, while approximately 60% worked primarily in customer or patient care. The respondents perceived AI as a crucial component of overall digital competence. However, they also expressed that their current level of competence, for example, in the ethical implementation of AI, was insufficient relative to the growing importance of AI technologies in everyday work. HSPs with 16–20 years of work experience exhibited the greatest AI competence deficit. In an occupational comparison, AI competence deficit was less probable among practical nurses, likely due to the well-established role of health technologies in their education in Finland. To enhance AI competence among HSPs, national and regional collaboration with educational institutions should be strengthened, incorporating both formal and informal learning opportunities.

The development of public online services for assessing diet quality, having automated feedback, and getting support for dietary changes: the Finnish Nutrition Navigator and the Finnish Nutrition Path (Ravitsemusnavigaattori and Ravitsemuspolku)

2025-01-12T08:25:08+02:00

Nutrition is one of the most important factors in the prevention of noncommunicable diseases. However, most Finns do not adhere to the nutrition recommendations. Furthermore, there are no commonly used digital dietary screener tools to measure and report diet quality. No such open tools or reliable consumer-oriented nutrition websites exist either for consumers interested in their quality of diet.
Two public online services were created including (1) a web app to measure diet quality with automated personalized feedback system based on the scientifically validated Healthy Diet Index (HDI) and nutrition recommendations, and (2) a website for a self-care path to support the individual in making dietary changes. We utilized service design, several user and expert interviews and feedback questionnaires in the development. The work is part of the National and North Savo regional FOODNUTRI projects funded by Research Council of Finland and North Savo Regional Council, co-funded by the European Union.
The Finnish Nutrition Navigator and the Finnish Nutrition Path were launched in November 2024 (in Finnish). The services are publicly available at no cost, targeted at adults aged 18–75 years. Services can be used independently or with a professional. The professional can guide the patient/citizen to fill in the dietary questionnaire in the Finnish Nutrition Navigator from which the user will get the automated feedback and a code. The user can give the code to the professional so that the information about the diet quality can be utilized and marked in a standard form. The Finnish Nutrition Path gives information and support for dietary changes.
The online services support (1) consumers seeking help with their diet, (2) health care and wellbeing professionals in dietary screening and nutrition counseling, (3) researchers to collect data on diet quality, and (4) health promoting sector to utilize data on population diet quality for reporting and planning and measuring effectiveness of health promotion actions. Using the services would standardize dietary assessment and documentation and provide evidence-based information of diet quality for consumers. The data collected can be used to study diet quality of the Finnish adults and the effectiveness and cost-effectiveness of nutrition and lifestyle counseling, allocate resources in health care, and support work to promote health and wellbeing.

Ecosystem supporting the commercialization of digital health innovations

2025-01-09T08:23:36+02:00

Digitalization has significantly impacted various industries; however, its full potential in healthcare remains unrealized. Despite the promise of digital health solutions to modernize healthcare and benefit the population at scale, their adoption and scalability lag behind other sectors due to ethical, regulatory, economic, and technological challenges. This article examines the barriers to commercializing digital health solutions and proposes a systematic approach to accelerate growth in this sector, presenting a preliminary commercialization roadmap.
In Finland, numerous wellbeing services counties, higher education institutes, and cities support testbed activities, offering real-world testing environments for health and wellbeing product developers. However, these activities face challenges such as resource uncertainty, funding issues, and lack of a unified national model.
This study utilized thematic interviews and a structured survey to gather insights from stakeholders in the digital health ecosystem. Key challenges identified include the ethical unsustainability of applying agile software development methods in healthcare, the complex and often prohibitive regulatory environment, and the lack of industry-specific funding and competence. The study also highlights the need for interdisciplinary collaboration and effective commercialization pathways.
The findings suggest that national coordination of testbed activities and a comprehensive understanding of the digital health innovation pathway are crucial for fostering innovation. Enhanced funding mechanisms, clear regulatory strategies, and platforms for interdisciplinary dialogue are recommended to support the commercialization of digital health solutions. A preliminary model illustrating the development pathway of digital health innovations is proposed, aiming to address identified challenges and streamline the commercialization process.

Conferences

2025-03-31T18:37:06+03:00