Early detection of breast cancer remains a critical challenge, particularly for women with dense breast tissue where mammography often has reduced sensitivity. This proof-of-concept study explores the feasibility of a wearable breast health monitoring vest utilizing microwave sensing as a complementary approach for early detection using anatomically realistic breast phantoms representing all four clinically recognized breast density categories. The vest integrates flexible antenna sensors, positioned according to prior electromagnetic simulations to ensure optimal coverage. Scattering parameter (S-parameter) measurements are performed under two conditions: reference models without tumors and models containing centrally located tumors of approximately 1 cm in diameter. The realistic phantom-based analysis addresses three research questions: (1) the accuracy of tumor detection across different breast densities, (2) the impact of breast density on microwave signal behavior and detection performance, and (3) practical implications for developing portable, patient-friendly solutions for telemedicine and self-screening. Results provide insight into the challenges posed by dense breast tissue and highlight the potential of microwave-based wearable systems as a complementary tool for early breast cancer detection. Although the present work represents phantom-based proof-concept evaluations, these initial findings offer valuable guidance for optimizing the vest design and advancing toward subsequent clinical validation studies.
Finland has long been a forerunner in producing structured client data, yet gaps remain in data quality, usability and national guidance. To support interoperable services, the Finnish Strategy for Healthcare and Social Welfare Code Systems 2025–2030 outlines a plan for strengthening semantic interoperability through coherent governance of classifications, terminologies and value sets. The strategy identifies key priorities, including the adoption of international code systems such as SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms), ICD-11 (International Classification of Diseases, version 11), and LOINC (Logical Observation Identifiers Names and Codes). The strategy aims to enhance data quality and reusability while supporting service provision, information management and effective use of health and social welfare data both in Finland and within the broader European context.
Patient-centred learning has always been a fundamental element of medical education. Consequently, the use of virtual patient simulators has become increasingly common in medical education. The aim of this study was to generate new knowledge on the pedagogical value and impact of a virtual patient simulator, specifically in relation to students’ learning processes. The study was conducted in Finland at one university as part of an elective course offered to fourth- and fifth-year medical students (n = 25) between 2023–2025. The course focused on practising clinical reasoning by solving 10 virtual patient cases designed to simulate primary healthcare scenarios. The students received personalised feedback from the simulator. The students were then required to reflect on their reasoning processes. The patient cases were subsequently reviewed in joint face-to-face sessions. The data for this study consisted of students’ written reflections and written course feedback. The research methodology applied a qualitative, theory-guided, abductive thematic analysis. Targeted learning outcomes for licentiates of medicine, activity theory and expansive learning theory were used as the conceptual framework for examining virtual patient cases. The results indicate that virtual patient cases can effectively support medical students’ deep learning and clinical reasoning skills, as reflected in students’ written reflections. The findings suggest that the added value of virtual patient cases lies in their ability to integrate several key competence areas. From the perspective of expansive learning, virtual patient cases may challenge the traditional teacher-centered activity system by shifting the initiative for learning towards students’ own learning needs.
Despite increased awareness and understanding of healthy lifestyles, interventions typically have only short-term effects on behavior. Limitations of traditional behavior change theories and the lack of theory integration hinder theory-driven behavior change applications. The aim of this systematic review is to synthesize existing evidence on strategies for enhancing motivation and engagement in lifestyle change within digital health promotion interventions. This review was conducted according to the guidelines of the Joanna Briggs Institute (JBI) and a Preferred Reporting Items for Systematic Reviews (PRISMA) statement. All studies were searched in online databases PubMed, ProQuest, ScienceDirect, and CINAHL. The search period was from inception to May 17th, 2025. The selection of the studies was carried out jointly by two independent reviewers. The research quality was evaluated using the JBI critical appraisal tools. 1404 studies were screened, and 19 were included. The interventions included mobile-based, web-based, and multi-component interventions. Population ranged from 47 to 4591 participants. Interventions targeted diet quality, calcium intake, physical activity, weight gain prevention and weight-related behaviors, metabolic syndrome (MetS) prevention, substance use, gambling, digital media use, sexual health, preconception care, and self-selected health behaviors. Many interventions were developed using health behavior change techniques and theoretical frameworks. Interventions used multiple different methods supporting motivation and engagement. To achieve behavior change through lifestyle interventions, it is essential to design interventions that foster motivation and sustain user engagement. Modern digital solutions could help improve the usability and engaging elements in interventions. Future studies should aim to investigate post intervention effects on behavior change to determine the long-term effects of digital lifestyle change interventions.
Evidence indicates that digital care pathways (DCPs) are more effective at improving patient outcomes than traditional methods. Personalized approaches and comprehensive content play key roles in supporting long‑term success and adherence. Likewise, pathways specifically designed for individuals with chronic pain have been shown to reduce pain‑related anxiety and catastrophic thinking patterns. Remote access to services helps conserve healthcare resources, yet user acceptability remains essential for the success of digital health solutions. While DCPs can reach broader populations with fewer resources, cost savings are not guaranteed and depend on leadership‑driven process changes. Studies on Tonsillectomy, Multiple Sclerosis, and Sleep Apnea pathways highlight the importance of analyzing service delivery and patient flow. While satisfaction with these DCPs is high, synchronous services remain necessary, indicating untapped potential. DCPs facilitate new modes of information exchange, offering structured educational content, and enabling professionals to understand patients’ home environments better. They also contribute to informed consent processes, as demonstrated by the kidney donation study, and require a combination of clinical and digital competence. Patient–professional interaction is reshaped by increased patient-centeredness and empowerment. Digital literacy enhances engagement in decision-making and supports participatory care. The competence and proactive attitude of healthcare professionals are essential for successful implementation, yet a lack of organizational support may hinder their ability to guide patients. DCPs have increased patient involvement and altered professional roles, freeing more time for meaningful interaction. However, disparities persist, particularly among elderly patients and those with limited digital skills. Ensuring equitable access to and effective use of DCPs requires attention to professional competencies and inclusive design. Overall, the findings support the effectiveness of Omapolku DCPs while highlighting areas for further development and integration. Additional research is needed to strengthen the evidence base and optimize implementation.
National telehealth and eHealth societies are essential actors in digital transformation, yet their impact remains uneven, fragmented, and insufficiently coordinated. Drawing on trends across ten countries, including Finland, Germany, India, the Ivory Coast, Japan, Jordan, Morocco, Nigeria, Poland, and Slovenia, this opinion argues that these societies hold crucial but underused positions in global digital health governance. They contribute to evidence generation, regulatory discourse, workforce development, and the adaptation of digital solutions to local contexts. However, without structured mechanisms for collaboration, such strengths remain isolated and global disparities deepen. We propose that the International Society for Telemedicine and eHealth (ISfTeH) can evolve from a networking platform into an orchestrator that consolidates knowledge, reduces duplication, and supports equitable digital transformation. The future of telehealth depends not only on technological innovation but also on institutions’ capacity to share expertise, co-develop strategies, and build collective capabilities.
Finland’s nationwide health registers and universal healthcare system provide comprehensive, longitudinal electronic health record data with strong potential for artificial intelligence-driven clinical research. Despite their coverage and richness, raw electronic health record datasets are not directly usable for advanced analytics due to fragmentation, heterogeneity, missingness, and inconsistencies in documentation and coding. This study describes data quality challenges encountered while preparing a breast cancer cohort (diagnosed 2012–2022) from the Wellbeing Services County of North Ostrobothnia as a preparatory step for artificial intelligence-based survival modelling. The initial dataset included 8074 patients across multiple domain-specific data files capturing diagnoses, laboratory results, pathology reports, medications, and procedural information. Following predefined cohort restrictions and preprocessing steps, 1967 patients remained for analysis. Identified challenges were grouped into four categories: 1. human-generated errors 2. decentralization-generated issues 3. time or system life-cycle–generated inconsistencies and 4. data governance/coding issues. The study adopts a qualitative research design aimed at systematically characterizing data quality challenges relevant to artificial intelligence application, and no predictive model was developed at this stage. The findings demonstrate that substantial preprocessing and data loss are often unavoidable in real-world electronic health record research and emphasize the need for standardized documentation, harmonized data structures, and closer collaboration between healthcare professionals, system developers, and data scientists to fully realize the potential of register-based electronic health record data in reliable artificial intelligence-driven research.
Digitaalisten työkalujen ja digipalveluiden käyttö on lisääntynyt merkittävästi terveydenhuollossa viime vuosikymmeninä. Työterveyshoitajien ammatissa digitaalisten ratkaisujen hyödyntäminen on olennainen osa työnkuvaa, sillä niiden avulla voidaan tehostaa asiakastyön prosesseja, parantaa tiedonkulkua sekä vahvistaa ennaltaehkäisevän terveydenhuollon toteutumista. Tämän tutkimuksen tarkoituksena oli kartoittaa työterveyshoitajien digiosaamisen tasoa ja tunnistaa siihen vaikuttavia tekijöitä. Aineisto kerättiin validoiduilla DigiHealthCom- ja DigiComInf -mittareilla Suomen Työterveyshoitajaliitto ry:n jäseniltä (N=986) maaliskuussa 2025. Vastausprosentti oli 12 (n=114). Mittarit sisälsivät kysymyksiä digitaalisesta osaamisesta ja digitaaliseen osaamiseen vaikuttavista tekijöistä neliportaisella Likert-asteikolla itsearvioituna. Aineisto analysoitiin kuvailevin tilastollisin menetelmin. Tulokset osoittivat, että työterveyshoitajien itsearvioitu digiosaamisen taso oli hyvää. Tilastollisesti merkitsevää eroa ilmeni vastaajan iän, työkokemuksen, työpaikan koon sekä työterveyshuoltoon pätevöittäneen koulutuksen käyneiden osalta. Parhaimmiksi osa-alueiksi arvioitiin ICT-osaaminen ja digitaalisten ratkaisujen eettinen osaaminen. Työterveyshoitajan pätevöittävä koulutus korostui myönteisesti digitaalisten ratkaisujen eettisessä osaamisessa. Suurissa organisaatioissa työskentelevät arvioivat digitaalisuuden osana työtä korkeammaksi suuremmalle tasolle kuin pienissä organisaatioissa työskentelevät. Kaikki ikäryhmät arvioivat kollegoiden vaikutuksen digiosaamiseensa keskimääräistä suuremmaksi, mutta alle 40-vuotiaat arvioivat vaikutuksen pienimmäksi. Yli 60-vuotiaat arvioivat kollegoiden vaikutuksen digiosaamiseen suurimmalle tasolle ja merkityksellisintä se oli kokeneimmilla työterveyshoitajilla. Digiosaamiseen vaikuttavista tekijöistä heikoimmiksi koettiin organisaation ja yksikön käytänteet digiosaamisen kehityksen tukena sekä johtajien tuki. Tulokset osoittavat työterveyshoitajien arvioivan digiosaamisensa pääosin hyväksi, mutta organisaatioiden ja johdon tarjoama tuki ei riitä sen systemaattiseen kehittämiseen. Lisätutkimusta tarvitaan erityisesti digiosaamisen tukemisesta organisaatioissa ja kollegoiden vaikutuksesta työuran eri vaiheissa.
Successful implementation of digital health technologies (DHT) into nursing is a multifaceted process, requiring careful consideration of individual, organisational and external factors. Building digital literacy in the nursing workforce is key in successful DHT implementation, but little is known about how the need to expedite the digital health transformation during a health care crisis affects DHT implementation in nursing. The aim of this cross-sectional mixed methods study was to explore nurses’ experiences of the implementation and use of DHTs to support care during the COVID-19 pandemic in Finland. A previously developed survey was translated into Finnish and distributed via professional and social media networks of the researchers using the snowball technique. The data analysis included descriptive statistics, inductive qualitative content analysis and thematic categorisation. 55 participants including registered nurses and nurse managers responded to the survey. The respondents were asked to describe the implementation of up to three DHTs, resulting in 84 individual DHT descriptions. These included DHTs to promote communication between the service user and the professional, professional communication, patient monitoring, documentation, medication administration and nursing management. Four approaches to support nursing professionals through digital health transformation were identified: 1) promoting the usability of DHTs, 2) enhancing patient care through DHTs, 3) providing comprehensive digital skill training and 4) fostering motivation to DHT use. The participants expressed mainly positive attitudes and experiences regarding DHT implementation, but the results indicate that nursing-specific needs have not adequately been addressed in their development and implementation, calling for better nurse involvement in interdisciplinary DHT development initiatives. Enhancing digital literacy throughout all levels of nursing as well as the strategies to successfully guide expedited implementation of DHTs during future crises are needed to support the provision of safe and high-quality care. Strategies to strengthen the organisational and digital infrastructure to support and motivate nurse engagement in DHT development can improve their usability, acceptability, and outcomes.
Mental disorders are among the leading causes of disability worldwide, creating an increasing demand for timely and effective mental healthcare. Digital decision support systems (DDSS) have emerged as promising tools for enhancing the assessment and treatment navigation of mental disorders. This review examines the international development and maturity levels of DDSS in mental healthcare. The objective is to identify recent systems, analyze their key features, and propose a technological maturity model for these systems, while comparing them to the Finnish Therapy Navigator (FTN) services. The study used a scoping review methodology to map the existing literature and identify relevant DDSS. The review was conducted in accordance with the PRISMA extension for scoping reviews (PRISMA-ScR) guidelines. A framework for a technological maturity model was developed through a thematic analysis of findings based on the prevalence, complexity, and clinical utility of system features, comparing functional features across systems to identify emerging patterns in technological sophistication. A total of 35 studies on adult DDSS and 38 studies on adolescent DDSS met the inclusion criteria, of which 10 distinct DDSS were identified for adults and 9 for adolescents, with one system designed for both groups. The most prevalent features included multi-disorder screening (100%), summary report generation (100%), and contextual factor mapping (65%). Less common but potentially more advanced features included automated treatment recommendations (35%), response-based therapeutic content (20%), and AI-driven capabilities such as chatbot with natural language processing and probabilistic reasoning (5%). Based on the prevalence and perceived clinical utility of these features, we propose a three-tiered technological maturity model to classify DDSS for mental healthcare assessment and treatment navigation: 1) structured data collection, 2) rule-based decision support, and 3) intelligent and adaptive decision support. FTN services fall within the first maturity level, as they primarily facilitate structured assessments without automated treatment recommendations. The proposed model highlights the transition from passive tools to interactive systems and to intelligent and adaptive platforms. The development of mental healthcare DDSS is still in its early stages, with significant potential for future advancements.
Innovation ecosystems are recognized as significant actors in promoting the adoption of digital innovations, such as artificial intelligence (AI). This study examines the organizational motivations for participating in Finland's government-led AI innovation ecosystem for healthcare and social welfare, which was established by the Ministry of Social Affairs and Health in 2024. The research addresses two questions: (RQ1) What motivates organizations to join a government-led healthcare and social welfare AI innovation ecosystem, and what are the key mechanisms behind joining? and (RQ2) How do different types of organizations perceive and seek value within this ecosystem? Employing a theoretical framework that combines innovation systems theory and ecosystem theory, this study analyzes data from ecosystem member organizations (N=166) collected via an online questionnaire during the ecosystem's initial four months, from June to September 2024. Five key interconnected mechanisms driving participation were identified: (1) knowledge synergy, (2) resource allocation, (3) legitimacy enhancement, (4) regulatory influence, and (5) societal impact. These mechanisms interact in systemic ways, with each supporting and reinforcing others when present, while their absence can constrain ecosystem engagement. Private companies focus on market opportunities, public organizations prioritize organizational improvements and efficiency, and research institutions emphasize knowledge development alongside practical applications. The research contributes to the theoretical understanding of government-led innovation ecosystems, particularly for advancing AI development in public healthcare and social welfare, and offers insights for designing and managing such initiatives.
In Finland, social and health care information management has been harmonized over the past ten years, especially with the development of recording patient and client information. However, the client and patient information systems in use by the organizations do not sufficiently support the information needs of customer management or guide individual but consistent client and patient processes. This case study examined customer management and value creation using the Person-Centered Data Model (PCDM) developed in the Finnish wellbeing services county of Kanta-Häme. The aim of the research was to understand the usability of a data-based customer management model and to identify the factors affecting value creation. In this study, customer management includes both the utilization of available information, and the practices used to identify customers’ service needs and organize services suitable for them. The research findings are based on semi-structured expert interviews conducted in the case organization, documents from the case organization, and a survey administered to the interviewees. The interviewees were gathered with snowball sampling in such a way that the interviewees suggested other interviewees who were experts in the subject area. The interview data was analyzed using theory-driven content analysis and the survey data was examined using the means (M) and standard deviations (SD) of the responses. This study found that a model based on PCDM is central to the organization’s information management and customer management. The model collects the information needed to provide the services and connects it to the individual customer, supporting customer management in the customer relationship management system (CRM). The CRM system uses PCDM and works to support professionals, improving customer experience and the allocation of resources. This study identified factors both promoting and hindering value creation. Promoting factors were, for example, the importance of strategy and available information, while hindering factors were, for example, operational models and lack of data. PCDM can support effective social and health care in accordance with the Quintuple Aim principles.
Digital health services have the potential to improve healthcare quality and patient safety within the wellbeing sector, but their adoption has many barriers. The aim of this study was to explore barriers to digitalized wellbeing services for children and families in Finland from healthcare leaders' views. Seven leaders from the Finnish wellbeing sector participated in the study. The data were thematically analyzed using an inductive approach. The results revealed two themes: internal and external barriers to digitalization within the healthcare context. Internal barriers encompassed four subthemes: operational differences and diversity in interactions, organizational changes and resource constraints, lack of digital competence and training, and insufficient coordination and unclear responsibilities. External barriers were identified as challenges related to technology development, challenges with laws and regulations, lack of updated education and research, and challenges related to citizens. By addressing these obstacles, healthcare leaders can enhance their capacity to drive digital transformation and improve access and equity within digital wellbeing services for children and families.
Tämän tutkimuksen tarkoituksena on tuottaa uutta tietoa palliatiivisen hoidon piirissä olevista potilaista ja ennakoivista hoitosuunnitelmista. Tutkimuksen tavoitteena on lisätä ymmärrystä rekisteritietojen hyödyntämisestä erikoissairaanhoidon päivystyskäyntien ja ennakoivien hoitosuunnitelmien seurannassa. Tutkimus toteutettiin rekisteridataan perustuvana poikittaistutkimuksena yhden suomalaisen hyvinvointialueen erikoissairaanhoidon päivystyksessä poimimalla retrospektiivisesti data hyvinvointialueen rekisteristä ajanjaksolta 01/2018–08/2023. Aineisto sisälsi potilasmäärän, diagnoosit, päivystykseen tulotavan, ICPC2-luokituksen mukaisen käyntisyyn, sekä ennakoivat palliatiivisen hoidon hoitosuunnitelmat, jotka oli kirjattu järjestelmään toimenpidekoodi WPA10 avulla. Aineisto analysoitiin kuvailevalla analyysimenetelmällä. 01/2018–08/2023 välisenä aikana yhteensä 178 619 potilasta kävi erikoissairaanhoidon päivystyksessä ja käyntejä kirjattiin yhteensä 292 093. Tutkimusjakson aikana 161 palliatiivista potilasta kävi päivystyksessä yhteensä 177 kertaa. Näiden potilaiden mediaani-ikä oli 75 vuotta. Yli puolet palliatiivisista potilaista saapui päivystykseen ambulanssilla. Palliatiivisten potilaiden yleisimmät päädiagnoosit olivat kasvaimiin liittyvät (C-diagnoosit) ja verenkiertoelimistön sairaudet (I-diagnoosit). Yleisimpiä päivystyskäynnin syitä palliatiivisilla potilailla olivat yleinen heikkous (A04) ja hengenahdistus (R02). Ennakoivan palliatiivisen hoidon hoitosuunnitelman (WPA10) osalta 180 henkilöllä oli sekä Z51.5-diagnoosi että ennakoiva hoitosuunnitelma kirjattu missä tahansa hyvinvointialueen yksikössä. Näistä henkilöistä noin joka viides vieraili tarkastelujakson aikana päivystyksessä. Tämä tutkimus korostaa ennakoivan hoitosuunnitelman dokumentoinnin tärkeyttä, sillä huolellisella ja yhtenäisellä dokumentoinnilla voidaan vähentää tarpeettomia päivystyskäyntejä ja parantaa hoitoa. Vaikka dokumentoitujen ennakoivien hoitosuunnitelmien määrä on kasvanut, monet palliatiiviset potilaat käyvät edelleen päivystyksessä. Tämä osoittaa tarpeen kehittää tehokkaita palliatiivisen hoidon strategioita. Ennakoivien hoitosuunnitelmien järjestelmällinen dokumentointi toimenpidekoodin avulla on keskeinen palliatiivisten potilaiden hoidon hallinnassa ja päivystyspalveluiden tarpeen vähentämisessä. Tämä tutkimus korostaa kehitystyön tarvetta ennakoivien hoitosuunnitelmien toteuttamiseksi kliinisessä käytännössä.
