Högskolan i Skövde

Background: The global shift towards an ageing population and workforce shortages increases demands on health and social care systems. Proactive, personalized, and resource-efficient care models are therefore needed. Continuous monitoring using wearables, together with artificial intelligence (AI), offers potential for early detection of health deterioration and timely intervention. Still, existing solutions often target single diseases and lack integration into clinical workflows.

Objective: This article presents the study protocol for the project Predicting Care Needs of Older Adults in the Healthcare System through AI-Enabled Analysis of Patient Monitoring Data (PAI), which aims to develop an AI-driven predictive model based on data from wearables (smartwatches) to identify health decline among older persons in the near future. In addition, the project will evaluate the pilot implementation of this model within health and social care settings in three countries and generate recommendations for future adoption.

Methods: To answer the project aim, the AI model will be developed using historical datasets from wearables linked to emergency health care visits. To guide and evaluate the pilot implementation in Sweden, Norway, and Spain, staff from health and social care, managers, and IT professionals will be interviewed before implementation to explore current work practices and relevant contextual factors. Users of the smartwatch (older persons) will also be interviewed to explore their experiences, needs, and expectations. Follow-up interviews will be conducted after implementation to capture users’ and health and social care staff’s experiences of use. In addition, quantitative data on the AI model’s performance will be collected. The recommendations will be developed in an iterative process, including both researchers and stakeholders.

Expected Results: The project will identify key data requirements, deliver a predictive AI model, and develop evidence-based recommendations to support the responsible and scalable implementation of the proposed AI-solution in healthcare and social care settings.

Conclusions: By combining technical innovation with real-world implementation research, the PAI project seeks to advance the use of AI in care for older persons, support proactive and person-centered interventions, and contribute to more sustainable healthcare systems.

Plain Language summary

As people live longer, many older persons develop complex health conditions that require extended care. At the same time, health and social care services are facing growing pressure from staff shortages and increasing demand. Therefore, they need to act early to preserve older persons’ health while conditions can be managed at home. This project explores how artificial intelligence (AI) can assist by using information from smartwatches and other monitoring data to identify early signs of health decline. The aim is to predict when someone may be at risk of a serious health issue in the next days or weeks, giving health and social care staff the chance to act earlier and possibly prevent it. To achieve this, historical data will be used to build an AI model that later will be pilot tested in health and social care settings in Sweden, Norway, and Spain. It will assess whether this technology can improve care, reduce the strain on health services, and support older persons in living independently at home for longer.

Background: Healthcare systems struggle with an imbalance between the required resources and existing demand. The number of patients seeking emergency care has increased steadily, placing additional strain on emergency departments, which are also challenged by a high volume of non-urgent visits. When patients perceive a need to seek emergency care, the decision is influenced by various factors, including the availability and quality of support and the information they use to make informed decisions. Digital health support encompasses a range of technologies designed to assist at various stages of the healthcare continuum. They are intended to support patients and personnel, as well as effective resource utilization in healthcare. More knowledge is needed to understand the factors involved when patients decide to seek emergency care, and how digital health support can be introduced to benefit both patients and personnel. This study aims to identify and understand important factors that influence patients’ decisions when seeking emergency care, focusing on the information they gather and various sources of support, especially digital health support.

Methods: This qualitative interview study included 31 participants seeking care at an emergency department in western Sweden. The data were analysed through reflexive thematic analysis.

Results: The analysis resulted in four themes: (1) human support needed; (2) going back and forth about making the right decision; (3) digital reassurance; and (4) digital support with hesitation. The participants based their decisions on various forms of information and support. Patients who used digital health support reported mixed experiences, describing both opportunities and barriers. Some patients mentioned expectations for future digital solutions, mainly expressing a desire to preserve human contact.

Conclusion: Patients strive to make the right decision about whether, when, and where to seek care in perceived urgent situations. In this decision-making process, patients use human and digital support for guidance and to facilitate their decision. However, navigating the healthcare system is challenging for patients, and digital health support provides both enabling opportunities and several obstacles. The results of this study indicate that further development of digital health support for patients seeking emergency care would benefit if end users were included in the co-creating process.

This paper wrestles with how to manage prominent global transition challenges on local and regional scales to co-create a better world. It introduces an approach to managing navigation in wicked problems by expanding maneuverability to increase capacities to drive transformation in multi-actor decision spaces in the context of complex societal challenges. This demands a transdisciplinary engineering approach, where we propose using the concept of relational interfaces to enhance understanding across boundaries in shared problem spaces, providing a foundation for co-creation and collaboration over knowledge domains to enable transformational momentum and navigational capacity. A multiplicity of pressing issues on the global canvas urges action on local and regional scales. This paper draws on cases from regional healthcare system development, under demographic and resource-driven pressures in the Global North, and from regional energy transition planning, where diverse stakeholders require improved coordination for co-creation in the face of cultural, economic, and institutional disparities. Wicked problems often blind actors to their full scope unless addressed collaboratively. This paper emphasizes the need to surface the knowledge and experience of actors through visualizations and digital models, to foster openness and co-creation. Through enhanced understanding of how parts interact within the holistic system across silos, this is enabling actors to manage interfaces between contributions. The conclusions from the empirical cases show the potential of the identification and management of these interfaces to unlock profound change, fostering collaborative solutions to persistent societal challenges — a step toward co-creating a better world and a vital calling for future transdisciplinary engineers.

This chapter summarises findings from an empirical study investigating how digital healthcare solutions should be developed to satisfy individual demands for understanding and managing healthcare information and activities. Despite the quick development of new digital healthcare services to accomplish service efficiency and cost-effectiveness, and at the same time supporting the achievement of a wide range of sustainable development goals, some users perceive challenges due to different age-related, physical, and cognitive starting points. The chapter offers a broad view of the development of digital healthcare solutions and considers literature and the perspectives of technologists, caregivers, and users through a qualitative approach using interviews and autoethnography. A main finding is that the development of digital healthcare solutions that enhance health literacy needs a comprehensive strategy, in which users, healthcare providers, family members, and other stakeholders should participate.

European higher education institutions (HEIs) are facing increasing demands for more flexible learning and flexibility in learning paths.

This report from a 2023 European University Association Learning & Teaching Thematic Peer Group on “Flexible learning and teaching” explores the complexity of implementing flexible learning at HEIs, starting by defining what it means and entails for the institution, and its members and entities (staff, students, leadership, faculties). With the view that the development of flexible learning is an essential condition for the future of learning at universities, the group identified challenges and examples of practice, and offered recommendations for institutions to reflect on their strategy and build capacity for flexible learning.

This paper presents results from a simulation case study analyzing care strategies for elderly patients in a regional healthcare system (HCS) in Sweden. Three strategies to reduce emergency visits, hospitalisations, and stays were evaluated: care coordinators at emergency departments, mobile health clinics visiting fragile patients in their homes, and proactive primary care. Using system dynamics modelling and empirical data, the impact on the regional HCS was explored considering the reduced care demand and demographic changes. Subsequently, the impact on the population's health status was assessed. Combining strategies yielded the best outcome, but improving patients' health status may increase long-term care demand. The study emphasizes the importance of implementing these strategies to offer better care for elderly patients and reduce healthcare costs. Findings highlight the potential long-term effects of improving health status and the need for a comprehensive approach to address the evolving care demands of an ageing population.

Digitalization is forcing the industry to rethink current practices in all business domains, pushing for a digital transformation of business and operations at a high rate and, thus, paving the way for new business models and making others redundant. For small and medium-sized companies (SME), in particular, it is an enormous challenge to keep up with the pace of technological development. Several initiatives have argued the industry’s need for continuous digitalization, innovation, transformation ability, and future skills and competencies development. However, the advancement of the Swedish industry in this area has been uneven, where larger organizations have begun their digital transformation journey to some extent, but SMEs risk falling behind. In addition to the technological transformation, the challenges regarding the industries’ skills supply need to be solved, where a workforce with the right competencies, knowledge, and skill sets are equally, if not more, important for remaining competitive. One of the key elements to face these challenges in the companies will be to recruit knowledgeable employees or re-skill the existing ones. Efficient access to relevant knowledge and skills is still a major concern for companies that will surely affect their competitiveness for a long time to come. This paper elaborates on the opportunities and challenges that Swedish universities face in the context of lifelong learning and education for industry professionals. The paper presents results and experiences gained from a lifelong learning project for industry professionals at the University of Skövde in collaboration with ten industry partners. The results from the project show that in addition to pedagogical methods, current structures and policies within academia need to be further developed to effectively serve industry professionals. The paper also presents a concept of education for industry professionals in the lifelong learning context based on the results and experience gained from the project.

The expected demographic changes, and especially the rise in life expectancy, will considerably increase elderly patients' demand for healthcare. There are different strategies that can offer better care for these patients, reduce their unnecessary visits to the emergency departments, and in consequence, reduce the number of hospitalizations and days at the hospital. This study employed system dynamics to analyze the economic and quality-related effects of different closer care strategies such as investments in care coordinators and mobile health clinics, as well as to offer proactive care in the primary care facilities for elderly patients. The results indicate that a combination of the different strategies will support better care for patients, will reduce hospital costs and will reduce the existing pressure on the emergency department. The paper also reflects on the process followed to conduct the study and the lessons learned. 

Lean is and will still be one of the most popular management philosophies in the Industry 4.0 context and simulation is one of its key technologies. Many authors discuss about the benefits of combining Lean and simulation to better support decision makers in system design and improvement. However, there is a lack of reviews in the domain. Therefore, this paper presents a four-stage comprehensive review and analysis of existing literature on their combination. The aim is to identify the state of the art, existing methods and frameworks for combining Lean and simulation, while also identifying key research perspectives and challenges. The main trends identified are the increased interest in the combination of Lean and simulation in the Industry 4.0 context and in their combination with optimisation, Six Sigma, as well as sustainability. The number of articles in these areas is likely to continue to grow. On the other hand, we highlight six gaps found in the literature regarding the combination of Lean and simulation, which may induce new research opportunities. Existing technical, organisational, as well as people and culture related challenges on the combination of Lean and simulation are also discussed.

The rapid changes in the market including globalization, the requirement for personalizedproducts and services by the customers, shorter product life-cycles, the exponential growthof technological advances, and the demographical changes, will demand organizations toeffectively improve and design their systems in order to survive. This is the actual paradigmcharacterizing the industrial and service sectors. This scenario presents a considerablechallenge to decision makers who will need to decide about how to design and improve amore than ever complex system without compromising the quality of the decision taken.Lean, being a widely applied management philosophy with very powerful principles, itsmethods and tools are static in nature and have some limitations when it comes to the designand improvement of complex and dynamic systems. Some authors have proposed thecombined use of simulation with Lean in order to overcome these limitations. Furthermore,optimization and post-optimization tools coupled to simulation, provide knowledge aboutoptimal or nearly optimal system configurations to choose from. However, even if Leanprinciples, methods and tools, as well as simulation and optimization, pursue the objectiveof supporting organizations regarding system design and improvement, a bilateral approachfor their combination and its benefits have barely been addressed in the literature.Many studies focus only on how specific Lean tools and simulation can be combined, treatingLean purely as a toolbox and not considering how Lean can support the simulation process.The aim of this research is to address this knowledge gap by analyzing the mutualbenefits and presenting a framework for combining Lean, simulation and optimization tobetter support decision makers in system design and improvement where the limitationsof Lean tools and simulation are overcome by their combination. This framework includesa conceptual framework explaining the relationships between the Lean philosophy, methodsand tools with simulation and optimization; the purposes for this combination and stepby step processes to achieve these purposes; the identification of the roles involved in eachprocess; a maturity model providing guidelines on how to implement the framework; existingbarriers for the implementation; and ethical considerations to take into account. Anindustrial handbook has also been written which explains how to deploy the framework.The research has been conducted in three main stages including an analysis of the literatureand the real-world needs, the definition and formulation of the framework, and finally, itsevaluation in real-world projects and with subject matter experts. The main contributionof this research is the reflection provided on the bilateral benefits of the combination, aswell as the defined and evaluated framework, which will support decision makers take qualitydecisions in system design and improvement even in complex scenarios.

De snabba förändringarna på marknaden såsom globalisering, ökat krav på personliga produkteroch tjänster från kunderna, kortare produktlivscykler, tekniska framsteg med exponentielltillväxt samt demografiska förändringar medför ökat krav på att organisationer effektivtförbättrar och utformar sina system. Detta är det nuvarande paradigmet som karaktäriserarindustri- och tjänstesektorerna. Det är ett scenario som utgör en stor utmaningför beslutsfattare, vilka kommer att behöva ta beslut i än mer komplexa system där det blirsvårare att utforma och förbättra system med bibehållen kvalitet. Lean är en allmänt tilllämpadproduktionsfilosofi med kraftfulla principer, med metoder och verktyg som är statiskatill sin natur vilka har begränsningar när det gäller utformning och förbättring avkomplexa och dynamiska system. En del författare har föreslagit den kombinerade användningenav simulering med Lean för att övervinna dessa begränsningar. Dessutom erbjudersimulering kombinerat med optimering och postoptimeringsverktyg genererandet av kunskapom optimala eller nästan optimala systemkonfigurationer. Även om både Lean-principermed dess metoder och verktyg och simulering syftar till att stödja organisationer vidutformning och förbättring av sina system tar litteraturen upp få fördelar med ett kombinerattillvägagångssätt. Flera studier fokuserar endast på hur specifika verktyg inom Leankan kombineras med simulering men behandlar inte hur Lean som filosofi kan stödja simuleringsprocessen.Syftet med denna forskning är att ta itu med denna kunskapsluckagenom att analysera fördelar med kombinationen Lean, simulering och optimering, samtbeskriva hur dess svagheter var för sig kan överbryggas när de kombineras. Resultatet presenterasi ett ramverk med beskrivning av dess genomförande, vilket syftar till att genereraett bättre beslutsstöd vid utformning och förbättring av komplexa och dynamiska system.Ramverket innefattar ett konceptuellt ramverk som förklarar relationerna mellan Lean-filosofin,dess metoder och verktyg, med simulering och optimering; olika ändamål för kombinationenbeskrivs, samt genomgång av steg för steg processer ges för att uppnå dessaändamål; identifiering av de roller som är inblandade i varje process beskrivs; en mognadsmodellpresenteras som ger riktlinjer för hur man implementerar ramverket; befintligahinder för genomförandet och etiska överväganden att ta hänsyn till lyfts också fram. Slutligenhar en industriell handbok skrivits som förklarar hur man ska implementera ramverket.Forskningen har genomförts i tre faser, bland annat en behovsanalys utifrån litteraturenoch verkliga projekt, definitionen av ramverket, och avslutningsvis utvärderas det genomverkliga projekt och med ämnesexperter. Huvudbidraget för denna forskning är reflektionenöver det extra utbytet med kombinationen Lean, simulering och optimering medXIIdess fördelar, vilket bygger på det framtagna ramverket och dess utvärdering. Där ramverkethar för avsikt att stödja beslutsfattare att fatta kvalitetsbeslut vid utformning och identifieringav förbättringar i sina system även i komplexa scenarier.