Background: Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insufficient engagement with well-documented sociotechnical pitfalls. Readiness models offer a systematic way to evaluate project preparedness and to build the capabilities needed for successful artificial intelligence in nursing care (AINC) research, development, and implementation. As of yet, an evidence-based AI readiness assessment prioritizing AINC projects and accounting for their diversity in care settings is missing. Objective: This study aimed to develop a comprehensive artificial intelligence nursing care readiness assessment (AINCRA) to support planning, execution, and evaluation of AINC projects. Methods: In a sequential exploratory multimethods bottom-up approach to maturity model development, key AI readiness dimensions and attributes were identified to develop a pilot readiness assessment. The pilot version was grounded on insights from an expert workshop (n=21) and expert interviews (n=14), an online survey (n=53), a rapid review (n=292), and a nominal group consensus process. A systematic literature review (n=7) further triangulated AI readiness attributes. Finally, a think-aloud interview study and focus group discussions involving experts (n=18) from nursing practice, nursing science, and AI research and development who had conducted AINC projects prior to data collection validated the attributes. Results: The resulting AINCRA encompasses 5 core dimensions: regulatory, processual, technical, social, ethical, and community building requirements and aspects. Including 69 attributes and capabilities of AI nursing care readiness, the core dimensions reflect key areas of action where AINC project stakeholders can influence project outcomes. Clinical partners can assess their organization's maturity level in relation to the implementation of AI. An assessment of each dimension and its attributes across 5 maturity levels allows reflecting on and proactively shaping individual project approaches. Overall, experts regarded AINCRA as a useful instrument for the development, management, and evaluation of AINC projects while emphasizing that established principles of good practice in project and data management should not be neglected when using AINCRA as a project management tool. Conclusions: AINCRA enables practitioners from AI research and development, clinical partners, and nursing and health scientists to plan, evaluate, and enhance AI projects across their lifecycle, thereby supporting effective AI integration in nursing care. While AINCRA was developed within the European and German legal framework for AI in health care settings, respective attributes can be adapted to international requirements.

Although some studies have suggested that homelike care environments can have beneficial effects on people living with dementia (PlwDs) and people living with mild cognitive impairment (PlwMCIs), studies on effects of a non-pharmacological, psychosocial intervention on behavioral and psychological symptoms of dementia (BPSDs) in the setting of shared-housing arrangements (SHAs) are still lacking. In the prospective, multicenter, mixed-methods, cluster-randomized controlled DemWG study, 97 SHAs comprising 341 PlwDs or PlwMCIs were randomly assigned to either the intervention group (IG) or control group (CG). The complex intervention consisted of the education of nursing staff in SHAs (Component A), the education of general practitioners (Component B), and the multicomponent, psychosocial group intervention MAKS-mk+ (Component C). BPSDs (secondary outcome of the DemWG study) were assessed with the Cohen-Mansfield Agitation Inventory-Short Form (CMAI-SF) and the Neuropsychiatric Inventory-Nursing Home Version (NPI-NH) at baseline (t0), 6 months after baseline (t1) and 12 months after baseline (t2). Unadjusted and adjusted generalized estimating equations (GEE) models were computed to investigate possible effects of the complex intervention on the outcome variables at t1 or t2. In the intention-to-treat (ITT) sample, the adjusted GEE models showed that participants in the IG had a significantly lower CMAI-SF score at t1 and at t2 than participants in the CG with a small- to medium-sized effect (RESI = 0.26 [t1] RESI = 0.26 [t2]). Regarding the NPI-NH, the adjusted GEE models showed no significant differences between the IG and CG at t1 and t2. Sensitivity analyses on individuals’ actual average weekly frequency of participating in the MAKS-mk + intervention (“as treated”) showed results comparable to the ITT analysis. The results of the study show that the complex intervention had a positive effect on agitation and aggression in PlwDs or PlwMCIs with a small- to medium-sized effect. Overall, these findings should also contribute to improvement in the caregiving situation and living conditions of relatives and professional caregivers. As the intervention has demonstrated feasibility in the SHA setting, more consideration should be given to implementing it in everyday SHA care. ISRCTN89825211 (Registered prospectively, July 16, 2019).

BackgroundSocial health is increasingly recognized as a key dimension of wellbeing in dementia, yet it remains unclear to what extent available assistive technologies are personalisable, usable, and effective in addressing related unmet needs.ObjectiveThis umbrella review aimed to (1) identify how many and which technologies are personalisable, usable and effective in supporting social health in dementia, and (2) synthesize recommendations from the current literature on how to improve equitable implementation.MethodsAn explorative review of reviews was conducted, including 28 reviews published between 2007 and 2024. The INDUCT/DISTINCT Best Practice Guidance for Human Interaction with Technology in Dementia was also included. Technologies and recommendations were analyzed using a combined frequency-based and thematic approach and categorized according to the three social health domains (fulfilling potential and obligations; managing life with some degree of independence; participation in social activities) and across micro-, meso-, and macrolevels.ResultsOf all technologies discussed, 48% were reported as personalisable and 59% as usable. However, only 23% of personalisable technologies demonstrated effectiveness in at least one randomized controlled trial. Most evidence related to the domain of managing life with some degree of independence, while fewer technologies showed demonstrated effectiveness for fulfilling potential or enhancing social participation. Recommendations primarily addressed implementation strategies, equity considerations, and stakeholder collaboration. Future research priorities included the development of needs-based, personalisable, and diversity-sensitive technologies, improved methodological rigor, and supportive policy and funding structures.ConclusionsWhile half of the technologies are described as adaptable to user needs, preferences or abilities and more than half as usable, robust evidence for their effectiveness in promoting social health remains limited. Clearer operationalisation of personalisation, stronger evaluation designs and improved implementation strategies are needed to ensure that people with dementia can equitably access technologies that promote their social health.

Background and Objectives:Cognitive and functional impairments can both influence and result from deteriorating social health (SH), yet their interplay during aging remains poorly understood. This study investigated the concordance and discordance of trajectories in SH, cognitive, and daily functioning. Research Design and Methods:We analyzed 15-year follow-up data (2001-2015) from 2,848 initially dementia-free older adults in the Swedish National study on Aging and Care in Kungsholmen. Cognition and daily functioning were assessed with the Mini-Mental State Examination and activities of daily living (ADLs)/instrumental ADLs. SH encompassed indices of social participation, connections, and support. Trajectories across these five dimensions were identified using latent growth curve analyses, latent class growth analyses, and growth mixture models. Results:Two cognitive trajectories-relatively preserved (91%) and fast decline (9%)-and two daily functioning trajectories-stable (95%) and declining (5%)-were identified. SH trajectories included stable groups, gradually declining social participation (70%), and low initial social connections (29%). Social support showed stable (95%), declining (2%), and increasing (3%) trajectories. Women were more likely to belong to the initially low-stable social connections group, whereas higher education was linked to favorable trajectories across most dimensions but not social support. Concordance was observed among those with the lowest cognitive, daily functioning, and SH profiles. Notably, increasing social support was linked to low cognition but high daily functioning (odds ratios [OR] = 4.2, 95% CI: 2.3, 7.6). Discussion and Implications:Findings underscore the central role of SH in aging, particularly how dynamic changes in social participation, connections, and support relate to cognitive and functional outcomes.

BACKGROUND:Social health is increasingly recognised as an important factor influencing cognitive ageing and experiences of dementia. Yet definitions and measurements remain inconsistent, and evidence on how social health relates to cognitive outcomes remains limited. AIM AND METHODS:This narrative review presents the conceptual framework and synthesises the empirical findings from the Social Health and Reserve in the Dementia Patient Journey (SHARED) consortium, established to advance understanding of social health across the continuum from preclinical cognitive change to dementia, with a central aim to develop a comprehensive social health framework. SHARED combined conceptual framework development, global qualitative and quantitative studies, coordinated analyses across more than 40 cohorts (∼150,000 participants) and investigations of pathways underlying cognitive resilience. RESULTS:We refined the conceptualisation of social health by integrating individual capacities with features of the social environment. Qualitative interviews further identified novel and often unmeasured dimensions, informing refinement of the framework. Across multiple global cohorts, better social health was associated with higher cognitive performance, slower decline, and reduced risks of mild cognitive impairment and dementia, although associations varied across markers, domains, and contexts. Mechanistic analyses linked social health to markers of brain reserve, including total brain volume and white matter microstructure, and showed that depressive symptoms partially mediated social support-cognition associations. CONCLUSIONS:SHARED delivers a comprehensive, multidimensional framework for social health and provides strong multi-cohort evidence of its importance for cognitive ageing and dementia. Findings highlight the need for improved social health measurement and further work to disentangle its mechanisms and bidirectional links with cognitive ageing and dementia.

Recent advances in dementia research highlight the critical role of the built neighborhood environment in supporting the cognitive and social health of people with dementia (PlwD). This study, part of the Den-HB project, uses Geographic Information Systems (GIS) to analyze urban environments in Bremen, Germany, focusing on neighborhoods with a high proportion of older residents (>65 years). The analysis covers districts, sub-districts, and statistical quarters and examines key indicators such as demography, green and blue spaces, noise pollution, accident hotspots, public transport accessibility, daily shopping, meeting places, and health services. Preliminary results show that multi-level GIS mapping provides crucial insights into the spatial distribution of dementia-friendly factors. For example, while an expanded public transport network can improve mobility for PlwD, it may also contribute to higher noise levels and increased accident risks. GIS enables the visualization of these trade-offs by mapping areas where benefits and challenges coexist. Incorporating thematic fields based on existing evidence allows for systematic evaluation of urban environments, identifying areas with specific needs or exemplary features. This approach highlights zones requiring targeted intervention or serving as models for dementia-friendly planning. By integrating findings from different domains, this research advances understanding of how geospatial technologies can inform evidence-based strategies for inclusive urban development. While further validation is ongoing, these initial findings provide a solid foundation for improving the dementia-friendliness of urban neighborhoods, ultimately supporting the establishment of communities tailored to the unique needs of people living with dementia.

People living with dementia (PlwD) have a 1.4 times higher risk of hospitalization than people living without dementia. Hospital admissions lead to negative consequences for PlwD and people living with mild cognitive impairment (PlwMCI). Housing models such as shared-housing arrangements (SHAs), which are predominantly used by PlwD, enable care-dependent people to experience daily life as ordinary as possible. However, studies are needed to show how complex non-pharmacological interventions affect hospital admissions, especially in the SHAs setting. The longitudinal, multicenter, cluster-randomized, controlled, and prospective mixed methods study from April 1, 2019, to December 31, 2022, was part of the German DemWG study and included a waitlist control group design. The multicomponent complex intervention consisted of (a) education of nursing staff in the SHAs—at the beginning of the study, (b) digital education of general practitioners—at the beginning of the study, and (c) the multimodal, psychosocial group intervention MAKS-mk + —structured application of MAKS-mk + between t0 (baseline) and t1 (after 6 months). Longitudinal data were collected at three survey times t0-t2 (t2 at another 6 months follow-up). The primary outcome parameter—hospital admission—was assessed using the nursing documentation. Poisson-models with hierarchical random effects were used for statistical analysis. Nationwide, 97 SHAs with 341 residents participated at t0. Within the longitudinal observation period (12 months, t0-t2), data from 236 participants at t1 and 168 participants at t2 with mild cognitive impairment or mild to moderate dementia were evaluated. In the intention-to-treat sample, the adjusted Poisson-model showed that participants in the intervention group (IG, n = 201) had a significantly lower number of hospital admissions at t1 than participants in the control group (CG, n = 140) (p-value = 0.048; CI = 0.22; 0.99). Beyond t1—“open phase” of the study, no further statistically significant long-term effects of the IG could be identified (p-value ≤ 0.498; CI = 0.25; 1.98). The complex intervention significantly reduced the number of hospital admissions for PlwD and PlwMCI in the “structured phase” of DemWG. This leads to significant improvements in the nursing care and living situation for PlwD and PlwMCI. Since the intervention has been proven to have positive effects and can be easily integrated into SHAs, regular and nationwide integration into everyday care should be given greater consideration. ISRCTN89825211 (Registered prospectively, 16 July 2019).

Integrating Artificial Intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insufficient engagement with well-documented socio-technical pitfalls. Readiness models offer a systematic way to evaluate project preparedness and to build the capabilities needed for successful AI in nursing care (AINC) research, development and implementation. A novel AI Nursing Care Readiness Assessment (AINCRA) tool was designed to support planning, execution, and evaluation of AINC projects. A sequential exploratory mixed-methods bottom-up approach to maturity model development identified key AI readiness dimensions and attributes. The initial AINCRA version is grounded on insights from expert workshops, an online survey, and a nominal group consensus process. A systematic literature review further triangulated AI readiness attributes. Lastly, a think aloud interview study and focus group discussions involving experts from diverse disciplines validated the attributes. The resulting AINCRA encompasses five core dimensions: regulatory, processual, technical, social and ethical, and community building requirements and aspects. Across five maturity levels, 69 AINC readiness attributes enable practitioners from AI research and development, clinical partners and nursing and health scientists to plan, evaluate and enhance AI projects across their lifecycle, thereby supporting effective AI integration in nursing care. not applicable

In dementia care, access to effective psychosocial interventions is often addressed by evidence-based guidelines for care providers. However, it is unclear if current guidelines consider personal characteristics that may impact intervention effectiveness. This study investigates if, and within what framing, dementia care guidelines in Europe address what is effective and for whom. A review of 47 guidelines from 12 European countries was conducted. Content analysis focused on (i) if guidelines recommended specific psychosocial interventions, and how guidelines referred to (ii) social health, (iii) the intersection of social positioning, and (iv) inequities in care or outcomes. Thirty-five guidelines (74%) recommended specific psychosocial interventions. Around half referenced aspects of social health and of intersectionality. Thirteen guidelines (28%) referenced inequities. Social health was not explicitly recognised as a mechanism of psychosocial interventions. Only age and comorbidity were consistently considered to impact interventions’ effectiveness. Inequities were acknowledged to arise from within-country regional variations and individual economic status, but were not linked to (intersectional) individual societal positions such as sex and/or gender, sexuality, and/or religion. The results between European countries were heterogeneous. Current guidelines offer little insight into what works for whom. Policymakers and guideline developers should work with researchers, generating and translating evidence into policy.

Abstract Background Nursing home residents frequently utilize medical care, but there lacks a complete picture of their acute medical care utilization. We quantified hospitalizations, emergency medical care utilization, and contacts with the regional on-call medical services among nursing home residents, and investigated individual characteristics that may be associated with the utilization of these medical care types. Methods Cross-sectional data from the “Needs-based provision of medical care to nursing home residents” (MVP-STAT) study were analyzed, which were collected in 44 German nursing homes from 442 residents in 2018/2019. Proportions of residents with at least one hospitalization, emergency medical care utilization (via the nationwide phone number 112), and contact with an on-call medical service (nationwide via 116117) over the previous 12 months were determined. Associations between individual characteristics and the utilization of the three medical care types were examined using multivariable logistic regressions. Results Of the analyzed residents, 45.8% were hospitalized, 23.2% utilized emergency medical care, and 12.1% had contact with an on-call medical service at least once in the previous 12 months. Hospitalizations were positively associated with male vs. female sex (adjusted odds ratio 1.99 [95% confidence interval 1.22–3.26]), age group 85 + vs. 60–74 years (2.15 [1.12–4.13]), long-term care grades 4/5 vs. 1/2 (2.78 [1.48–5.21]), 6 + vs. 0–1 Elixhauser diseases (2.58 [1.01–6.62]), and the risk or presence of vs. no malnutrition (3.10 [1.52–6.35] and 2.01 [1.26–3.21]); and not associated with years of residence in the respective nursing home. Emergency medical care utilization was positively associated with age group 85 + vs. 60–74 years (2.58 [1.14–5.84]) and long-term care grades 3 and 4/5 vs. 1/2 (2.65 [1.07–6.55], 6.31 [2.60–15.35]); negatively associated with 5 + vs. 1- < 3 years of residence (0.46 [0.24–0.86]); and not associated with sex, the number of Elixhauser diseases, and nutritional status. No associations were found with on-call medical services. Conclusions Hospitalizations and emergency medical care utilization were more frequent among nursing home residents than contacts with on-call medical services. Future studies should investigate whether the frequent hospitalizations and emergency medical care utilization among nursing home residents are justified, or whether they can be reduced by strengthening medical care provision by on-call doctors and other professionals. Trial registration DRKS00012383 [2017/12/06].

Recent studies underscore the importance of the neighbourhood-built environment (NBE) for the cognitive and social health of older people with mild cognitive impairment (MCI) or people living with dementia (PlwD). While previous overview reviews have provided valuable insights, they often focus narrowly on either objective environmental features or subjective experiences and typically lack an integrated perspective. This umbrella review addresses this gap by systematically examining how specific NBE aspects (a) influence the cognitive and social health of older people with MCI or PlwD, and (b) subjective experiences by PlwD and their caregivers. By combining these perspectives, the review aims to support the development of dementia-friendly neighbourhood design and planning. To answer these questions, an umbrella review was performed. Scopus, MEDLINE (Pubmed), APA PsychINFO (Ebesco), CINAHL Complete (Ebesco), Cochrane Library, and Epistemonikos databases were used for the systematic literature research. We included peer-reviewed reviews or meta-analyses (quantitative, qualitative, or mixed-method studies) in German or English. Ten reviews with 364 primary studies were identified. Reviews predominantly included quantitative studies, but also qualitative studies. The primary focus of the reviews was on the positive and negative influences of the NBE on MCI and/or dementia. Subjective experiences on social health targets were also addressed, but received less attention. The results of the reviews, although heterogeneous, highlight potential relationships between various NBE aspects and the cognitive and social health of older people with MCI or PlwD. Clear associations were identified for certain NBE features—such as green spaces and transportation infrastructure—which demonstrate positive influences on both cognitive functioning and social participation. These findings emphasise the importance of considering both objective environmental characteristics and the subjective perceptions of PlwD and their caregivers when designing dementia-friendly neighbourhoods. By doing so, this umbrella review contributes evidence-based guidance to support autonomy and independent living for people with MCI or dementia. Further research is needed to explore the specific influence of individual NBE aspects on social health and the lived experiences of PlwD and their caregivers.

BACKGROUND:Previous studies have identified inequities in the diagnostic and therapeutic procedures used with community-dwelling people living with dementia (PlwDs) or people living with mild cognitive impairment (PlwMCIs) depending on the urban vs. rural location of their residence. Whether those differences in health care and health services utilization still exist for people residing in shared-housing arrangements (SHAs) remains unclear at this point. METHODS:In a prospective, multicenter, mixed-methods, cluster-randomized controlled trial, the "DemWG study," 341 PlwDs or PlwMCIs living in a total of 97 SHAs across Germany were recruited. 31 of the participating SHAs were rural (133 participants), 66 were urban (208 participants). As a secondary analysis we evaluated health care data (e.g. vaccinations, medication), utilization of inpatient/outpatient medical services, non-pharmacological therapies according to the German Remedies Directive, provision of health and medical aids and structural data of the SHAs. Variables were assessed at baseline by trained staff from the SHAs using validated instruments (e.g. FIMA - questionnaire for health-related resource use in an elderly population). Descriptive and inferential statistical methods were applied. P-values were corrected with the Benjamini-Hochberg procedure. RESULTS:The majority of the assessed health care data did not show significant differences between urban and rural SHA inhabitants. After the p-values were corrected, only two variables remained different: inhabitants of rural SHAs were prescribed a significantly larger number of total drugs, while urban inhabitants had significantly more appointments with neurologists/psychiatrists in the last 6 months. There were no significant differences in the use of all other type of inpatient/outpatient services, non-pharmacological therapies, use of health and medical aids. Also, the structural data of the SHAs like staffing did not significantly differ between urban and rural place of living. DISCUSSION:While it seems that most inequities in the care of PlwDs/PlwMCIs living in SHAs between rural and urban areas have been overcome, there is still the one crucial difference in this non-representative sample of SHAs: the contact with neurologic/psychiatric specialists who offer elaborated diagnostic procedures is less frequent in rural areas. TRIAL REGISTRATION:ISRCTN89825211 (Registered prospectively, 16 July 2019).

Nursing homes are not only places where people in need of care are cared for, they are also increasingly seen as places of partnership between academia and practice and places of knowledge transfer. They offer practical approaches to skills development and lifelong learning for staff, promote research capacity and improve outcomes for residents. This requires continuous organizational development, the expansion of digitalization potential, the training of specialized geriatric staff and the integration of evidence-based, person-centred care into the operation of nursing homes. Academic-Practice Partnership models are therefore gaining increasingly attention as a feasible approach to achieve these goals. This symposium will describe interdisciplinary collaboration between scientists, care providers and educators in nursing homes in four countries: United States, Germany, the Netherlands, and the Austria. Experiences of stakeholders, research activities and the evaluation and implementation of digital services will be discussed. The first presentation will presentation will provide an overview of the Dutch Living Lab in Long-term care. The second presentation will describe interdisciplinary staff’s experiences and the impact of Age-Friendly Care 4M Rounding with older adults living in long-term care. The third presentation will highlight the collaborative development and implementation of a practice-oriented, evidence-based toolkit for non-pharmacological pain management within the nursing home environment of the Austrian living lab. The final presentation will describe the TCALL project in Germany, with a focus on implementing innovative digital tools into daily practice. A discussion will follow addressing future directions and challenges of academic-practice partnership in nursing homes including policy implications.

BACKGROUND:Urinary incontinence affects 5% to 35% of the older adult population. Untreated urinary incontinence is associated with reduced quality of life, amongst others. Pelvic floor muscle training is the first-line treatment. Existing evidence on the proportion of physiotherapy care remains limited, particularly regarding men with urinary incontinence, and insufficiently accounts for care situation- or age-specific disparities. This study investigated the proportion of physiotherapy care, differentiated by age, sex, care situation, informal provider networks, and temporal trends, to address these evidence gaps. METHOD:We analysed health insurance fund claims data covering a period of 9 years (2008-2016), from up to 6,433,070 individuals aged 65+, and applied a network approach to identify patient sharing networks. We calculated the proportion of physiotherapy care on a quarterly basis. RESULTS:The proportion of physiotherapy care remained relatively stable over time. In the first quarter of 2016, it was 10.5% for people with incident urinary incontinence in total, 7.9% for those without care, 11.9% for people with home care, and 14.0% for nursing home residents. The lowest proportion of physiotherapy care (3.5%) was found among men with incident urinary incontinence in the 85 to 89 age group receiving no care, and the highest proportion (19.3%) among women with incident urinary incontinence in the age group 70 to 74 years living in a nursing home. The variation in the proportion of physiotherapy care between patient sharing networks was the highest for women and men in nursing homes (SD 9.7% and 9.2%, respectively). CONCLUSIONS:These findings indicate a systematic underuse of physiotherapy services for both sexes across all age groups and care situations. Older men without care needs are particularly at risk for underuse.

Dementia is one of the major age-related diseases world-wide and challenges not only people living with dementia and their caregivers, but also societies and health care systems as a whole. To better meet the needs of people living with dementia, innovative care environments are being developed worldwide, as part of the wider community. Aiming to strengthen independence and slow down the cognitive decline, efforts concentrate on continuously engaging people living with dementia in activities of daily life, despite a progression of the disease. This international symposium will provide four presentations on innovative dementia care environments in four different countries, which stimulate and support autonomy of older people living with dementia in an active daily life. It examines diverse environmental elements of the care environment, including organizational, social and physical aspects, and what their impact is on residents and their caregivers. The first presentation explores Green Care Farms in the Netherlands, focusing on the impact of organizational environment, in particular culture and staff’s task integration, on residents’ autonomy. The second presenter discusses results from two Dementia Village models in Canada, exploring the environmental effect on residents’ quality of life and staff’s care practices. The third presentation examines the impact of the neighborhood-built environment on social health of older residents living with dementia in Germany, using Geographical Information Systen (GIS) analyses. Finally, the last presenter describes the effects of adaptation in the physical environment, i.e. smart, ambient bright light on residents with dementia living in nursing homes in the United States.

Ensuring high-quality care is emerging as a key challenge for the future in Germany, particularly in light of demographic change and a shrinking workforce. Improving working conditions in long-term care through digital innovations seems to be a promising approach to improve quality of care and quality of work. The Transfer Cluster of Academic Teaching Nursing Homes in long-term care in Germany (TCALL) enables the implementation of digital innovations in regular operations and offers a direct transfer from academia to healthcare practice and back from healthcare practice to research and education. TCALL thus constitutes a conceptual space for innovative transfer activities and simultaneously provides a permanent physical environment for recursive innovation development, testing and implementation. Such transfer and innovation structures as regular and obligatory processes are currently lacking in Germany. For the first time, TCALL offers structures that directly contribute to the rapid and process-oriented development of the state of the art through innovative insights and products. We present the concept of TCALL, which has been implemented so far in three nursing homes in Bremen, and discuss examples of the implementation of digital solutions (e.g., an AI-based management for the prevention and documentation of falls). We identify the facilitators and barriers to implementing digital technologies in terms of structural and process-related factors, explore the implications of innovation implementation for personnel and organizational development, and share lessons learned from participatory approaches.

Zusammenfassung Digitale Pflegetechnologien gewinnen in der Langzeitpflege zunehmend an Bedeutung. Sie umfassen alle Technologien, die mittels Vernetzung und/oder Sensorik Prozesse und/oder Produkte verändern, und schließen künstliche Intelligenz, also Verfahren, Methoden und Algorithmen, um mittels Daten zu lernen und darauf aufbauend zielorientierte Handlungen zu ermöglichen, ein. Ihre Anwendung reicht von der Förderung professioneller Zusammenarbeit über Steuerung und Verwaltung, Wissenserwerb und -weitergabe, Interaktion und Beziehung bis zur körpernahen Pflege. Digitale Pflegetechnologien haben das Potenzial, gleichzeitig die Qualität der Pflege zu erhöhen und die Arbeitsbedingungen in der Pflege zu verbessern. Allerdings stehen dem Hemmnisse auf verschiedenen Ebenen entgegen: Die Entwicklung dieser Technologien wird häufig von den technischen Möglichkeiten getrieben, sodass Produkte entstehen, die im Pflegealltag keinen konkreten Nutzen entfalten. Bei der Implementation wird nur die Bedienung geschult; es erfolgt aber keine Organisationsentwicklung zur systematischen Integration der Technologien in den Arbeitsalltag. Zudem fehlen hochwertige Evaluationen, die den tatsächlichen Nutzen im Arbeitsalltag abbilden, um so potenzielle Anwender:innen für die Technologie zu gewinnen. Schließlich ist die nachhaltige Finanzierung, insbesondere der Unterhaltung dieser Technologien, nicht gesichert. Eine gelingende Digitalisierung in der Pflege setzt daher voraus, dass Technikentwickler:innen und -anwender:innen ebenso wie Politik und Wissenschaft gemeinsam diese Hemmnisse überwinden. Das impliziert, dass Pflegende von Anfang an in den Entwicklungsprozess einbezogen sind, aber auch dass Orte geschaffen werden, in denen die Wirkung digitaler Pflegetechnologien im tatsächlichen Versorgungsgeschehen evaluiert werden kann.