Aplicaciones psicosociales de la tecnología para la capacitación en salud y bienestar de adultos mayores con demencia y deterioro cognitivo leve y sus cuidadores en zonas rurales

Tesis por compendio de publicaciones.[EN]Introduction: The transition to an ageing population has brought several challenges to societies and healthcare systems around the world. The need for new healthcare approaches and interventions to adjust to the new situation is one of the most relevant issues worldwide. This project particularly targets three of these challenges: the complexity of older adult care, the increase of people living with dementia and their caregivers, and the poor accessibility of rural populations to access healthcare services to face these challenges. Aims: To develop a proof of concept of a technological platform integrating several innovative digital tools for health and wellness coaching of older adults with dementia and cognitive impairment and their carers, and to study the effects of utilisation of the platform on physical health, mental and emotional wellbeing, activities of daily living, social and cognitive functioning and professional care use. To involve older adults with dementia and their carers in the design and development of the platform, assessing their satisfaction, the impact of the system in realistic settings, acceptability and usability, to enable them to manage the system autonomously in daily life. Methodologies: Two systematic reviews were conducted in July 2021 and April 2023 in PubMed, CINAHL, and Web of Science. A qualitative appraisal/risk of bias was performed for the studies included. Three qualitative studies were conducted, implementing online and face-to-face workshops, semi-structured interviews, focus groups, and co-design and co-production processes with Patient and Public Involvement (PPI). Thematic analysis was the chosen approach for the analysis of the results. A mixed-methods usability and user experience study and a pilot study of an online training and support programme for caregivers of people living with dementia are being carried out, implementing semi-structured interviews and questionnaires targeting usability, dementia knowledge and caregiver burden. Results: A series of steps necessary to create the foundations of a technological platform were identified: a) the interRAI LTFC and the interRAI HC were recommended as the CGAs to be used for the assessment and monitoring of potential users in long-term care facilities and home care, respectively; b) the barriers for the usability and implementation of DHTs to assist and to help to reach the full potential of CGAs are described, as well as a series of recommendations to improve its usability and implementation by healthcare professionals and clinical settings; c) a framework to study the pros and cons of developing digital patient and public involvement and suggestions to improve the implementation of e-PPI were developed and identified; d) the facilitators and barriers to implementing the socio-community intervention of the Meeting Centre Support Programme were identified and several recommendations were described to overcome the limitations for a successful implementation; and e) as an attempt to offer a support service alternative for caregivers of PLwD in remote rural areas, the cultural adaptation of the iSupport training and support programme for carers of PLwD was developed, and its usability and user-experience, and impact on dementia knowledge and caregiver burden are under study. Conclusions: This project described a series of steps necessary to create the foundations of a technological platform for health and wellness coaching of older adults with dementia and cognitive impairment and their carers. By embedding the findings in this project and including novel technologies such as AI, robotics, wearable technologies, and monitoring devices, the idea of the technological platform could be feasible. Further projects could implement these initiatives to generate an impact on facing the current challenges of the ageing population. [ES]Introducción: La transición hacia una población que envejece ha planteado varios retos a las sociedades y los sistemas sanitarios de todo el mundo. La necesidad de nuevos enfoques e intervenciones sanitarias para adaptarse a la nueva situación es una de las cuestiones más relevantes en todo el mundo. Este proyecto se centra especialmente en tres de estos retos: la complejidad de la atención a los adultos mayores, el aumento del número de personas que viven con demencia y de sus cuidadores, y la escasa accesibilidad de las poblaciones rurales a los servicios sanitarios para hacer frente a estos retos. Objetivos: Desarrollar una prueba de concepto de una plataforma tecnológica que integre varias herramientas digitales innovadoras para la capacitación en salud y bienestar de adultos mayores con demencia y deterioro cognitivo y sus cuidadores, y estudiar los efectos de la utilización de la plataforma en la salud física, el bienestar mental y emocional, las actividades de la vida diaria, el funcionamiento social y cognitivo y el uso para los cuidados profesionales. Involucrar a los adultos mayores con demencia y a sus cuidadores en el diseño y desarrollo de la plataforma, evaluando su satisfacción, el impacto del sistema en entornos realistas, su aceptabilidad y usabilidad, para permitirles manejar el sistema de forma autónoma en la vida diaria. Métodos: Se realizaron dos revisiones sistemáticas en julio de 2021 y abril de 2023 en PubMed, CINAHL y Web of Science. Se realizó una valoración cualitativa/riesgo de sesgo de los estudios incluidos. Se realizaron tres estudios cualitativos, implementando talleres online y presenciales, entrevistas semiestructuradas, grupos focales y procesos de codiseño y coproducción con Participación de Pacientes y Público (PPI). El análisis temático fue el enfoque elegido para el análisis de los resultados. Se está llevando a cabo un estudio de usabilidad y experiencia de usuario con métodos mixtos y un estudio piloto de un programa en línea para la capacitación y formación de cuidadores de personas que viven con demencia, en los que se aplicarán entrevistas semiestructuradas y cuestionarios sobre usabilidad, conocimiento de la demencia y sobrecarga de los cuidadores. Resultados: Se identificaron una serie de pasos necesarios para crear las bases de una plataforma tecnológica: a) se recomendaron el interRAI LTFC y el interRAI HC como las Evaluaciones Geriátricas Integrales (EGI) que se utilizarán para la evaluación y el seguimiento de los usuarios potenciales en los centros de larga estancia y en la atención domiciliaria, respectivamente; b) se describen las barreras para la usabilidad y la implementación de las Tecnologías de Salud Digital (TSD) para asistir y ayudar a alcanzar todo el potencial de las EGI, así como una serie de recomendaciones para mejorar su usabilidad e implementación por parte de los profesionales sanitarios y los entornos clínicos; c) se desarrolló e identificó un marco para estudiar los pros y los contras del desarrollo de la participación digital de pacientes y público (e-PPI, por sus siglas en inglés) y sugerencias para mejorar la implementación de e-PPI; d) se identificaron los factores que facilitan y dificultan la aplicación de la intervención sociocomunitaria del Programa de Atención de Centros de Encuentro (MCSP, por sus siglas en inglés) y se describieron varias recomendaciones para superar las limitaciones y lograr una aplicación satisfactoria; y e) como intento de ofrecer una alternativa de servicio de apoyo a los cuidadores de personas que viven con demencia en zonas rurales remotas, se desarrolló la adaptación cultural del programa de formación y apoyo iSupport para cuidadores de personas que viven con demencia, y se está estudiando su usabilidad y experiencia de usuario, así como su impacto en los conocimientos sobre la demencia y la sobrecarga en los cuidadores. Conclusión: Este proyecto describe una serie de pasos necesarios para crear los cimientos de una plataforma tecnológica para la capacitación en salud y bienestar de los adultos mayores con demencia y deterioro cognitivo y sus cuidadores. La idea de la plataforma tecnológica podría ser factible si se incorporan los resultados de este proyecto y se incluyen tecnologías novedosas como la inteligencia artificial, la robótica, las tecnologías ponibles y los dispositivos de monitorización. Otros proyectos podrían poner en práctica estas iniciativas para generar un impacto a la hora de afrontar los retos actuales del envejecimiento de la población

World Alzheimer report 2016: improving healthcare for people living with dementia: coverage, quality and costs now and in the future

The World Alzheimer Report 2016, Improving healthcare for people living with dementia: Coverage, quality and costs now and in the future, reviews research evidence on the elements of healthcare for people with dementia, and, using economic modelling, suggests how it should be improved and made more efficient. The report argues that current dementia healthcare services are over-specialised, and that a rebalancing is required with a more prominent role for primary and community care. This would increase capacity, limit the increased costs associated with scaling up coverage of care, and, coupled with the introduction of care pathways and case management, improve the coordination and integration of care. Modelling of the costs of care pathways was carried out in Canada, China, Indonesia, Mexico, South Africa, South Korea and Switzerland, to estimate the costs of dementia healthcare under different assumptions regarding delivery systems. The report was researched and authored by Prof Martin Prince, Ms Adelina Comas-Herrera, Prof Martin Knapp, Dr Maëlenn Guerchet and Ms Maria Karagiannidou from The Global Observatory for Ageing and Dementia Care, King’s College London and the Personal Social Services Research Unit (PSSRU), London School of Economics and Political Science

Comprehensive Geriatric Assessment in hospital and hospital-at-home settings: a mixed-methods study

Background: The Comprehensive Geriatric Assessment (CGA) is a multidisciplinary process that determines a frail older person’s medical, functional, psychological and social capability to ensure that they have a co-ordinated plan for treatment and follow-up. Objectives: To improve our understanding of the effectiveness, cost-effectiveness and implementation of the CGA across hospital and hospital-at-home settings. Methods: We used a variety of methods. We updated a Cochrane review of randomised trials of the CGA in hospital for older people aged ≥ 65 years, conducted a national survey of community CGA, analysed data from three health boards using propensity score matching (PSM) and regression analysis, conducted a qualitative study and used a modified Delphi method. Results: We included 29 trials recruiting 13,766 participants in the Cochrane review of the CGA. Older people admitted to hospital who receive the CGA are more likely to be living at home at 3–12 months’ follow-up [relative risk (RR) 1.06, 95% confidence interval (CI) 1.01 to 1.10] (high certainty). The probability that the CGA would be cost-effective at a £20,000 ceiling ratio for quality-adjusted life-years (QALYs), life-years (LYs) and LYs living at home was 0.50, 0.89, and 0.47, respectively (low-certainty evidence). After PSM and regression analysis comparing CGA hospital with CGA hospital at home, we found that the health-care cost (from admission to 6 months after discharge) in site 1 was lower in hospital at home (ratio of means 0.82, 95% CI 0.76 to 0.89), in site 2 there was little difference (ratio of means 1.00, 95% CI 0.92 to 1.09) and in site 3 it was higher (ratio of means 1.15, 95% CI 0.99 to 1.33). Six months after discharge (excluding the index admission), the ratio of means cost in site 1 was 1.27 (95% CI 1.14 to 1.41), in site 2 was 1.09 (95% CI 0.95 to 1.24) and in site 3 was 1.70 (95% CI 1.40 to 2.07). At 6 months’ follow-up (excluding the index admission), there may be an increased risk of mortality (adjusted) in the three hospital-at-home cohorts (site 1: RR 1.09, 95% CI 1.00 to 1.19; site 2: RR 1.29, 95% CI 1.15 to 1.44; site 3: RR 1.27, 95% CI 1.06 to 1.54). The qualitative research indicates the importance of relational aspects of health care, incorporating caregivers’ knowledge in care planning, and a lack of clarity about the end of an episode of health care. Core components that should be included in CGA focus on functional, physical and mental well-being, medication review and a caregiver’s ability to care. Limitations: The risk of residual confounding limits the certainty of the findings from the PSM analysis; a second major limitation is that the research plan did not include an investigation of social care or primary care. Conclusions: The CGA is an effective way to organise health care for older people in hospital and may lead to a small increase in costs. There may be an increase in cost and the risk of mortality in the population who received the CGA hospital at home compared with those who received the CGA in hospital; randomised evidence is required to confirm or refute this. Caregiver involvement in the CGA process could be strengthened. Funding: The National Institute for Health Research Health Services and Delivery Research programme

Building a tiered rehabilitation system: the case of Yunnan Province

Research purposes: The hierarchical rehabilitation system model of Yunnan Province is built to provide a reference for the establishment of a standardized three-level rehabilitation system so as to meet the patient demands for different functional rehabilitation at different stages during the whole treatment. Research methods: 1. The General System Theory model is adopted as a guidance for the organizational structure construction of the hierarchical rehabilitation system model in rehabilitation centers, rehabilitation sub-centers, and rehabilitation stations in Yunnan Province. Standardized hierarchical rehabilitation hardware construction for these rehabilitation institutions of different levels helps form an exemplary structural model of a three-level standardized rehabilitation system. 2. The Learning Cycle Theory model is adopted as a guidance for the unified standardized training for patient rehabilitation management in the exemplary rehabilitation institutions of the three-level system. The researchers regularly guide, supervise, and summarize the standard implementation situations of patient rehabilitation management in these institutions and assess the operational quality and management efficiency of the hierarchical rehabilitation system model in Yunnan Province, finally forming the exemplary and standardized three-level rehabilitation system model. 3. The researchers analyze the operating parameters of the medical institutions at all levels in the three-level standardization rehabilitation system and evaluate the structural process and operational efficiency of the three-level standardized rehabilitation system model based on the analysis results.O modelo do sistema de reabilitação hierárquico da Província Yunnanfoi concebido comoumreferencial para a implementação de um sistema de reabilitação estruturado em três níveis, de modo a responder às necessidades dos doentes nas diferentes fases da sua reabilitação funcional. Como guias metodológicos foram adotadosa Teoria Geral dos Sistemas e o LearningCycleTheory, entre outros contributos teóricos considerados relevantes. Os investigadores participantes supervisionaram a operacionalização do sistema e avaliaram as instituições de cada um dos três níveis, quanto àestrutura, ao processo e à eficiência operacional. Quanto aos resultados houve uma clara perceção dos ganhos obtidos em várias dimensões. Pelo lado das instituições governamentais, pela redução dos recursos utilizados e pela maior mobilização e empenhamento dos profissionais e por parte dos doentes, pela maior rapidez de resposta às suas necessidades e a uma redução do tempo da sua reintegração no mercado de trabalho. A reputação deste sistema implicoutambém ganhos significativos nas receitas obtidas, que aumentaram em mais de 10% em dois anos, tendo mesmo algumas serviços atingido incrementos de 89,6%. A mudança de cultura organizacional das instituições envolvidas,no sentido da inovação e da proatividadeé também um facto a reter com particular relevância. Como conclusão, poderemos referir que este modelorespondeu as expectativas de todos os stakeholders, desde o governo, aos doentes e ao público em geral, bem assim como às das instituições de saúde implicadas e os seus profissionais. Deste modo, este modelo pode fornecer contributos sustentados de aprendizagem para a conceção e implementação de sistemas de reabilitação regional de um modo rápido e estruturado

CLARA: Building a Socially Assistive Robot to Interact with Elderly People

Although the global population is aging, the proportion of potential caregivers is not keeping pace. It is necessary for society to adapt to this demographic change, and new technologies are a powerful resource for achieving this. New tools and devices can help to ease independent living and alleviate the workload of caregivers. Among them, socially assistive robots (SARs), which assist people with social interactions, are an interesting tool for caregivers thanks to their proactivity, autonomy, interaction capabilities, and adaptability. This article describes the different design and implementation phases of a SAR, the CLARA robot, both from a physical and software point of view, from 2016 to 2022. During this period, the design methodology evolved from traditional approaches based on technical feasibility to user-centered co-creative processes. The cognitive architecture of the robot, CORTEX, keeps its core idea of using an inner representation of the world to enable inter-procedural dialogue between perceptual, reactive, and deliberative modules. However, CORTEX also evolved by incorporating components that use non-functional properties to maximize efficiency through adaptability. The robot has been employed in several projects for different uses in hospitals and retirement homes. This paper describes the main outcomes of the functional and user experience evaluations of these experiments.This work has been partially funded by the EU ECHORD++ project (FP7-ICT-601116), the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 825003 (DIH-HERO SUSTAIN), the RoQME and MiRON Integrated Technical Projects funded, in turn, by the EU RobMoSys project (H20202-732410), the project RTI2018-099522-B-C41, funded by the Gobierno de España and FEDER funds, the AT17-5509-UMA and UMA18-FEDERJA-074 projects funded by the Junta de Andalucía, and the ARMORI (CEIATECH-10) and B1-2021_26 projects funded by the University of Málaga. Partial funding for open access charge: Universidad de Málaga

Application of machine learning approaches in predicting clinical outcomes in older adults – a systematic review and meta-analysis

BACKGROUND: Machine learning-based prediction models have the potential to have a considerable positive impact on geriatric care.DESIGN: Systematic review and meta-analyses.PARTICIPANTS: Older adults (≥ 65 years) in any setting.INTERVENTION: Machine learning models for predicting clinical outcomes in older adults were evaluated. A random-effects meta-analysis was conducted in two grouped cohorts, where the predictive models were compared based on their performance in predicting mortality i) under and including 6 months ii) over 6 months.OUTCOME MEASURES: Studies were grouped into two groups by the clinical outcome, and the models were compared based on the area under the receiver operating characteristic curve metric.RESULTS: Thirty-seven studies that satisfied the systematic review criteria were appraised, and eight studies predicting a mortality outcome were included in the meta-analyses. We could only pool studies by mortality as there were inconsistent definitions and sparse data to pool studies for other clinical outcomes. The area under the receiver operating characteristic curve from the meta-analysis yielded a summary estimate of 0.80 (95% CI: 0.76 - 0.84) for mortality within 6 months and 0.81 (95% CI: 0.76 - 0.86) for mortality over 6 months, signifying good discriminatory power.CONCLUSION: The meta-analysis indicates that machine learning models display good discriminatory power in predicting mortality. However, more large-scale validation studies are necessary. As electronic healthcare databases grow larger and more comprehensive, the available computational power increases and machine learning models become more sophisticated; there should be an effort to integrate these models into a larger research setting to predict various clinical outcomes.</p

Application of machine learning approaches in predicting clinical outcomes in older adults – a systematic review and meta-analysis

BACKGROUND: Machine learning-based prediction models have the potential to have a considerable positive impact on geriatric care.DESIGN: Systematic review and meta-analyses.PARTICIPANTS: Older adults (≥ 65 years) in any setting.INTERVENTION: Machine learning models for predicting clinical outcomes in older adults were evaluated. A random-effects meta-analysis was conducted in two grouped cohorts, where the predictive models were compared based on their performance in predicting mortality i) under and including 6 months ii) over 6 months.OUTCOME MEASURES: Studies were grouped into two groups by the clinical outcome, and the models were compared based on the area under the receiver operating characteristic curve metric.RESULTS: Thirty-seven studies that satisfied the systematic review criteria were appraised, and eight studies predicting a mortality outcome were included in the meta-analyses. We could only pool studies by mortality as there were inconsistent definitions and sparse data to pool studies for other clinical outcomes. The area under the receiver operating characteristic curve from the meta-analysis yielded a summary estimate of 0.80 (95% CI: 0.76 - 0.84) for mortality within 6 months and 0.81 (95% CI: 0.76 - 0.86) for mortality over 6 months, signifying good discriminatory power.CONCLUSION: The meta-analysis indicates that machine learning models display good discriminatory power in predicting mortality. However, more large-scale validation studies are necessary. As electronic healthcare databases grow larger and more comprehensive, the available computational power increases and machine learning models become more sophisticated; there should be an effort to integrate these models into a larger research setting to predict various clinical outcomes.</p