Risk stratification tools to predict future hospital admissions in elderly people. Application, development and implementation in the Valencian Healthcare System

La presente tesis se enmarca en un escenario caracterizado por una población que cada vez vive más años y en la que el porcentaje de personas mayores es progresivamente más alto. De forma adicional, el aumento de la prevalencia de las enfermedades crónicas (EC) supone un importante impacto sobre los sistemas sanitarios dado que éstas son la principal causa de muerte a nivel mundial y, en muchos casos, están asociadas a situaciones de dependencia y a la necesidad de cuidados de larga duración. Con el objetivo de llevar a cabo un abordaje más efectivo de las enfermedades asociadas al envejecimiento y a la cronicidad los sistemas asistenciales deberían sufrir un cambio de paradigma en el que se sitúe al paciente en el centro de la relación asistencial. Los servicios de atención primaria (AP) juegan un papel clave para favorecer un cambio de cultura asistencial introduciendo mejoras en la gestión, atención y derivación de pacientes mayores y/o con EC. No obstante, para no sobrecargar las funciones diarias de los profesionales de AP, sería interesante y útil la implementación de sistemas que les ayuden a tomar decisiones relacionadas con la gestión de este tipo de pacientes. Así pues, la presente tesis apuesta por el uso potencial de los sistemas de estratificación en población mayor con EC desde los servicios de AP. A lo largo de esta tesis doctoral se han desarrollado tres estudios independientes pero interconectados entre sí que ofrecen una visión global de la viabilidad y el uso potencial de las herramientas de estratificación en los servicios de AP con el objetivo de detectar pacientes con riesgo de sufrir un ingreso hospitalario futuro (IHF). En primer lugar, se estudió la aplicación de dos herramientas originalmente desarrolladas y validadas en Estados Unidos (Probability of Repeated Admission – Pra – y The Community Assessment Risk Screen – CARS) en una muestra de personas mayores del Sistema Valenciano de Salud (SVS). En segundo lugar, dado que los resultados del estudio anterior fueron limitados, se desarrolló un modelo de estratificación nuevo – asociado a un algoritmo matemático predictivo – partiendo de las características propias del SVS y de la población mayor de la Comunidad Valenciana. Finalmente, se presenta un caso práctico del uso de herramientas de estratificación poblacional para seleccionar e incluir pacientes con EC en un programa de telemonitorización en función su nivel de riesgo de sufrir un IHF. La tesis concluye con una serie de recomendaciones políticas extraídas de los resultados obtenidos en los tres estudios que la componen que el SVS u otros sistemas sanitarios con características similares podrían tener en consideración para mejorar la gestión de pacientes mayores con EC.The scenario in which this thesis is framed is characterized by a population each time living longer and with a percentage of older people being progressively higher. Additionally, the increasing prevalence of chronic diseases (CD) means an important impact on healthcare systems, as they are the main cause of death worldwide and, in many cases, they are associated to dependency situations and long-term care. In order to approach more effectively the conditions associated to ageing and chronicity, care systems should experience a paradigm change in which the patient is placed in the centre of the care relationship. Primary care (PC) services play an indispensable role to encourage these changes in the care culture by introducing improvements in the management, care and referral of elderly patients and/or with CD. However, in order to not overload the daily functions of PC professionals it would be interesting and useful the implementation of support decision making systems related to the management of these patients. Thus, this thesis banks on the potential use of stratification systems in elderly population with CD at PC services. Throughout this doctoral thesis, three independent but interconnected studies have been carried out. They offer a global view of the viability and potential use of stratification tools at PC services aimed to detect patients at risk of future hospital admissions (FHA). Firstly, it was studied the application of two stratification tools originally developed and validated in the United States (Probability of Repeated Admission – Pra – and The Community Assessment Risk Screen – CARS) – in a sample of elderly people from the Valencian Healthcare System (VHS). Secondly, due to the limited results of the previous study, a new stratification model was developed – associated to a predictive mathematical algorithm – based on the own characteristics of the VHS and the elderly population of the Valencia Region. Finally, a practical implementation using population stratification systems is presented aimed to select and include patients with CD in a telemonitoring programme according to their risk of suffering FHA. The thesis concludes with a set of policy recommendation taken from the results obtained in the three studies. These recommendations may be taken into consideration to improve the management of elderly patients with CD at the VHS or other healthcare systems with similar characteristics

Improving the management of potentially predictable hospital readmissions of the elderly and their quality of life through new icts

3rd International Conference on the Elderly and New Technologies. III Jornadas Internacionales de Mayores y Nuevas Tecnologías.The ageing population is currently beginning to create economic repercussions, as ageing often implies an increase of health expenditure related to, specially, hospital admissions and/or unplanned readmissions and long term care services. The present paper deals with two strategies that could be implemented through the establishment and use of new technologies to avoid these increasing costs: 1) screening tools of health information systems aimed at identifying patients at risk of hospital readmissions or repeated use of health resources; and 2) new icts at elderly homes to improve and monitor their quality of life. On the one hand, the screening tool The Community Assessment Risk Screen (cars) has been tested in several health areas in the Valencian Community, Spain. On the other hand, the results obtained in this research topic are connected with the proposal of installing technologies at elderly homes through the project Smart technologies for self-service to seniors in social housing – host. This user-friendly technology is aimed at improving the quality of life of the elderly, to reinforce their social inclusion and to make possible they live for a longer period of time with independence in their houses. Thus, through new technologies the efficiency of social and health resources could improve, and it will contribute to optimize their use, their management, efficiency and the sustainability of current social protection systems.Actualmente el envejecimiento de la población está dando lugar a repercusiones de tipo económico, pues implica un incremento del gasto sanitario asociado, especialmente, a ingresos hospitalarios u hospitalizaciones no planificadas, así como a cuidados de larga duración. En el presente artículo se tratan dos estrategias que podrían llevarse a cabo a través de la implementación y el uso de nuevas tecnologías con el objetivo de evitar el incremento en dicho tipo de gastos: 1) aplicación dentro de los sistemas de información sanitaria de herramientas de detección de pacientes con riesgo de sufrir reingresos hospitalarios o de hacer un uso repetido de recursos de tipo sanitario; y 2) nuevas tics instaladas en las casas de personas mayores para mejorar y monitorizar su calidad de vida. Por una parte, se ha aplicado la herramienta The Community Assessment Risk Screen –cars– en distintos departamentos de salud de la Comunidad Valenciana (España). Por otro lado, los resultados obtenidos en dicha investigación están estrechamente conectados con la propuesta de instalación de tecnologías en las casas de personas mayores que ofrece el proyecto Smart technologies for self-service to seniors in social housing – host. Esta tecnología fácil de usar está destinada a mejorar la calidad de vida de las personas mayores, a reforzar su inclusión social y a facilitar que puedan vivir durante más tiempo con independencia en sus hogares. De este modo, a través de las nuevas tecnologías, se podría mejorar la eficiencia de los recursos sociosanitarios, así como su coordinación y, finalmente, la sostenibilidad del sistema de protección social actual

Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs

[EN] Palliative care (PC) has demonstrated benefits for life-limiting illnesses. Bad survival prognosis and patients' decline are working criteria to guide PC decision-making for older patients. Still, there is not a clear consensus on when to initiate early PC. This work aims to propose machine learning approaches to predict frailty and mortality in older patients in supporting PC decision-making. Predictive models based on Gradient Boosting Machines (GBM) and Deep Neural Networks (DNN) were implemented for binary 1-year mortality classification, survival estimation and 1-year frailty classification. Besides, we tested the similarity between mortality and frailty distributions. The 1-year mortality classifier achieved an Area Under the Curve Receiver Operating Characteristic (AUC ROC) of 0.87 [0.86, 0.87], whereas the mortality regression model achieved an mean absolute error (MAE) of 333.13 [323.10, 342.49] days. Moreover, the 1-year frailty classifier obtained an AUC ROC of 0.89 [0.88, 0.90]. Mortality and frailty criteria were weakly correlated and had different distributions, which can be interpreted as these assessment measurements are complementary for PC decision-making. This study provides new models that can be part of decision-making systems for PC services in older patients after their external validation.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the InAdvance project (H2020-SC1-BHC-2018-2020 No. 825750).Blanes-Selva, V.; Doñate-Martínez, A.; Linklater, G.; Garcia-Gomez, JM. (2022). Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs. Health Informatics Journal. 28(2):1-18. https://doi.org/10.1177/1460458222109259211828

Responsive and Minimalist App Based on Explainable AI to Assess Palliative Care Needs during Bedside Consultations on Older Patients

[EN] Palliative care is an alternative to standard care for gravely ill patients that has demonstrated many clinical benefits in cost-effective interventions. It is expected to grow in demand soon, so it is necessary to detect those patients who may benefit from these programs using a personalised objective criterion at the correct time. Our goal was to develop a responsive and minimalist web application embedding a 1-year mortality explainable predictive model to assess palliative care at bedside consultation. A 1-year mortality predictive model has been trained. We ranked the input variables and evaluated models with an increasing number of variables. We selected the model with the seven most relevant variables. Finally, we created a responsive, minimalist and explainable app to support bedside decision making for older palliative care. The selected variables are age, medication, Charlson, Barthel, urea, RDW-SD and metastatic tumour. The predictive model achieved an AUC ROC of 0.83 [CI: 0.82, 0.84]. A Shapley value graph was used for explainability. The app allows identifying patients in need of palliative care using the bad prognosis criterion, which can be a useful, easy and quick tool to support healthcare professionals in obtaining a fast recommendation in order to allocate health resources efficiently.This work was supported by the InAdvance project (H2020-SC1-BHC-2018-2020 grant agreement number 825750.) and the CANCERLEss project (H2020-SC1-2020-Single-Stage-RTD grant agreement number 965351), both funded by the European Union's Horizon 2020 research and innovation programme.Blanes-Selva, V.; Doñate-Martínez, A.; Linklater, G.; Garcés-Ferrer, J.; Garcia-Gomez, JM. (2021). Responsive and Minimalist App Based on Explainable AI to Assess Palliative Care Needs during Bedside Consultations on Older Patients. Sustainability. 13(17):1-11. https://doi.org/10.3390/su13179844111131

Equal opportunities to social inclusion for autistic Children

La tasa de prevalencia de los trastornos del espectro del autismo (TEA) se ha incrementado dramáticamente en los últimos años. El Centro para el Control y la Prevención de Enfermedades de Atlanta estima que aproximadamente 1 de cada 68 niños ha sido identificado con TEA. Los niños con TEA presentan problemas en las habilidades sociales, emocionales, de comunicación y de la vida diaria. Por otra parte, presentan dificultades desde la primera infancia en áreas clave para el aprendizaje y para su desarrollo. Debido a estas características la mayoría de los niños con TEA necesitan programas específicos de inclusión educativa; en este sentido, la acción y la atención temprana es muy importante para favorecer un desarrollo positivo, así como su inclusión en la sociedad. El proyecto titulado "Igualdad de Oportunidades para la Inclusión Social para Niños Autistas, EOSIAC", financiado dentro del programa Grundtvig de la Comisión Europea (ref. 2013-1-SR1-GRU06-29490) está principalmente destinado a apoyar la integración de los niños entre 5 y 10 años de edad con autismo en la educación pública. A través de este proyecto transnacional profesionales de diferentes ámbitos implicados en la atención del autismo de diferentes países (Rumanía, España, Italia, Alemania, Turquía y Bulgaria) están intercambiando conocimientos y mejores prácticas dirigidas a crear una red de educadores especializados y consejeros. Este punto es muy importante ya que implica un empoderamiento de los profesionales en este campo a través de la adquisición de más conocimiento acerca de la inclusión educativa de TEA basado en las diferentes realidades de varios contextos europeos. Dentro del proyecto, el Instituto de Investigación Polibienestar (www.polibienestar.org) está a cargo del desarrollo de una metodología de integración de los niños autistas en la educación pública que se puede aplicar con éxito en cada país participante en el proyecto. Estas directrices metodológicas se basan en las referencias científicas y las buenas prácticas basadas en la evidencia, teniendo en consideración una revisión de investigaciones recientes, las iniciativas y los marcos legislativos. La metodología contendrá la base principal para una integración efectiva de los niños y debe ser de fácil adaptción a diferentes contextos culturales, educativos y legislativos. Otros productos relevantes del proyecto serán la elaboración de directrices para los padres de niños con ASD para ayudarles en el cuidado de sus hijos; y para los profesores con el objetivo de proporcionarles conocimientos y habilidades para la integración. Así, a través de la participación de los padres de niños con TEA y sus profesores se espera que el proyecto tenga un impacto real en la calidad de vida y el bienestar de los niñosThe prevalence rate of autism disorders has dramatically increased during the last years. The Centre for Disease Control and Prevention from Atlanta estimates that about 1 in 68 children have been identified with autism spectrum disorder (ASD). Children with ASD present problems with social, emotional and communication skills in their daily life. Moreover, they present difficulties since early childhood in key areas for learning and development processes. Due to these characteristics most of children with ASD need specific programmes of educative inclusion; in this sense, early action and care is very important to favor a positive long-term development, as well as their inclusion into society. The project entitled “Equal Opportunities to Social Inclusion for Autistic Children, EOSIAC”, funded under the Grundtvig programme from the European Commission (ref. 2013-1-RO1-GRU06-29490) is mainly aimed to support the integration of children between 5 and 10 years old with autism in public education. Through this transnational project professionals from different fields involved in the care of autism from different countries (Romania, Spain, Italy, Germany, Turkey and Bulgaria) are exchanging knowledge and best practices aimed to create a network of specialized educators and counselors. This point is very relevant as it entails an empowerment of professionals in this field through the acquisition of more knowledge about educative inclusion of ASD based in the different realities from several European contexts. Within the project, Polibienestar Research Institute (www.polibienestar.org) is in charge of the development of a methodology for integrating the phenomenon of autistic children in public education that can be applied successfully in each country participating in the project. These methodological guidelines will be based in references and good practices with scientific evidence, taking into consideration a revision of recent researches, initiatives and legislation frameworks. The methodology will contain the main basis for an effective integration of children and it will be easy-to-adapt to different cultural, educative and legislative contexts. Other relevant products of the project will be the development of guidelines for parents of children with ASD to help them in the care of their children; and guidelines for teachers providing knowledge and skills on integration. So, through the involvement of parents of children with ASD and their teachers it is expected that the project has a real impact on children’s quality of life and wellbein

User-centred design of a clinical decision support system for palliative care: Insights from healthcare professionals

[EN] Objective:Although clinical decision support systems (CDSS) have many benefits for clinical practice, they also have several barriers to their acceptance by professionals. Our objective in this study was to design and validate The Aleph palliative care (PC) CDSS through a user-centred method, considering the predictions of the artificial intelligence (AI) core, usability and user experience (UX). Methods:We performed two rounds of individual evaluation sessions with potential users. Each session included a model evaluation, a task test and a usability and UX assessment. Results:The machine learning (ML) predictive models outperformed the participants in the three predictive tasks. System Usability Scale (SUS) reported 62.7 +/- 14.1 and 65 +/- 26.2 on a 100-point rating scale for both rounds, respectively, while User Experience Questionnaire - Short Version (UEQ-S) scores were 1.42 and 1.5 on the -3 to 3 scale. Conclusions:The think-aloud method and including the UX dimension helped us to identify most of the workflow implementation issues. The system has good UX hedonic qualities; participants were interested in the tool and responded positively to it. Performance regarding usability was modest but acceptable.The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the InAdvance project (H2020-SC1-BHC-2018¿2020 grant number 825750) and the CANCERLESS project (H2020-SC1-2020-Single-Stage-RTD grant number 965351), both funded by the European Union¿s Horizon 2020 research and innovation programme. Also, it was partially supported by the ALBATROSS project (National Plan for Scientific and Technical Research and Innovation 2017¿ 2020, grant number PID2019-104978RB-I00)Blanes-Selva, V.; Asensio-Cuesta, S.; Doñate-Martínez, A.; Pereira Mesquita, F.; Garcia-Gomez, JM. (2023). User-centred design of a clinical decision support system for palliative care: Insights from healthcare professionals. Digital Health. 9:1-13. https://doi.org/10.1177/20552076221150735113

Functional requirements to mitigate the Risk of Harm to Patients from Artificial Intelligence in Healthcare

The Directorate General for Parliamentary Research Services of the European Parliament has prepared a report to the Members of the European Parliament where they enumerate seven main risks of Artificial Intelligence (AI) in medicine and healthcare: patient harm due to AI errors, misuse of medical AI tools, bias in AI and the perpetuation of existing inequities, lack of transparency, privacy and security issues, gaps in accountability, and obstacles in implementation. In this study, we propose fourteen functional requirements that AI systems may implement to reduce the risks associated with their medical purpose: AI passport, User management, Regulation check, Academic use only disclaimer, data quality assessment, Clinicians double check, Continuous performance evaluation, Audit trail, Continuous usability test, Review of retrospective/simulated cases, Bias check, eXplainable AI, Encryption and use of field-tested libraries, and Semantic interoperability. Our intention here is to provide specific high-level specifications of technical solutions to ensure continuous good performance and use of AI systems to benefit patients in compliance with the future EU regulatory framework.Comment: 14 pages, 1 figure, 1 tabl

Evaluation design of the patient-centred pathways of early palliative care, supportive ecosystems and appraisal standard (InAdvance):a randomised controlled trial

BACKGROUND: Palliative care aims to contribute to pain relief, improvement with regard to symptoms and enhancement of health-related quality of life (HRQoL) of patients with chronic conditions. Most of the palliative care protocols, programmes and units are predominantly focused on patients with cancer and their specific needs. Patients with non-cancer chronic conditions may also have significantly impaired HRQoL and poor survival, but do not yet receive appropriate and holistic care. The traditional focus of palliative care has been at the end-of-life stages instead of the relatively early phases of serious chronic conditions. The ‘Patient-centred pathways of early palliative care, supportive ecosystems and appraisal standard’ (InAdvance) project implements and evaluates early palliative care in the daily clinical routine addressing patients with complex chronic conditions in the evolution towards advanced stages. The objective of the current study is to evaluate the acceptability, feasibility, effectiveness and cost-effectiveness of this novel model of palliative care in the relatively early phases in patients with chronic conditions. METHODS: In this study, a single blind randomised controlled trial design will be employed. A total of 320 participants (80 in each study site and 4 sites in total) will be randomised on a 1:1 basis to the Palliative Care Needs Assessment (PCNA) arm or the Care-as-Usual arm. This study includes a formative evaluation approach as well as a cost-effectiveness analysis with a within-trial horizon. Study outcomes will be assessed at baseline, 6 weeks, 6 months, 12 months and 18 months after the implementation of the interventions. Study outcomes include HRQoL, intensity of symptoms, functional status, emotional distress, caregiving burden, perceived quality of care, adherence to treatment, feasibility, acceptability, and appropriateness of the intervention, intervention costs, other healthcare costs and informal care costs. DISCUSSION: The InAdvance project will evaluate the effect of the implementation of the PCNA intervention on the target population in terms of effectiveness and cost-effectiveness in four European settings. The evidence of the project will provide step-wise guidance to contribute an increased evidence base for policy recommendations and clinical guidelines, in an effort to augment the supportive ecosystem for palliative care. TRIAL REGISTRATION: ISRCTN, ISRCTN24825698. Registered 17/12/2020

Aplicación de The Community Assessment Risk Screen en centros de atención primaria del Sistema Sanitario Valenciano

Objetivo: Aplicar la herramienta The Community Assessment Risk Screen (CARS) para detectar pacientes mayores con riesgo de reingreso hospitalario y estudiar la viabilidad de su inclusión en los sistemas de información sanitaria. Diseño: Estudio de cohortes retrospectivo. Emplazamiento: Departamentos de salud 6, 10 y 11 de la Comunidad Valenciana. Participantes: Pacientes de 65 años o más atendidos en diciembre de 2008 en 6 centros de salud. La muestra fue de 500 pacientes (error muestral = ± 4,37%, fracción de muestreo = 1/307). Mediciones: Instrumento CARS formado por 3 ítems: diagnósticos (enfermedades cardiacas, diabetes, infarto de miocardio, ictus, EPOC, cáncer), número de fármacos prescritos e ingresos hospitalarios o visitas a urgencias en los 6 meses previos. Los datos procedían de SIA-Abucasis, GAIA y CMBD, y fueron contrastados con profesionales de atención primaria. La variable de resultado fue el ingreso durante 2009. Resultados: Los niveles de riesgo del CARS están relacionados con el futuro reingreso (p < 0,001). El valor de la sensibilidad y la especificidad es de 0,64, el instrumento identifica mejor a los pacientes con baja probabilidad de ser hospitalizados en el futuro (valor predictivo negativo = 0,91; eficacia diagnóstica = 0,67), pero tiene un valor predictivo positivo del 0,24. Conclusiones: El CARS original no identifica adecuadamente a la población con alto riesgo de reingreso hospitalario. No obstante, si fuese revisado y mejora su valor predictivo positivo, podría ser incorporado en los sistemas informáticos de atención primaria, siendo útil en el cribado y la segmentación inicial de la población de pacientes crónicos con riesgo de rehospitalización

Palliative Care in Older People with Multimorbidities: A Scoping Review on the Palliative Care Needs of Patients, Carers, and Health Professionals

Although numerous studies have been conducted previously on the needs of cancer patients at the end of their life, there is a lack of studies focused on older patients with non-oncological complex chronic multipathologies. Examining these needs would help to gain a greater understanding of the profile of this specific population within the palliative care (PC) pathway and how the health and care systems can address them. The aim of this review was to identify the needs influencing PC among older patients with multimorbidities, their relatives or informal caregivers, and the health professionals who provide care for these patients. A scoping literature review guided by the Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist was carried out with literature searched in the Medline, Embase, CINAHL, WoS, Cochrane Library, PsycINFO, and Scopus databases from 2009 to 2022. Eighty-one studies were included, demonstrating a great variety of unaddressed needs for PC among chronic older patients and the complexity in detecting those needs and how to refer them to PC pathways. This review also suggested a scarcity of tools and limited pathways for professionals to satisfy their needs for these patients and their families, who often felt ignored by the system. Substantial changes will be needed in health and care systems at the institutional level, providing more specialized PC environments and systematizing PC processes