Research in primary care as an area of knowledge. SESPAS Report 2012

Atenció primària de la salut; Recerca; Medicina familiar i comunitàriaAtención primaria de la salud; Investigación; Medicina familiar y comunitariaPrimary health care; Research; Family medicineLa atención primaria de salud ofrece grandes oportunidades para la investigación. Constituye un área de conocimiento propio, que es necesario desarrollar para mejorar la calidad de sus servicios y la salud de los pacientes. Estas oportunidades son únicas para la investigación clínica de base poblacional, con un enfoque de promoción de la salud y de prevención de la enfermedad, ya sea primaria, secundaria o terciaria. Es prioritario investigar en el desarrollo del modelo biopsicosocial de atención, nuevos modelos de atención integrada y atención comunitaria. Cabe destacar la actividad y la estructura generada por la Red de Investigación en Actividades Preventivas y de Promoción de la Salud (redIAPP), que ha atraído a su alrededor gran parte de la actividad investigadora en atención primaria de salud en nuestro país. A pesar del esfuerzo de diversas instituciones y fundaciones, así como de unidades docentes y de investigación, el desarrollo de la investigación no ha alcanzado el volumen, la relevancia, la calidad y el impacto deseables. La presencia de los profesionales de atención primaria de salud en las estructuras de investigación sigue siendo escasa, y la inversión en proyectos y líneas de investigación propias es pobre. Para poder invertir esta situación se precisa una serie de medidas: consolidar estructuras organizativas de apoyo específicas, con adecuada dotación de personal y recursos económicos; facilitar que los profesionales puedan compatibilizar su labor clínica con una dedicación específica a la investigación, para que elaboren proyectos relevantes y consoliden líneas de investigación estables de contenidos acordes con el área de conocimiento propio, y que se apliquen a la mejora de la calidad y a la innovación de los servicios de atención primaria de salud.Primary care offers huge potential for research. This setting is an area of knowledge that must expand to improve the quality of its services and patients’ health. Population-based clinical studies with a focus on health promotion and primary, secondary and tertiary disease prevention offer unique research opportunities. Developing research in the biopsychosocial model of clinical practice and new models of integrated healthcare and community care is therefore a priority. The framework and activities carried out by the Research Network in Preventive Activities and Health Promotion have been instrumental in the development of research in primary care in Spain. Despite the efforts invested by various institutions, foundations, teaching and research departments in primary care research, the projected outputs in terms of volume, quality and impact have not been achieved. The involvement of primary care professionals in research platforms is insufficient, with scarce contribution toward investment in specific primary care research projects. To change the current status of research in primary care, a number of measures are required, namely, the consolidation of research organisms specific to primary care with adequate allocation of funding and staff, and the allocation of specific time for research to primary care professionals to enable them to produce significant projects and consolidate established research lines in their areas of expertise, with applications mainly in quality improvement and innovation of primary care services

Contribution of frailty to multimorbidity patterns and trajectories: Longitudinal dynamic cohort study of aging people

Background: Multimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people. Objective: This study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older. Methods: Longitudinal data were drawn from electronic health records through the SIDIAP (Sistema d’Informació pel Desenvolupament de la Investigació a l’Atenció Primària) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period. Results: The study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers &peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1% (656,778/1,456,052) remained in the same pattern. Conclusions: Our results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories.The project received a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded in 2019 under the Health Strategy Action 2013-2016, within the National Research Programme oriented to Societal Challenges, within the Technical, Scientific and Research National Plan 2013-2016 (reference PI19/00535), and the PFIS Grant FI20/00040, co-funded with European Union ERDF (European Regional Development Fund) funds.Peer ReviewedPostprint (published version

Prediction models using artificial intelligence and longitudinal data from electronic health records: a systematic methodological review

Objective: To describe and appraise the use of artificial intelligence (AI) techniques that can cope with longitudinal data from electronic health records (EHRs) to predict health-related outcomes. Methods: This review included studies in any language that: EHR was at least one of the data sources, collected longitudinal data, used an AI technique capable of handling longitudinal data, and predicted any health-related outcomes. We searched MEDLINE, Scopus, Web of Science, and IEEE Xplorer from inception to January 3, 2022. Information on the dataset, prediction task, data preprocessing, feature selection, method, validation, performance, and implementation was extracted and summarized using descriptive statistics. Risk of bias and completeness of reporting were assessed using a short form of PROBAST and TRIPOD, respectively. Results: Eighty-one studies were included. Follow-up time and number of registers per patient varied greatly, and most predicted disease development or next event based on diagnoses and drug treatments. Architectures generally were based on Recurrent Neural Networks-like layers, though in recent years combining different layers or transformers has become more popular. About half of the included studies performed hyperparameter tuning and used attention mechanisms. Most performed a single train-test partition and could not correctly assess the variability of the model’s performance. Reporting quality was poor, and a third of the studies were at high risk of bias. Conclusions: AI models are increasingly using longitudinal data. However, the heterogeneity in reporting methodology and results, and the lack of public EHR datasets and code sharing, complicate the possibility of replication.The project received a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded on the 2019 call under the Health Strategy Action 2013-2016, within the National Research Programme oriented to Societal Challenges, within the Technical, Scientific and Innovation Research National Plan 2013-2016 (reference PI19/00535), and the PFIS Grant FI20/00040, cofunded with European Union ERDF (European Regional Development Fund) funds. The project has also been partially funded by Generalitat de Catalunya through the AGAUR (grant numbers 2021-SGR-01033, 2021-SGR-01537).Peer ReviewedPostprint (published version

Dynamics of multimorbidity and frailty, and their contribution to mortality, nursing home and home care need: A primary care cohort of 1 456 052 ageing people

Envejecimiento; Fragilidad; Mortalidad; Atención primariaAging; Fragility; Mortality; Primary health careEnvelliment; Fragilitat; Mortalitat; Atenció primàriaBackground: Prevalence of both multimorbidity and frailty increases with age, but more evidence is needed to elucidate their relationship and their association with other health-related outcomes. We analysed the dynamics of both conditions as people age and calculate the associated risk of death, nursing home admission, and need for home care. Methods: Data were drawn from the primary care electronic health records of a longitudinal cohort of people aged 65 or older in Catalonia in 2010-2019. Frailty and multimorbidity were measured using validated instruments (eFRAGICAP, a cumulative deficit model; and SNAC-K, respectively), and their longitudinal evolution was described. Cox regression models accounted for the competing risk of death and adjusted by sex, socioeconomical status, and time-varying age, alcohol and smoking. Findings: We included 1 456 052 patients. Prevalence of multimorbidity was consistently high regardless of age, while frailty almost quadrupled from 65 to 99 years. Frailty worsened and also changed with age: up to 84 years, it was more related to concurrent diseases, and afterwards, to frailty-related deficits. While concurrent diseases contributed more to mortality, frailty-related deficits increased the risk of institutionalisation and the need for home care. Interpretation: The nature of people's multimorbidity and frailty vary with age, as does their impact on health status. People become frailer as they age, and their frailty is more characterised by disability and other symptoms than by diseases. Mortality is most associated with the number of comorbidities, whereas frailty-related deficits are associated with needing specialised care.Instituto de Salud Carlos III through PI19/00535, and the PFIS Grant FI20/00040 (Co-funded by European Regional Development Fund/European Social Fund)

Dynamics of multimorbidity and frailty, and their contribution to mortality, nursing home and home care need: A primary care cohort of 1 456 052 ageing people

Background: Prevalence of both multimorbidity and frailty increases with age, but more evidence is needed to elucidate their relationship and their association with other health-related outcomes. We analysed the dynamics of both conditions as people age and calculate the associated risk of death, nursing home admission, and need for home care. Methods: Data were drawn from the primary care electronic health records of a longitudinal cohort of people aged 65 or older in Catalonia in 2010–2019. Frailty and multimorbidity were measured using validated instruments (eFRAGICAP, a cumulative deficit model; and SNAC-K, respectively), and their longitudinal evolution was described. Cox regression models accounted for the competing risk of death and adjusted by sex, socioeconomical status, and time-varying age, alcohol and smoking. Findings: We included 1 456 052 patients. Prevalence of multimorbidity was consistently high regardless of age, while frailty almost quadrupled from 65 to 99 years. Frailty worsened and also changed with age: up to 84 years, it was more related to concurrent diseases, and afterwards, to frailty-related deficits. While concurrent diseases contributed more to mortality, frailty-related deficits increased the risk of institutionalisation and the need for home care. Interpretation: The nature of people’s multimorbidity and frailty vary with age, as does their impact on health status. People become frailer as they age, and their frailty is more characterised by disability and other symptoms than by diseases. Mortality is most associated with the number of comorbidities, whereas frailty-related deficits are associated with needing specialised care.The project received a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded on the 2019 call under the Health Strategy Action 2013−2016, within the National Research Programme oriented to Societal Challenges,within the Technical, Scientific and Innovation Research National Plan 2013−2016, (reference PI19/00535), and the PFIS Grant FI20/00040, co-funded with European Union ERDF (European Regional Development Fund) funds. The funder had no role in the study design, data collection, data analysis, data interpretation, or writing of this work.Peer ReviewedPostprint (published version

Evaluation of a support system for health professionals confined by COVID-19

OBJETIVOS: Evaluar la implementación de un circuito telefónico de apoyo a profesionales sanitarios confinados por COVID-19 en una dirección de Atención Primaria de Barcelona, en España.  MÉTODOS: Estudio observacional, descriptivo y transversal, realizado con profesionales confinados en domicilio entre el 11 de marzo y el 31 de mayo de 2020. Se envió por correo electrónico un cuestionario con 18 preguntas cerradas y una abierta. Se realizó un análisis descriptivo de las respuestas cerradas y un análisis del contenido temático de la pregunta abierta. RESULTADOS: 398 profesionales puntuaron globalmente el circuito con 6,54 en una escala de 1 a 10. El formato de las llamadas realizadas en el circuito de apoyo se estimó con las puntuaciones máximas, la unidad de apoyo psicológico y la coordinación por diferentes colectivos se evaluaron con las puntuaciones más bajas. El análisis del contenido de la pregunta abierta ofrece argumentos explicativos de los resultados cuantitativos.  CONCLUSIONES: El estudio permitió evaluar de manera válida y fiable la implementación de un circuito de apoyo a profesionales confinados, además de reconocer áreas de mejora. OBJECTIVE: To evaluate the implementation of a telephone system in a department of Primary Care in Barcelona, Spain, supporting health professionals confined by COVID-19.  METHODS: We conducted an observational, descriptive, cross-sectional study with confined professionals, between March 11 and May 31, 2020. We emailed a questionnaire with 18 closed-ended questions and one open-ended question and performed a descriptive analysis of the closed-ended answers and an analysis of the thematic content of the open-ended question.  RESULTS: Thirty-nine hundred and ninety-eight professionals evaluated the system overall with a score of 6.54 on a scale of 1 to 10. The evaluation of the format of calls made in the support system had higher scores, while the psychological support unit and the coordination of the different groups had lower scores. The content analysis of the open-ended question provides explanatory arguments for the quantitative results.  CONCLUSIONS: The study allowed a valid and reliable evaluation of the implementation of a support system for confined professionals, in addition to recognizing areas for improvement.

Determinación de la presión arterial con metodología usual y con registro continuo de 24 horas comparación entre ambos métodos para el diagnóstico y seguimiento de los hipertensos

Objetivos : Comparar dos métodos de toma de la presión arterial (PA), el usual, esfigmomanómetro de mercurio y el registro continuo de medición de la PA durante 24 horas en hipertensos. Material y métodos: La PA se midió a los 3, 2, 1 mes previo a la colocación del Holter. Se definieron criterios de normalidad para el método clásico y el Holter. Variables de estudio: presión arterial sistólica y diastólica (PAS, PAD) diurna y nocturna, frecuencia cardiaca (FC), tipo de tratamiento. Conclusiones: La media de la PAS y PAD del Holter diurna y nocturna es inferior a la del método clásico. La media de la PA es poco fiable para predecir el perfil circadiano de la PA. Los criterios de control del Holter no están influenciados por el tratamiento. Las dos técnicas no son comparables. El ritmo circadiano de la PA no se modifica, independientemente del grado de PA que tengan durante la vigilia

Research in primary care as an area of knowledge. SESPAS Report 2012

Atenció primària de la salut; Recerca; Medicina familiar i comunitàriaAtención primaria de la salud; Investigación; Medicina familiar y comunitariaPrimary health care; Research; Family medicineLa atención primaria de salud ofrece grandes oportunidades para la investigación. Constituye un área de conocimiento propio, que es necesario desarrollar para mejorar la calidad de sus servicios y la salud de los pacientes. Estas oportunidades son únicas para la investigación clínica de base poblacional, con un enfoque de promoción de la salud y de prevención de la enfermedad, ya sea primaria, secundaria o terciaria. Es prioritario investigar en el desarrollo del modelo biopsicosocial de atención, nuevos modelos de atención integrada y atención comunitaria. Cabe destacar la actividad y la estructura generada por la Red de Investigación en Actividades Preventivas y de Promoción de la Salud (redIAPP), que ha atraído a su alrededor gran parte de la actividad investigadora en atención primaria de salud en nuestro país. A pesar del esfuerzo de diversas instituciones y fundaciones, así como de unidades docentes y de investigación, el desarrollo de la investigación no ha alcanzado el volumen, la relevancia, la calidad y el impacto deseables. La presencia de los profesionales de atención primaria de salud en las estructuras de investigación sigue siendo escasa, y la inversión en proyectos y líneas de investigación propias es pobre. Para poder invertir esta situación se precisa una serie de medidas: consolidar estructuras organizativas de apoyo específicas, con adecuada dotación de personal y recursos económicos; facilitar que los profesionales puedan compatibilizar su labor clínica con una dedicación específica a la investigación, para que elaboren proyectos relevantes y consoliden líneas de investigación estables de contenidos acordes con el área de conocimiento propio, y que se apliquen a la mejora de la calidad y a la innovación de los servicios de atención primaria de salud.Primary care offers huge potential for research. This setting is an area of knowledge that must expand to improve the quality of its services and patients’ health. Population-based clinical studies with a focus on health promotion and primary, secondary and tertiary disease prevention offer unique research opportunities. Developing research in the biopsychosocial model of clinical practice and new models of integrated healthcare and community care is therefore a priority. The framework and activities carried out by the Research Network in Preventive Activities and Health Promotion have been instrumental in the development of research in primary care in Spain. Despite the efforts invested by various institutions, foundations, teaching and research departments in primary care research, the projected outputs in terms of volume, quality and impact have not been achieved. The involvement of primary care professionals in research platforms is insufficient, with scarce contribution toward investment in specific primary care research projects. To change the current status of research in primary care, a number of measures are required, namely, the consolidation of research organisms specific to primary care with adequate allocation of funding and staff, and the allocation of specific time for research to primary care professionals to enable them to produce significant projects and consolidate established research lines in their areas of expertise, with applications mainly in quality improvement and innovation of primary care services

Autoencoders for health improvement by compressing the set of patient features

A challenge to solve when analyzing multimorbidity patterns in elderly people is the management of a high number of characteristics associated with each patient. The main variables to study multimorbidity are diseases, however other variables should be considered to better classify the people included in each pattern. Age, sex, social class and medication are frequently used in the typing of each multimorbidity pattern. Subsequently the cardinality of the set of features that characterize a patient is very high and normally, the set is compressed to obtain a patient vector of new variables whose dimension is noticeably smaller than that of the initial set. To minimize the loss of information by compression, traditionally Principal Component Analysis (PCA) based projection techniques have been used, which although they are generally a good option, the projection is linear, which somehow reduces its flexibility and limits the performance. As an alternative to the PCA based techniques, in this paper, it is proposed to use autoencoders, and it is shown the improvement in the obtained multimorbidity patterns from the compressed database, when the registered data on about a million patients (5 years' follow-up) are processed. This work demonstrates that autoencoders retain a larger amount of information in each pattern and results are more consistent with clinical experience than other approaches frequently found in the literature.Clinical relevance- From an epidemiological perspective, the contribution is relevant, since it allows for a more precise analysis of multimorbidity patterns, leading to better approaches to patient health strategies.Work supported by Carlos III Institute of Health, Spanish Ministry of Economy and Competitiveness and ERDF (UE) funds under Grant PI16/00639, and in part by Catalan Government funds under Grants 2017 SGR 578 AGAUR and Strategic Plan for Research in Health PERIS grant number SLT002/16/00058Peer ReviewedPostprint (published version

Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: Cross-sectional study in a Mediterranean population

The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population =65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.Peer Reviewe