Q3144496 (Q3144496): Difference between revisions
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(Created claim: summary (P836): Objective: Creation of models to predict the risk of re-entry in the short term (30-90 days) and in the medium term (one year).Identify the differences between re-entry and non-re-entry patients and the most frequent preventable re-entry profiles in our environment. Methodology: Prospective observational cohort study of patients discharged with a diagnosis of heart failure in the 5 participating centers. In addition, a case-control nested in the...) |
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Objective: Creation of models to predict the risk of re-entry in the short term (30-90 days) and in the medium term (one year).Identify the differences between re-entry and non-re-entry patients and the most frequent preventable re-entry profiles in our environment. Methodology: Prospective observational cohort study of patients discharged with a diagnosis of heart failure in the 5 participating centers. In addition, a case-control nested in the previous cohort will be performed, with the cases being the patients who re-enter and the controls will be chosen according to age, sex, HF etiology, comorbidities and functional status. Sociodemographic, clinical and quality of life variables, empowerment and basal self-efficacy will be collected as predictors of re-entry. Regarding cases and controls, the quality of life in the post-high transition period, empowerment and self-efficacy, caregiver burden, social support, discharge care model, use of health services and adequacy, reconciliation and adherence to medication will be evaluated. Proportional Cox risk models will be developed for the creation of the predictive model, as well as conditioned logistic regression models to identify differences between cases and controls. Expected results: The SNS will be equipped with tools for predicting the risk of useful re-entry for clinicians and managers in order to be able to offer individualised high-care models. The most frequent characteristics of re-entry will be identified and preventable re-entry will be profiled, which will help create specific prevention actions in the future. (English) | |||||||||||||||
| Property / summary: Objective: Creation of models to predict the risk of re-entry in the short term (30-90 days) and in the medium term (one year).Identify the differences between re-entry and non-re-entry patients and the most frequent preventable re-entry profiles in our environment. Methodology: Prospective observational cohort study of patients discharged with a diagnosis of heart failure in the 5 participating centers. In addition, a case-control nested in the previous cohort will be performed, with the cases being the patients who re-enter and the controls will be chosen according to age, sex, HF etiology, comorbidities and functional status. Sociodemographic, clinical and quality of life variables, empowerment and basal self-efficacy will be collected as predictors of re-entry. Regarding cases and controls, the quality of life in the post-high transition period, empowerment and self-efficacy, caregiver burden, social support, discharge care model, use of health services and adequacy, reconciliation and adherence to medication will be evaluated. Proportional Cox risk models will be developed for the creation of the predictive model, as well as conditioned logistic regression models to identify differences between cases and controls. Expected results: The SNS will be equipped with tools for predicting the risk of useful re-entry for clinicians and managers in order to be able to offer individualised high-care models. The most frequent characteristics of re-entry will be identified and preventable re-entry will be profiled, which will help create specific prevention actions in the future. (English) / rank | |||||||||||||||
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| Property / summary: Objective: Creation of models to predict the risk of re-entry in the short term (30-90 days) and in the medium term (one year).Identify the differences between re-entry and non-re-entry patients and the most frequent preventable re-entry profiles in our environment. Methodology: Prospective observational cohort study of patients discharged with a diagnosis of heart failure in the 5 participating centers. In addition, a case-control nested in the previous cohort will be performed, with the cases being the patients who re-enter and the controls will be chosen according to age, sex, HF etiology, comorbidities and functional status. Sociodemographic, clinical and quality of life variables, empowerment and basal self-efficacy will be collected as predictors of re-entry. Regarding cases and controls, the quality of life in the post-high transition period, empowerment and self-efficacy, caregiver burden, social support, discharge care model, use of health services and adequacy, reconciliation and adherence to medication will be evaluated. Proportional Cox risk models will be developed for the creation of the predictive model, as well as conditioned logistic regression models to identify differences between cases and controls. Expected results: The SNS will be equipped with tools for predicting the risk of useful re-entry for clinicians and managers in order to be able to offer individualised high-care models. The most frequent characteristics of re-entry will be identified and preventable re-entry will be profiled, which will help create specific prevention actions in the future. (English) / qualifier | |||||||||||||||
point in time: 12 October 2021
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Revision as of 14:07, 12 October 2021
Project Q3144496 in Spain
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | No label defined |
Project Q3144496 in Spain |
Statements
25,600.0 Euro
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51,200.0 Euro
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50.0 percent
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1 January 2016
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31 March 2020
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FUNDACION VASCA DE INNOVACION E INVESTIGACION SANITARIAS
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43°13'59.74"N, 2°50'43.22"W
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48036
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Objetivo: Creación de modelos de predicción del riesgo de reingreso a corto plazo (30-90 días) y a medio plazo (un año).Identificar las diferencias entre los pacientes que reingresan y que no reingresan, y los perfiles de reingresos prevenibles más frecuentes en nuestro medio. Metodología: Estudio observacional cohortes prospectivo de pacientes que son dados de alta con diagnostico de insuficiencia cardiaca en los 5 centros participantes. Se realizará además un caso-control anidado en la cohorte previa, siendo los casos los pacientes que reingresan y los controles serán elegidos en función de edad, sexo, etiología de la IC, comorbilidades y estado funcional. Se recogerán variables sociodemográficas, clínicas y relacionadas con la calidad de vida, empoderamiento y autoeficacia basales como predictoras de reingreso. Respecto a los casos y controles, se evaluarán la calidad de vida en el periodo transicional post-alta, el empoderamiento y autoeficacia, carga del cuidador, apoyo social, modelo de atención al alta, uso de servicios sanitarios y adecuación, conciliación y adherencia a la medicación. Se realizarán modelos de riesgos proporcionales de Cox para la creación del modelo predictivo, así como modelos de regresión logística condicionada para identificar las diferencias entre los casos y controles. Resultados esperados: Se dotará al SNS de instrumentos de predicción del riesgo de reingresos de utilidad para clínicos y gestores para poder ofertar modelos de atención al alta individualizados. Se identificarán las características más frecuentes de los reingresan y se perfilarán reingreso prevenibles, que ayudarán a crear acciones específicas de prevención de los mismos en el futuro. (Spanish)
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Objective: Creation of models to predict the risk of re-entry in the short term (30-90 days) and in the medium term (one year).Identify the differences between re-entry and non-re-entry patients and the most frequent preventable re-entry profiles in our environment. Methodology: Prospective observational cohort study of patients discharged with a diagnosis of heart failure in the 5 participating centers. In addition, a case-control nested in the previous cohort will be performed, with the cases being the patients who re-enter and the controls will be chosen according to age, sex, HF etiology, comorbidities and functional status. Sociodemographic, clinical and quality of life variables, empowerment and basal self-efficacy will be collected as predictors of re-entry. Regarding cases and controls, the quality of life in the post-high transition period, empowerment and self-efficacy, caregiver burden, social support, discharge care model, use of health services and adequacy, reconciliation and adherence to medication will be evaluated. Proportional Cox risk models will be developed for the creation of the predictive model, as well as conditioned logistic regression models to identify differences between cases and controls. Expected results: The SNS will be equipped with tools for predicting the risk of useful re-entry for clinicians and managers in order to be able to offer individualised high-care models. The most frequent characteristics of re-entry will be identified and preventable re-entry will be profiled, which will help create specific prevention actions in the future. (English)
12 October 2021
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Galdakao
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Identifiers
PI15_01343
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