Hospital Readmission in Stroke Survivors in Social Vulnerability: Predictive Modeling with Machine Learning from the Perspective of the Chronic Conditions Care Model

Erisonval Saraiva da Silva (), Thereza Maria Magalhães Moreira, Ana Célia Caetano de Souza, Ana Maria Ribeiro dos Santos, Ana Roberta Vilarouca da Silva, Lariza Martins Falcão, Livia Carvalho Pereira, Jardeliny Corrêa da Penha, Manoel Borges da Silva Junior, Francisco Lucas de Lima Fontes, Isaias Wilmer Dueñas Sayaverde, Maria del Pilar Serrano Gallardo and José Wicto Pereira Borges
Additional contact information
Erisonval Saraiva da Silva: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Thereza Maria Magalhães Moreira: Postgraduate Program in Clinical Care in Nursing, State University of Ceará (UECE), Fortaleza 60.714-903, CE, Brazil
Ana Célia Caetano de Souza: Walter Cantídio University Hospital, Federal University of Ceará (UFC), Fortaleza 60.020-181, CE, Brazil
Ana Maria Ribeiro dos Santos: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Ana Roberta Vilarouca da Silva: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Lariza Martins Falcão: Nursing Department, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Livia Carvalho Pereira: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Jardeliny Corrêa da Penha: Postgraduate Program in Health and Community, Federal University of Piauí (UFPI), Teresina 64.000-020, PI, Brazil
Manoel Borges da Silva Junior: Postgraduate Program in Health and Community, Federal University of Piauí (UFPI), Teresina 64.000-020, PI, Brazil
Francisco Lucas de Lima Fontes: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil
Isaias Wilmer Dueñas Sayaverde: School of Nursing, National Autonomous University of Chota (UNACH), Chota-Cajamarca 06421, Peru
Maria del Pilar Serrano Gallardo: Nursing Department, Faculty of Medicine, Universidad Autónoma de Madrid, 28040 Madrid, Spain
José Wicto Pereira Borges: Postgraduate Program in Nursing, Federal University of Piauí (UFPI), Teresina 64.049-550, PI, Brazil

IJERPH, 2025, vol. 22, issue 11, 1-17

Abstract: Hospital readmission among stroke survivors is frequent, especially in contexts of social vulnerability, compromising recovery and overburdening health services. This study aimed to develop a predictive model of hospital readmission among socially vulnerable stroke survivors, based on the Chronic Conditions Care Model (CCCM). Machine learning algorithms were applied, specifically decision tree and logistic regression, with data split into training (70% and 80%) and testing (30% and 20%) sets. Analyses were conducted using Python, with accuracy evaluated through ROC curves, AUC, and the confusion matrix in Analyse-it ® , adopting a 5% significance level. The decision tree with an 80/20 partition achieved an accuracy of 92.45%. The variables most associated with readmission were falls, time since the first stroke, presence of a caregiver, and difficulty sleeping. In logistic regression, falls increased the risk by 235%, ischemic stroke by 155%, complications by 153.53%, COVID-19 by 132%, and time since stroke by 11.5% per year. The model proved to be feasible and robust, with the decision tree standing out, highlighting its potential to support preventive strategies and enhance care management.

Keywords: stroke; decision trees; logistic models; chronic disease; healthcare models; social vulnerability; patient readmission (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/22/11/1705/pdf (application/pdf)
https://www.mdpi.com/1660-4601/22/11/1705/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:22:y:2025:i:11:p:1705-:d:1792409

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().