Hierarchical analysis of factors associated with hospital readmissions for coronary heart disease: A case–control study

• Published in: Journal of clinical nursing Vol. 29; no. 13-14; pp. 2329 - 2337
• Main Authors: Albuquerque, Nila Larisse Silva, Araujo, Thelma Leite, Oliveira Lopes, Marcos Venicios, Moreira, Thereza Maria Magalhães
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01-07-2020
• Subjects: acute coronary syndrome; Acute coronary syndromes; Cardiovascular disease; case–control studies; Heart attacks; hospital readmission; Hospitalization; Hospitals; medication adherence; myocardial infarction; Nursing; Patient admissions; Patient compliance; regression analysis; risk factors; Variables; cardiovascular disease; hospital readmission; risk factors; acute coronary syndrome; myocardial infarction; regression analysis; medication adherence; case-control studies
• ISSN: 0962-1067; 1365-2702
• DOI: 10.1111/jocn.15244

Aims and objectives
To analyse, hierarchically, factors associated with hospital readmissions for acute coronary syndrome.
Background
Hospital readmissions have risen, especially in patients with multiple comorbidities, which are most often chronic. The leading causes of hospital readmission include acute coronary syndrome, which is costly and often preventable. Determining clinical and nonclinical variables that increase the chances of readmission is important to assess and evaluate patients hospitalised for coronary heart diseases.
Design
A case–control study whose dependent variable was hospital readmission for acute coronary syndrome.
Methods
The study included 277 inpatients, of whom 132 were in their first hospitalisation and 145 had already been hospitalised for acute coronary syndrome. The independent variables for this hierarchical model were sociodemographic conditions, life habits, access to health services and physical health measures. Data were obtained by interviews, anthropometric measurements and patient records. Logistic regression analysis was performed using the stepwise technique, with Microsoft Excel and R version 3.2.3. The research was reported via strengthening the reporting of observational studies in epidemiology (STROBE).
Results
In the final hierarchical logistic model, the following risk factors were associated with readmission for acute coronary syndrome: inadequate drug therapy adherence, stress, history of smoking for 30 years or more, and the lack of use of primary healthcare services.
Conclusions
Clinical and nonclinical variables are related to hospital readmission for acute coronary syndrome and can increase the chance of readmission by up to six times.
Relevance to clinical practice
The predictive model can be used to avoid readmission for acute coronary syndrome, and it represents an advance in the prediction of the occurrence of the outcome. This implies the need for a reorientation of the network for postdischarge care in the first hospitalisation for acute coronary syndrome.