“…In other studies readmission was mostly related to age, comorbidities and the type of chronic illnesses [5,6,8,9], the role of age being explained by the fact that older people have more chronic diseases and a lower mean functional status [5].…”
Background: The aim of this study was to identify which factors were associated with a risk of hospital readmission within 3 months after discharge of a sample of elderly patients admitted to internal medicine and geriatric wards. Methods: Of the 1178 patients aged 65 years or more and discharged from one of the 66 wards of the 'Registry Politerapie SIMI (REPOSI)' during 2010, 766 were followed up by phone interview 3 months after discharge and were included in this analysis. Univariate and multivariate logistic regression models were used to evaluate the association of several variables with rehospitalization within 3 months from discharge. Results: Nineteen percent of patients were readmitted at least once within 3 months after discharge. By univariate analysis in-hospital clinical adverse events (AEs), a previous hospital admission, number of diagnoses and drugs, comorbidity and severity index (according to Cumulative Illness Rating Scale-CIRS), vascular and liver diseases with a level of impairment at discharge of 3 or more at CIRS were significantly associated with risk of readmission. Multivariate logistic regression analysis showed that only AEs during hospitalization, previous hospital admission, and vascular and liver diseases were significantly associated with the likelihood of readmission.Conclusions: The results demonstrate the need for increased medical attention towards elderly patients discharged from hospital with characteristics such as AEs during the hospitalization, previous admission, vascular and liver diseases.
“…In other studies readmission was mostly related to age, comorbidities and the type of chronic illnesses [5,6,8,9], the role of age being explained by the fact that older people have more chronic diseases and a lower mean functional status [5].…”
Background: The aim of this study was to identify which factors were associated with a risk of hospital readmission within 3 months after discharge of a sample of elderly patients admitted to internal medicine and geriatric wards. Methods: Of the 1178 patients aged 65 years or more and discharged from one of the 66 wards of the 'Registry Politerapie SIMI (REPOSI)' during 2010, 766 were followed up by phone interview 3 months after discharge and were included in this analysis. Univariate and multivariate logistic regression models were used to evaluate the association of several variables with rehospitalization within 3 months from discharge. Results: Nineteen percent of patients were readmitted at least once within 3 months after discharge. By univariate analysis in-hospital clinical adverse events (AEs), a previous hospital admission, number of diagnoses and drugs, comorbidity and severity index (according to Cumulative Illness Rating Scale-CIRS), vascular and liver diseases with a level of impairment at discharge of 3 or more at CIRS were significantly associated with risk of readmission. Multivariate logistic regression analysis showed that only AEs during hospitalization, previous hospital admission, and vascular and liver diseases were significantly associated with the likelihood of readmission.Conclusions: The results demonstrate the need for increased medical attention towards elderly patients discharged from hospital with characteristics such as AEs during the hospitalization, previous admission, vascular and liver diseases.
“…Ce mode de recueil est fiable pour une maladie donnée à l'échelle d'un établissement de santé avec des rapports de vraisemblance positifs qui s'échelonnent de 8 à 308. L'originalité du projet PATH a été de restreindre l'analyse du taux de réadmissions à une maladie traceuse pour minimiser la variabilité d'un taux constitué de mesures de plusieurs maladies [12][13][14][15][16][17]. L'information recueillie est plus spécifique et plus adaptée à l'analyse des processus d'une prise en charge clairement identifiée.…”
Section: Discussionunclassified
“…La plupart des réadmis-sions évitables surviennent dans les 30 jours après la date de sortie du séjour traceur [9][10][11]. Leur nombre est corrélé à l'âge et aux comorbidités du patient, à la durée du séjour traceur, et au type de maladie traceuse [12][13][14][15][16][17].…”
“…Some authors consider it to be subsequent admissions in which the main diagnosis is the same or directly related to the initial admission, 14 whereas others consider them to be admissions to the same service, irrespective of the readmission diagnosis. 28 There is also a divergence of defi nitions related to the interval of time between admissions, varying between 14 days to one year after discharge. 2,4,28 Few studies relate the incidence of adverse events related to medication during the previous admission with hospital readmissions.…”
mentioning
confidence: 99%
“…28 There is also a divergence of defi nitions related to the interval of time between admissions, varying between 14 days to one year after discharge. 2,4,28 Few studies relate the incidence of adverse events related to medication during the previous admission with hospital readmissions. 15,24 We found only one study on associations with drug interactions.…”
OBJECTIVE:To examine the relationship between potential drug interactions and hospital readmissions.
METHODS:Retrospective study with 1,487 adult patients (> 18 years old) admitted to a general hospital in the city of Vitória da Conquista, Northeastern Brazil, from January to December 2007. Data were collected from Hospital Admission Authorization (AIH) forms in the Brazilian National Health System Hospital Database (SIH/SUS). Probabilistic linkage was used to combine multiple AIH forms from the same admission into a single record and to identify readmissions. Information on prescriptions was manually added to the SIH/ SUS records. Logistic regression was used to quantitatively assess the impact of drug interactions on hospital readmissions. Cox regression was performed to test the impact of this variable on time to fi rst readmission.
RESULTS:A total of 99 readmissions (7% of all patients) were identifi ed. Potential drug interactions were found in 35% of all prescriptions evaluated. Patients with potential drug interactions in a prior admission were more likely to be readmitted. The adjusted odds ratio indicated a 2.4-fold increase in odds of being readmitted; and the adjusted hazard ratio showed that this risk was increased by 79% in patients with potential drug interactions (p < 0.01).
CONCLUSIONS:The study results suggest an association between prior drug interactions and increased risk of readmission. Health professionals should be aware of potential hazard of certain drug combinations and closely monitor high-risk patients such as elderly patients and those with renal impairment.
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