[Factors associated with the incidence of hospital readmission]. 1997

J Fernández Gracia, and M A Martínez González, and J García Rodríguez, and A Bueno Cavanillas, and P Lardelli Claret, and M García Martín
Service de Medicina Preventiva, Hospital Universitario de Granada.

BACKGROUND To identify factors associated with hospital readmission, especially those potentially avoidable. This information could be useful to reduce the incidence of hospital readmissions. METHODS A paired (1:1) case-control study nested into the cohort of first admissions at the Granada University Hospital, Spain, in 1990. All patients readmitted at the hospital within 3 years after release from the index-admission by the same diagnostic or complications of it comprised the case group. For each case, a control patient was matched for both primary diagnosis on admission and index-admission date. Information on risk factors associated with hospital readmission was obtained retrospectively from medical records. The relation between these risk factors and readmission was estimated from odds ratio both crude and adjusted using conditional logistic regression analysis. For the readmitted subsample, multiple linear regression models were applied to identify factors associated to the length of time between the index episode and the first readmission. RESULTS Variables with consistent positive associations with readmission include male sex (odds ratio = 2.86, 95% confidence interval = 1.37-5.88), widowed or single status (2.66, 10.7-6.59) and severity at index admission (3.20, 1.57-6.51). Factors related to quality of health care did not influence readmission risk. CONCLUSIONS Factors depending of the patient seem to be the most important variables associated to the incidence of hospital readmission.

UI MeSH Term Description Entries
D008297 Male Males
D010359 Patient Readmission Subsequent admissions of a patient to a hospital or other health care institution for treatment. Hospital Readmission,Rehospitalization,Unplanned Hospital Readmissions,Unplanned Readmission,30 Day Readmission,Hospital Readmissions,Readmission, Hospital,Readmissions, Hospital,Thirty Day Readmission,30 Day Readmissions,Hospital Readmission, Unplanned,Hospital Readmissions, Unplanned,Readmission, Patient,Readmission, Thirty Day,Readmission, Unplanned,Rehospitalizations,Thirty Day Readmissions,Unplanned Hospital Readmission,Unplanned Readmissions
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012307 Risk Factors An aspect of personal behavior or lifestyle, environmental exposure, inborn or inherited characteristic, which, based on epidemiological evidence, is known to be associated with a health-related condition considered important to prevent. Health Correlates,Risk Factor Scores,Risk Scores,Social Risk Factors,Population at Risk,Populations at Risk,Correlates, Health,Factor, Risk,Factor, Social Risk,Factors, Social Risk,Risk Factor,Risk Factor Score,Risk Factor, Social,Risk Factors, Social,Risk Score,Score, Risk,Score, Risk Factor,Social Risk Factor
D013030 Spain Country located between France on the northeast and Portugal on the west and bordered by the Atlantic Ocean and the Mediterranean Sea. The capital is Madrid. Balearic Islands,Canary Islands
D016014 Linear Models Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression. Linear Regression,Log-Linear Models,Models, Linear,Linear Model,Linear Regressions,Log Linear Models,Log-Linear Model,Model, Linear,Model, Log-Linear,Models, Log-Linear,Regression, Linear,Regressions, Linear
D016015 Logistic Models Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor. Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic
D016022 Case-Control Studies Comparisons that start with the identification of persons with the disease or outcome of interest and a control (comparison, referent) group without the disease or outcome of interest. The relationship of an attribute is examined by comparing both groups with regard to the frequency or levels of outcome over time. Case-Base Studies,Case-Comparison Studies,Case-Referent Studies,Matched Case-Control Studies,Nested Case-Control Studies,Case Control Studies,Case-Compeer Studies,Case-Referrent Studies,Case Base Studies,Case Comparison Studies,Case Control Study,Case Referent Studies,Case Referrent Studies,Case-Comparison Study,Case-Control Studies, Matched,Case-Control Studies, Nested,Case-Control Study,Case-Control Study, Matched,Case-Control Study, Nested,Case-Referent Study,Case-Referrent Study,Matched Case Control Studies,Matched Case-Control Study,Nested Case Control Studies,Nested Case-Control Study,Studies, Case Control,Studies, Case-Base,Studies, Case-Comparison,Studies, Case-Compeer,Studies, Case-Control,Studies, Case-Referent,Studies, Case-Referrent,Studies, Matched Case-Control,Studies, Nested Case-Control,Study, Case Control,Study, Case-Comparison,Study, Case-Control,Study, Case-Referent,Study, Case-Referrent,Study, Matched Case-Control,Study, Nested Case-Control
D018806 APACHE An acronym for Acute Physiology and Chronic Health Evaluation, a scoring system using routinely collected data and providing an accurate, objective description for a broad range of intensive care unit admissions, measuring severity of illness in critically ill patients. Acute Physiology and Chronic Health Evaluation,APACHE I,APACHE II,APACHE III

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