title: Hospital readmission prevalence and analysis of those potentially avoidable in southern Italy.
abstract: BACKGROUND
  One quality indicator of hospital care, which can be used to judge the process of care, is the prevalence of hospital readmission because it reflects the impact of hospital care on the patient's condition after discharge. The purposes of the study were to measure the prevalence of hospital readmissions, to identify possible factors that influence such readmission and to measure the prevalence of readmissions potentially avoidable in Italy.
  
  
  METHODS
  A sample of 2289 medical records of patients aged 18 and over admitted for medical or surgical illness at one 502-bed community non-teaching hospital were randomly selected.
  
  
  RESULTS
  A total of 2252 patients were included in the final analysis, equaling a response rate of 98.4%. The overall hospital readmission prevalence within 30 days of discharge was 10.2%. Multivariate logistic regression analysis revealed that the proportion of patients readmitted within 30 days of discharge significantly increased regardless of Charlson et al. comorbidity score, among unemployed or retired patients, and in patients in general surgery. A total of 43.7% hospital readmissions were judged to be potentially avoidable. Multivariate logistic regression analysis showed that potentially avoidable readmissions were significantly higher in general surgery, in patients referred to hospital by an emergency department physician, and in those with a shortened time between discharge and readmission.
  
  
  CONCLUSIONS
  Additional research on intervention or bundle of interventions applicable to acute inpatient populations that aim to reduce potentially avoidable readmissions is strongly needed, and health care providers are urged to implement evidence-based programs for more cost-effective delivery of health care.
authors.affiliation: Department of Health Sciences, Medical School, University of Catanzaro Magna Græcia, Catanzaro, Italy.
authors.forename: Aida
authors.initials: A
authors.lastname: Bianco
authors.forename: Antonio
authors.initials: A
authors.lastname: Molè
authors.forename: Carmelo G A
authors.initials: CG
authors.lastname: Nobile
authors.forename: Gabriella
authors.initials: G
authors.lastname: Di Giuseppe
authors.forename: Claudia
authors.initials: C
authors.lastname: Pileggi
authors.forename: Italo F
authors.initials: IF
authors.lastname: Angelillo
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003362:Cost-Benefit Analysis; D003430:Cross-Sectional Studies; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D007297:Inpatients; D007558:Italy; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010359:Patient Readmission; D015995:Prevalence; D011787:Quality of Health Care; D012044:Regression Analysis