[Socio-demographic determinants of the risk of inappropriate hospital use]

Ann Ig. 2007 Jul-Aug;19(4):369-80.
[Article in Italian]

Abstract

The aim of the study was to investigate the association between socio-demographic variables and "at high risk of inappropriateness" of hospital admissions. We used hospital admissions data of Local Health Unit (LHU) Rome H (year 2004). We investigated the relationship between socio-demographic variables (sex, age, job activity, marital status, nationality, place of residence, educational level) and a high risk of inappropriate hospital stay. We computed univariate and multivariate analysis using chi2 test and logistic regression model. Out of 32,233 hospital admissions, 4685 (14.5%) resulted at high risk of inappropriateness. The following variables were associated with high risk of inappropriateness: age (for patients aged 0-15 and 46-65 OR: 1.83 (95% C.I.: 1.57-2.13) and 1.56 (95% C.I.: 1.42-1.72) respectively); job activity (for employed OR: 1.98 (95% C.I.: 1.81-2.17), for students OR: 1.34 (95% C.I.: 1.16-155)); marital status (for unmarried OR: 1.37 (95% C.I.: 1.23-1.51)); place of residence (for patients belonging to LHU Rome H OR:1.09 (95% C.I.: 1.02-1.78)); nationality (for foreign nationals OR: 0.71 (95% C.I.: 0.58-0.87)); educational level (for high school degree and graduated people OR: 0.89 (95% C.I.: 0.81-0.98)). Our study demonstrates that socio-demographic variables are related to the high risk of inappropriate hospital admissions. We believe that these variables could be considered as potential factors to modulate the offer of health services.

Publication types

  • English Abstract

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Child
  • Child, Preschool
  • Educational Status
  • Female
  • Health Services Misuse / statistics & numerical data*
  • Hospital Units*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • Length of Stay / statistics & numerical data
  • Male
  • Marital Status / statistics & numerical data
  • Medical Records
  • Middle Aged
  • Patient Admission / statistics & numerical data
  • Retrospective Studies
  • Rome
  • Socioeconomic Factors
  • Students / statistics & numerical data