title: Preventable inpatient time: adequacy of electronic patient information systems.
abstract: OBJECTIVE
  This study assessed hospital electronic patient information systems (EPIS) for inclusion of variables associated with avoidable and extended hospitalization (preventable inpatient time).
  
  
  METHODS
  We searched MEDLINE and HealthSTAR databases to identify predictors of preventable inpatient time. We then audited the admissions process and the handwritten medical record at 1 hospital, and the EPIS at all hospitals, affiliated with the Yale University School of Medicine for inclusion of the predictors.
  
  
  RESULTS
  Whereas the written medical record included all 58 predictors, the EPIS of the 10 hospitals surveyed included an average of only 38% of the predictors.
  
  
  CONCLUSIONS
  The conventional approach to information gathering during hospital admission is highly inefficient. Revising EPIS to include predictors of preventable inpatient time could enhance efficiency and quality, while reducing costs, of hospital care.
authors.affiliation: Department of Preventive Medicine, Griffin Hospital, Derby, Conn. 06418, USA. katzdl@pol.net
authors.forename: D L
authors.initials: DL
authors.lastname: Katz
authors.forename: R
authors.initials: R
authors.lastname: Mazhari
authors.forename: R
authors.initials: R
authors.lastname: Kalus
authors.forename: H
authors.initials: H
authors.lastname: Nawaz
mesh_terms: D003237:Connecticut; D003625:Data Collection / Q000379:methods*; D019538:Health Care Surveys; D006302:Health Services Research / Q000706:statistics & numerical data*; D006751:Hospital Information Systems; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D010343:Patient Admission