title: The connection between personnel resources with work loading and patient satisfaction on in-patient wards.
abstract: OBJECTIVE
  The aim of the study is to describe the connection between the burden of nurses' work experience and patient dissatisfaction using electronic indicators available in databases.
  
  
  BACKGROUND
  The hospitals in this study have a lot of information stored in electronic databases, but the data is stored in different databases and there are no straight connections between them.
  
  
  METHODS
  This study was retrospective. Inpatient rates, workload statistics, patient classification, patient satisfaction and financial statistics were collected on 39 hospital wards from electronic databases. The data were analysed statistically.
  
  
  RESULTS
  The results showed that the higher care intensity index and number of gross treatment days are, the greater was the burden on nurses. The burden was smaller on those wards using a named nurse system.
  
  
  CONCLUSIONS
  Nurses' workload varies according to the condition of patients and patient flow. There is a connection between high workload and patient dissatisfaction. Nurse Managers should easily be able to use significant indicators.
  
  
  CONCLUSIONS
  Nursing management must have tools that are easy to use in every day workload measurement, burden adjustment and personnel planning in the long run. This article presents patient classification and the number of beds used including daily change percentage of wards as instruments for nursing management.
authors.affiliation: Pirkanmaa Hospital District, Tampere University Hospital, Tampere, Finland. pirjo.aalto@pshp.fi
authors.forename: Pirjo
authors.initials: P
authors.lastname: Aalto
authors.forename: Liisa
authors.initials: L
authors.lastname: Karhe
authors.forename: Anna-Maija
authors.initials: AM
authors.lastname: Koivisto
authors.forename: Maritta
authors.initials: M
authors.lastname: Välimäki
mesh_terms: D000328:Adult; D002983:Clinical Competence / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009726:Nurses / Q000706:statistics & numerical data*; D009741:Nursing Staff, Hospital; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D010563:Personnel Turnover / Q000706:statistics & numerical data; D011594:Psychometrics; D011787:Quality of Health Care / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012189:Retrospective Studies; D013223:Statistics as Topic; D016526:Workload / Q000706:statistics & numerical data*