title: The cost of nurse-sensitive adverse events.
abstract: OBJECTIVE
  The aim of this study was to describe the methodology for nursing leaders to determine the cost of adverse events and effective levels of nurse staffing.
  
  
  BACKGROUND
  The growing transparency of quality and cost outcomes motivates healthcare leaders to optimize the effectiveness of nurse staffing. Most hospitals have robust cost accounting systems that provide actual patient-level direct costs. These systems allow an analysis of the cost consumed by patients during a hospital stay. By knowing the cost of complications, leaders have the ability to justify the cost of improved staffing when quality evidence shows that higher nurse staffing improves quality.
  
  
  METHODS
  An analysis was performed on financial and clinical data from hospital databases of 3,200 inpatients. The purpose was to establish a methodology to determine actual cost per case. Three diagnosis-related groups were the focus of the analysis. Five adverse events were analyzed along with the costs.
  
  
  RESULTS
  A regression analysis reported that the actual direct cost of an adverse event was dollars 1,029 per case in the congestive heart failure cases and dollars 903 in the surgical cases. There was a significant increase in the cost per case in medical patients with urinary tract infection and pressure ulcers and in surgical patients with urinary tract infection and pneumonia. The odds of pneumonia occurring in surgical patients decreased with additional registered nurse hours per patient day.
  
  
  CONCLUSIONS
  Hospital cost accounting systems are useful in determining the cost of adverse events and can aid in decision making about nurse staffing. Adverse events add costs to patient care and should be measured at the unit level to adjust staffing to reduce adverse events and avoid costs.
authors.affiliation: Nursing Office, Porter Adventist Hospital, Denver, Colorado 80210, USA. sharonpappas@centura.org
authors.forename: Sharon Holcombe
authors.initials: SH
authors.lastname: Pappas
mesh_terms: D000058:Accidental Falls / Q000191:economics; D000066:Accounting / Q000458:organization & administration; D000328:Adult; D000704:Analysis of Variance; D003362:Cost-Benefit Analysis; D003428:Cross Infection / Q000191:economics; D005260:Female; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D019300:Medical Errors / Q000191:economics* / Q000451:nursing; D008875:Middle Aged; D015401:Nursing Administration Research; D009741:Nursing Staff, Hospital / Q000193:education / Q000458:organization & administration*; D017063:Outcome Assessment, Health Care; D010561:Personnel Staffing and Scheduling / Q000191:economics*; D003668:Pressure Ulcer / Q000191:economics; D019984:Quality Indicators, Health Care / Q000191:economics*; D011787:Quality of Health Care / Q000191:economics*; D012044:Regression Analysis; D012189:Retrospective Studies; D020379:Risk Adjustment; D012680:Sensitivity and Specificity; D016526:Workload / Q000191:economics