title: Estimating nursing intensity and direct cost using the nurse-patient assignment.
abstract: BACKGROUND
  This study examines the feasibility of using the nurse-patient assignment (NPA) to calculate direct nursing hours and costs for each inpatient-day. The NPA data are collected at every hospital and therefore represent a readily available information source that can establish the intensity and economic value of nursing care at US hospitals.
  
  
  METHODS
  Direct nursing care hours for each patient were collected twice a day using an existing nursing intensity database at a single university hospital between January 2004 and June 2005 for a total of 11,582 patient-days. Nursing intensity was also calculated for each shift using the NPA. Mean unit and hospital nursing hours were calculated and compared with the direct nursing care hours using ordinary least squares regression.
  
  
  RESULTS
  For the day shift, the NPA estimate explained 77.2% (r2 = 0.772) of the variance of patient-level nursing intensity. Unit and hospital mean estimates of nursing intensity had lower r of 0.574 and 0.456, respectively. The night-shift NPA, unit, and hospital r2 estimates were 0.824, 0.633, and 0.579, respectively.
  
  
  CONCLUSIONS
  The use of the NPA can provide a robust and easy method to calculate nursing intensity for individual patients using assignment data available in nearly all care settings. The NPA estimate can be used to allocate direct nursing time and costs for each patient within the hospital billing system and can also be used in pay-for-performance or for benchmarking nursing intensity within and across hospitals.
authors.affiliation: Medical University of South Carolina, College of Nursing, 99 Jonathan Lucas St, Room 527, Charleston, SC 29425, USA. weltonj@musc.edu
authors.forename: John M
authors.initials: JM
authors.lastname: Welton
authors.forename: Laurie
authors.initials: L
authors.lastname: Zone-Smith
authors.forename: Dipankar
authors.initials: D
authors.lastname: Bandyopadhyay
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000704:Analysis of Variance; D003625:Data Collection / Q000379:methods* / Q000592:standards; D004180:Direct Service Costs / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D020380:Needs Assessment / Q000458:organization & administration; D015401:Nursing Administration Research / Q000379:methods* / Q000592:standards; D009741:Nursing Staff, Hospital / Q000193:education / Q000458:organization & administration*; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration*; D040841:Resource Allocation; D012456:Salaries and Fringe Benefits / Q000191:economics; D013022:South Carolina; D013996:Time and Motion Studies; D016526:Workload / Q000145:classification / Q000191:economics*