title: Examining the value of inpatient nurse staffing: an assessment of quality and patient care costs.
abstract: BACKGROUND
  Inpatient quality deficits have important implications for the health and well-being of patients. They also have important financial implications for payers and hospitals by leading to longer lengths of stay and higher intensity of treatment. Many of these costly quality deficits are particularly sensitive to nursing care.
  
  
  OBJECTIVE
  To assess the effect of nurse staffing on quality of care and inpatient care costs.
  
  
  METHODS
  Longitudinal analysis using hospital nurse staffing data and the Healthcare Cost and Utilization Project State Inpatient Databases from 2008 through 2011.
  
  
  METHODS
  Hospital discharges from California, Nevada, and Maryland (n=18,474,860).
  
  
  METHODS
  A longitudinal, hospital-fixed effect model was estimated to assess the effect of nurse staffing levels and skill mix on patient care costs, length of stay, and adverse events, adjusting for patient clinical and demographic characteristics.
  
  
  RESULTS
  Increases in nurse staffing levels were associated with reductions in nursing-sensitive adverse events and length of stay, but did not lead to increases in patient care costs. Changing skill mix by increasing the number of registered nurses, as a proportion of licensed nursing staff, led to reductions in costs.
  
  
  CONCLUSIONS
  The study findings provide support for the value of inpatient nurse staffing as it contributes to improvements in inpatient care; increases in staff number and skill mix can lead to improved quality and reduced length of stay at no additional cost.
authors.affiliation: *RAND Corporation, Pittsburgh, PA †Formerly of RAND Corporation, Boston, MA ‡Truven Health Analytics, Santa Barbara, CA §Agency for Healthcare Research and Quality (AHRQ) Center for Delivery, Organization, and Markets (CDOM), Rockville, MD ∥RAND Corporation, Santa Monica, CA ¶Truven Health Analytics, Ann Arbor, MI.
authors.forename: Grant R
authors.initials: GR
authors.lastname: Martsolf
authors.forename: David
authors.initials: D
authors.lastname: Auerbach
authors.forename: Richele
authors.initials: R
authors.lastname: Benevent
authors.forename: Carol
authors.initials: C
authors.lastname: Stocks
authors.forename: H Joanna
authors.initials: HJ
authors.lastname: Jiang
authors.forename: Marjorie L
authors.initials: ML
authors.lastname: Pearson
authors.forename: Emily D
authors.initials: ED
authors.lastname: Ehrlich
authors.forename: Teresa B
authors.initials: TB
authors.lastname: Gibson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002140:California / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D005260:Female; D017721:Hospital Costs / Q000458:organization & administration* / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data; D008297:Male; D008396:Maryland / Q000453:epidemiology; D008875:Middle Aged; D009505:Nevada / Q000453:epidemiology; D009741:Nursing Staff, Hospital / Q000191:economics / Q000458:organization & administration* / Q000592:standards; D061214:Patient Safety / Q000191:economics / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D055815:Young Adult