title: Improving hospital patient falls: leveraging staffing characteristics and processes of care.
abstract: OBJECTIVE
  Predictive models for falls, injury falls, and restraint prevalence were explored within nursing unit structures and processes of care.
  
  
  BACKGROUND
  The patient care team is responsible for patient safety, and improving practice models may prevent injuries and improve patient safety.
  
  
  METHODS
  Using unit-level self-reported data from 215 hospitals, falls, injury falls, and restraint prevalence were modeled with significant covariates as predictors.
  
  
  RESULTS
  Fewer falls/injury falls were predicted by populations with fewer frail and at-risk patients, more unlicensed care hours, and prevention protocol implementation, but not staffing per se, restraint use, or RN expertise. Lower restraint use was predicted by fewer frail patients, shorter length of stay, more RN hours, more certified RNs, and implementation of fall prevention protocols.
  
  
  CONCLUSIONS
  In the presence of risk, patient injuries and safety were improved by optimizing staffing skill mix and use of prevention protocols.
authors.affiliation: Author Affiliations: Research Scientist (Drs Aydin and Aronow), Cedars-Sinai Medical Center and Burns & Allen Research Institute; and Director and Coinvestigator (Dr Aydin), Collaborative Alliance for Nursing Outcomes (CALNOC) Data Management Services, Los Angeles, California; Senior Scientist, CALNOC (Drs Donaldson and Brown), San Ramon, California; Clinical Professor (Dr Donaldson), UCSF School of Nursing, San Francisco, California; CALNOC Statistician (Dr Fridman), AMF Consulting, Inc, Los Angeles, California; and Executive Director (Dr Brown), Cost Improvement Strategy, Kaiser Permanente Northern California Region, Oakland, California.
authors.forename: Carolyn
authors.initials: C
authors.lastname: Aydin
authors.forename: Nancy
authors.initials: N
authors.lastname: Donaldson
authors.forename: Harriet Udin
authors.initials: HU
authors.lastname: Aronow
authors.forename: Moshe
authors.initials: M
authors.lastname: Fridman
authors.forename: Diane Storer
authors.initials: DS
authors.lastname: Brown
mesh_terms: D000056:Accident Prevention / Q000379:methods* / Q000706:statistics & numerical data; D000058:Accidental Falls / Q000517:prevention & control* / Q000706:statistics & numerical data; D002140:California; D006801:Humans; D015999:Multivariate Analysis; D009741:Nursing Staff, Hospital / Q000600:supply & distribution*; D009922:Oregon; D061214:Patient Safety; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration* / Q000706:statistics & numerical data; D012149:Restraint, Physical / Q000706:statistics & numerical data; D014861:Washington