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Improving Hospital Patient Falls: Leveraging Staffing Characteristics and Processes of Care

Aydin, Carolyn PhD; Donaldson, Nancy PhD, RN, FAAN; Aronow, Harriet Udin PhD; Fridman, Moshe PhD; Brown, Diane Storer PhD, RN, FNAHQ, FAAN

JONA: The Journal of Nursing Administration: May 2015 - Volume 45 - Issue 5 - p 254–262
doi: 10.1097/NNA.0000000000000195

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.

CONCLUSION: In the presence of risk, patient injuries and safety were improved by optimizing staffing skill mix and use of prevention protocols.

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.

This research was funded by the Robert Wood Johnson Foundation INQRI.

The authors declare no conflicts of interest.

Correspondence: Dr Aydin, CALNOC Data Management Services, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA 90048 (

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