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Modeling hospital-acquired pressure ulcer prevalence on medical-surgical units: nurse workload, expertise, and clinical processes of care.


ABSTRACT: This study modeled the predictive power of unit/patient characteristics, nurse workload, nurse expertise, and hospital-acquired pressure ulcer (HAPU) preventive clinical processes of care on unit-level prevalence of HAPUs.Seven hundred and eighty-nine medical-surgical units (215 hospitals) in 2009.Using unit-level data, HAPUs were modeled with Poisson regression with zero-inflation (due to low prevalence of HAPUs) with significant covariates as predictors.Hospitals submitted data on NQF endorsed ongoing performance measures to CALNOC registry.Fewer HAPUs were predicted by a combination of unit/patient characteristics (shorter length of stay, fewer patients at-risk, fewer male patients), RN workload (more hours of care, greater patient [bed] turnover), RN expertise (more years of experience, fewer contract staff hours), and processes of care (more risk assessment completed).Unit/patient characteristics were potent HAPU predictors yet generally are not modifiable. RN workload, nurse expertise, and processes of care (risk assessment/interventions) are significant predictors that can be addressed to reduce HAPU. Support strategies may be needed for units where experienced full-time nurses are not available for HAPU prevention. Further research is warranted to test these finding in the context of higher HAPU prevalence.

SUBMITTER: Aydin C 

PROVIDER: S-EPMC4369213 | biostudies-other | 2015 Apr

REPOSITORIES: biostudies-other

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Modeling hospital-acquired pressure ulcer prevalence on medical-surgical units: nurse workload, expertise, and clinical processes of care.

Aydin Carolyn C   Donaldson Nancy N   Stotts Nancy A NA   Fridman Moshe M   Brown Diane Storer DS  

Health services research 20141007 2


<h4>Objective</h4>This study modeled the predictive power of unit/patient characteristics, nurse workload, nurse expertise, and hospital-acquired pressure ulcer (HAPU) preventive clinical processes of care on unit-level prevalence of HAPUs.<h4>Data sources</h4>Seven hundred and eighty-nine medical-surgical units (215 hospitals) in 2009.<h4>Study design</h4>Using unit-level data, HAPUs were modeled with Poisson regression with zero-inflation (due to low prevalence of HAPUs) with significant covar  ...[more]

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