Date of Conferral

2022

Degree

Doctor of Healthcare Administration (D.H.A.)

School

Health Services

Advisor

DR Naser Naser

Abstract

AbstractIdentifying and containing patient falls before they happen, reporting fall occurrence, and analyzing fall causes could increase patient safety to achieve the triple aim of improved quality, reduced cost, and accessibility in healthcare. Patient falls within the medical-surgical population continue to present challenges to patients, families, hospitals, and society, despite the use of fall-related predictive analysis tools. The purpose of this quantitative study was to determine the extent to which the overall score on the Hester Davis Falls Risk Assessment Scale (HDS), comprised of patient-related factors such as medications, volume/electrolyte status, age, last known fall date, mobility, toileting needs, communication/sensory needs, mental status, and behavior variants, predicted the occurrence of patient falls in medical-surgical patients. The study was grounded on the health information technology safety measurement theoretical framework. A quantitative correlational cross-sectional methodology was applied in the study to analyze one year of patient fall data from a safety net hospital in Colorado. The HDS positively predicted (p > .05) patient fallers in the medical-surgical patient population. Patient-related factors (patient medications, volume/electrolyte status, mobility, toileting needs, communication/sensory needs, mental status, and behavior variants) were found to increase the risk of falls. Positive social change could result from the findings of this study, in that findings could contribute to improved quality of patient care and enhanced decision making by healthcare leaders to reduce patient falls. Fall prevention is critical to reduce patient injuries and the cost of care.

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