Arnetz, Judith E.

AbstractThe aim of this study was to identify hospital‐based workplace violence (WPV) risk factors with the Haddon Matrix Model (HMM) to determine its potential utility to conceptualize multiple risks for WPV events. This descriptive study utilized two independent convenience samples Data from behavioral emergencies (2014–2015) for patient violence (N = 192) and from health care staff (N = 380) 12‐month violence survey responses (2015) in a Midwestern academic hospital were analyzed. Logistic regression examined patient features associated with physical violence. Survey questions pertained to employee, environment, and cultural factors associated with WPV; responses were examined with Chi‐square and two‐sample t‐tests. Violence risk factors populated the 4 Haddon Matrix domains at pre‐event time frames as Host (worker)‐age/demographics, Agent (patient)‐age/gender, Physical Environment‐door/window structure, and Social Environment‐worker safety. Risks at event time frames populated for Agent—behavior/delirium, and Physical Environment—event medication/patient identification. The Haddon Matrix identification of hospital violence risks indicates its utility as a comprehensive approach to workplace violence.

BACKGROUND: Health care settings are a primary location for workplace violence that involves clients, but risk factors for behavioral emergencies in medical settings are largely unknown. AIM: This study proposed to identify risk factors for assault and physical aggression among medically hospitalized patients who needed a behavior emergency response team. METHOD: This descriptive study, conducted at a large Midwestern academic medical center, used univariable and multivariable logistic regression to assess relationships between demographic, medical, mental health, and contextual variables with assault and physical aggression. Predictive ability was summarized using area under the receiver operating characteristic curve. RESULTS: Among patients who received a behavior emergency response ( N = 820), 86 (10%) were assaultive. Physical aggression was the most significant predictor of assault. Physical aggression was predicted by older age, male gender, and verbal threats to others. Conversely, internalizing mental health conditions of anxiety, depression, and suicidal ideation were significant for decreased risk of assault and/or physical aggression. Contextual factors, identified as wanting to smoke or leave the hospital, were significantly associated with decreased risk of both assault and physical aggression. CONCLUSION: Health care providers are encouraged to (1) consider the demonstration of physical aggression as a sign to urgently implement precautionary measures for safety, (2) avoid predicting violent situations based on particular medical or mental health conditions alone, and (3) understand that not all disruptive behavior leads to violent situations.