Nurse safety outcomes: old problem, new solution - the differentiating roles of nurses' psychological capital and managerial support.

AIM: The aim of this study was to examine the impacts of nurses' psychological capital and managerial support, plus specific safety interventions (managerial safety priorities, safety training satisfaction), on nurses' in-role safety performance. BACKGROUND: Most hospitals in industrialized countries have adopted selective (often the least costly) aspects of safety, usually related to safety policies. However, patient safety remains a challenge in many countries. Research shows that training can be used to upskill employees in psychological capital, with statistically significant organizational and employee benefits, but this area is under-researched in nursing. DESIGN: Data were collected using a survey-based, self-report strategy. The emerging patterns of data were then compared with the findings of previous research. METHODS: Quantitative survey data were collected during 2014 from 242 nurses working in six Australian hospitals. Two models were tested and analysed using covariance-based Structural Equation Modelling. RESULTS: Psychological capital and safety training satisfaction were important predictors of nurses' in-role safety performance and as predictors of nurses' perceptions of whether management implements what it espouses about safety ('managerial safety priorities'). Managerial support accounted for just under a third of psychological capital and together, psychological capital and managerial support, plus satisfaction with safety training, were important to nurses' perceptions of in-role safety performance. CONCLUSION: Organizations are likely to benefit from upskilling nurses and their managers to increase nurses' psychological capital and managerial support, which then will enhance nurses' satisfaction with training and in-role safety performance perceptions.

Examining the antecedents of engaged nurses in Italy: perceived organisational support (POS); satisfaction with training and development; discretionary power.

AIM: This paper used Social Exchange Theory to empirically examine whether perceived organisational support, satisfaction with training and development and perception of discretionary power are antecedents of engagement for registered nurses working in Italian public and private hospitals (n = 827). BACKGROUND: According to Social Exchange Theory, effective workplace relationships support employees and encourage nurses to use training to enhance their workplace outcomes. METHOD: This research used a cross-sectional design. Data were collected from registered nurses working in six Italian hospitals using a survey-based, self-report strategy. RESULT: Regression analysis found that the variance of process-oriented supervision accounted for 6.9% of Italian registered nurse's perception of engagement, training and development accounted for 26.8% and discretionary power accounted for 2.1%. CONCLUSION: Workplace relationships enhance autonomy and engagement. Effective workplace relationship impacts positively on nurses' outcome. IMPLICATIONS FOR NURSING MANAGEMENT: This paper confirms the relevance of training to enhance engagement of nurses. It also confirms the importance of workplace relationships in enhancing autonomy and engagement. Previous research has identified the importance of nurses' autonomy in an environment where there are shortages of nurses. This study confirms a similar situation for Italian nurses. The findings underline the relevance of investments in continuous professional development to enhance nurses' engagement in private and public health-care settings.

An Analysis of the Number of Medical Malpractice Claims and Their Amounts.

Starting from an extensive database, pooling 9 years of data from the top three insurance brokers in Italy, and containing 38125 reported claims due to alleged cases of medical malpractice, we use an inhomogeneous Poisson process to model the number of medical malpractice claims in Italy. The intensity of the process is allowed to vary over time, and it depends on a set of covariates, like the size of the hospital, the medical department and the complexity of the medical operations performed. We choose the combination medical department by hospital as the unit of analysis. Together with the number of claims, we also model the associated amounts paid by insurance companies, using a two-stage regression model. In particular, we use logistic regression for the probability that a claim is closed with a zero payment, whereas, conditionally on the fact that an amount is strictly positive, we make use of lognormal regression to model it as a function of several covariates. The model produces estimates and forecasts that are relevant to both insurance companies and hospitals, for quality assurance, service improvement and cost reduction.