Longitudinal evaluation of an electronic audit and feedback system for patient safety in a large tertiary hospital setting.

Objective: This study sought to assess the impact of a novel electronic audit and feedback (e-A&F) system on patient outcomes. Methods: The e-A&F intervention was implemented in a tertiary hospital and involved near real-time feedback via web-based dashboards. We used a segmented regression analysis of interrupted time series. We modelled the pre-post change in outcomes for the (1) announcement of this priority list, and (2) implementation of the e-A&F intervention to have affected patient outcomes. Results: Across the study period there were 222,792 episodes of inpatient care, of which 13,904 episodes were found to contain one or more HACs, a risk of 6.24%. From the point of the first intervention until the end of the study the overall risk of a HAC reduced from 8.57% to 4.12% - a 51.93% reduction. Of this reduction the proportion attributed to each of these interventions was found to be 29.99% for the announcement of the priority list and 21.93% for the implementation of the e-A&F intervention. Discussion: Our findings lend evidence to a mechanism that the announcement of a measurement framework, at a national level, can lead to local strategies, such as e-A&F, that lead to significant continued improvements over time.

An evaluation of an electronic audit and feedback system for patient safety in a tertiary hospital setting: A study protocol.

An electronic audit and feedback (e-A&F) system was developed to support healthcare providers' awareness of their own performance, improve delivery of care and ultimately the safety of patients while in hospital. The point-of-care e-A&F system provides healthcare providers, from a 600-bed tertiary hospital in Western Australia, with near real-time feedback via web-based dashboards. The aim of this evaluation is to determine the implications of e-A&F across multiple dimensions and domains of care in a tertiary hospital setting. The study also aims to address the paucity in the literature by validating hypothesised design and implementation mechanisms on its effectiveness. Key datasets to be examined include those related to patient outcomes, staff behaviour and costs. Quantitative methods, such as interrupted time series analysis and multiple logistic regression analysis, amongst other methods, will be employed to achieve these aims.