{Reference Type}: Journal Article
{Title}: Developing a customised set of evidence-based quality indicators for measuring workplace violence towards healthcare workers: a modified Delphi method.
{Author}: Sethi R;Lyver B;Gorla J;Singh B;Hanagan T;Haines J;Toppings M;Schulz-Quach C;
{Journal}: BMJ Open Qual
{Volume}: 13
{Issue}: 3
{Year}: 2024 Jul 4
暂无{DOI}: 10.1136/bmjoq-2024-002855
{Abstract}: <B>BACKGROUND: </B>Workplace violence (WPV) is a complex global challenge in healthcare that can only be addressed through a quality improvement initiative composed of a complex intervention. However, multiple WPV-specific quality indicators are required to effectively monitor WPV and demonstrate an intervention's impact. This study aims to determine a set of quality indicators capable of effectively monitoring WPV in healthcare.<BR><B>METHODS: </B>This study used a modified Delphi process to systematically arrive at an expert consensus on relevant WPV quality indicators at a large, multisite academic health science centre in Toronto, Canada. The expert panel consisted of 30 stakeholders from the University Health Network (UHN) and its affiliates. Relevant literature-based quality indicators which had been identified through a rapid review were categorised according to the Donabedian model and presented to experts for two consecutive Delphi rounds.<BR><B>RESULTS: </B>87 distinct quality indicators identified through the rapid review process were assessed by our expert panel. The surveys received an average response rate of 83.1% in the first round and 96.7% in the second round. From the initial set of 87 quality indicators, our expert panel arrived at a consensus on 17 indicators including 7 structure, 6 process and 4 outcome indicators. A WPV dashboard was created to provide real-time data on each of these indicators.<BR><B>CONCLUSIONS: </B>Using a modified Delphi methodology, a set of quality indicators validated by expert opinion was identified measuring WPV specific to UHN. The indicators identified in this study were found to be operationalisable at UHN and will provide longitudinal quality monitoring. They will inform data visualisation and dissemination tools which will impact organisational decision-making in real time.