The development and validation of a dashboard prototype for real-time suicide mortality data

Abstract

Introduction/AimData visualisation is key to informing data-driven decision-making, yet this is an underexplored area of suicide surveillance. By way of enhancing a real-time suicide surveillance system model, an interactive dashboard prototype has been developed to facilitate emerging cluster detection, risk profiling and trend observation, as well as to establish a formal data sharing connection with key stakeholders via an intuitive interface.Materials and MethodsIndividual-level demographic and circumstantial data on cases of confirmed suicide and open verdicts meeting the criteria for suicide in County Cork 2008–2017 were analysed to validate the model. The retrospective and prospective space-time scan statistics based on a discrete Poisson model were employed via the R software environment using the “rsatscan” and “shiny” packages to conduct the space-time cluster analysis and deliver the mapping and graphic components encompassing the dashboard interface.ResultsUsing the best-fit parameters, the retrospective scan statistic returned several emerging non-significant clusters detected during the 10-year period, while the prospective approach demonstrated the predictive ability of the model. The outputs of the investigations are visually displayed using a geographical map of the identified clusters and a timeline of cluster occurrence.DiscussionThe challenges of designing and implementing visualizations for suspected suicide data are presented through a discussion of the development of the dashboard prototype and the potential it holds for supporting real-time decision-making.ConclusionsThe results demonstrate that integration of a cluster detection approach involving geo-visualisation techniques, space-time scan statistics and predictive modelling would facilitate prospective early detection of emerging clusters, at-risk populations, and locations of concern. The prototype demonstrates real-world applicability as a proactive monitoring tool for timely action in suicide prevention by facilitating informed planning and preparedness to respond to emerging suicide clusters and other concerning trends.

Using Real-Time Suicide Monitoring Systems to Inform Policy and Practice

“…The complexity of the task could partially explain the slow uptake in the use of real-time data to detect suicide clusters. The exception to this is the work by Benson and colleagues, who have used the scan statistic as the basis for prospective monitoring of suicide clusters in Cork County, Ireland (Benson et al, 2022). They developed a prototype real-time cluster surveillance system that presented summary results for dissemination in a way that supports decision-making in suicide prevention.…”

Police-led real-time surveillance system for suspected suicides in Great Britain

“…Real-time monitoring systems can also enable public health agencies and policy-makers to identify new trends, such as locations or populations of concern 17 18. For example, real-time monitoring in Japan during the COVID-19 pandemic identified that, after an initial decline in suicides, the numbers started to rise, particularly among young women,19 enabling a swift and targeted policy response 1.…”