Strategic Priority: Data

Use new and existing data to better understand, monitor, and prevent suicide and suicidal behavior

Suicide Prevention Strategic Plan

Data serve as the backbone of a public health approach to suicide prevention. Surveillance data are used by public health practitioners to define the problem of suicide; including its scope, magnitude, and trends over time. Data also direct us to the factors increasing or decreasing suicide risk; show where additional prevention resources are needed most; and help us understand the effectiveness of prevention policies, programs, and practices. However, gaps in data exist, and new data sources and innovative methods remain untapped. For example, data from traditional surveillance systems often lack timeliness, but the growth of syndromic surveillance and near real-time data offer the potential to track trends and identify spikes in suicide and suicide attempts. Additionally, geographic information systems software also provides the ability to geolocate suicide hotspots.

New data sources and innovative data methods can also provide opportunities for rapid preventive action in states and communities. Emerging data science tools, methods, and techniques also hold great promise for advancing our understanding of suicide and suicidal behavior and informing prevention efforts. For example, machine learning models using multiple near real-time data sources have shown potential for estimating weekly suicide trends with high accuracy and timeliness. Improvements in the data and tools to use them, coupled with dissemination to states and communities to drive action, can improve our efforts to stem increases in suicide and reverse current trends.

GOAL 1: Improve the quality and enhance the use of existing data sources and systems

OBJECTIVE 1.1: Link CDC data sources and other federal data systems to provide more comprehensive, holistic details on suicide mortality than each system can provide on its own, with a focus on vulnerable populations

OBJECTIVE 1.2: Improve the quality, utility, and accessibility of existing data for analyzing nonfatal suicide-related outcomes (e.g., self-harm, suicide attempts, nonsuicidal self-injury)

OBJECTIVE 1.3: Build state and community capacity to use existing data for comprehensive prevention

GOAL 2: Identify and leverage new data sources and methods

OBJECTIVE 2.1: Implement and expand coverage of syndromic surveillance of nonfatal suicide-related outcomes for improved timeliness, ability to identify spikes in outcomes, and prevention response

OBJECTIVE 2.2: Identify and make use of innovative data sources (e.g., social media) and data science tools, methods, and techniques to track and monitor suicide-related outcomes to inform prevention and for use in program evaluation and continuous quality improvement

OBJECTIVE 2.3: Build state and community capacity to use new data for comprehensive prevention