Suicide prevention research faces specific challenges related to characteristics of suicide attempts and attempters. The design of powerful suicide prevention studies is especially challenging. Suicide attempters have been described as poorly adhering to long term treatment, and organizing such interventions from the emergency department can be difficult. While approximately one third of those who attempt suicide seek treatment for their injuries from hospital emergency department, a previous SA is a strong precursor of suicide-related premature death. The post-discharge period constitutes a critical challenge for emergency and mental health care services both in the short- and long-terms. Given these issues, there has been growing interest in assessing the efficacy of interventions that focus on maintaining post-discharge contact and offering re-engagement with health care services to suicide attempters. Suicide risk assessment usually rely on brief medical visit and does not report the evolution of this risk after the patient discharge. However, the reattempt risk is still high several months after the initial attempt. In these setting, long term suicide prevention of at risk subjects are challenging. Thanks to recent technological advances, electronic health (eHealth) data collection strategies now can provide access to real-time patient self-report data during the interval between visits. The extension of the clinical assessment to the patient environment and data processing using data mining will support medical decision making.