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ALGOS: the development of a randomized controlled trial testing a case management algorithm designed to reduce
Guillaume Vaiva1, Michel Walter, Abeer S Al Arab
1Département Universitaire de Psychiatrie & Pole de l'Urgence, Lille University Hospital, Lille, France. guillaume.vaiva@chru-lille.fr
Background:
Suicide attempts (SA) constitute a serious clinical problem. People who attempt suicide are at high risk of further repetition. However, no interventions have been shown to be effective in reducing repetition in this group of patients.
Methods/Design:
Multicentre randomized controlled trial. We examine the effectiveness of "ALGOS algorithm": an intervention based in a decisional tree of contact type which aims at reducing the incidence of repeated suicide attempt during 6 months. This algorithm of case management comprises the two strategies of intervention that showed a significant reduction in the number of SA repeaters: systematic telephone contact (ineffective in first-attempters) and "Crisis card" (effective only in first-attempters). Participants who are lost from contact and those refusing healthcare, can then benefit from "short letters" or "postcards".
Discussion:
ALGOS algorithm is easily reproducible and inexpensive intervention that will supply the guidelines for assessment and management of a population sometimes in difficulties with healthcare compliance. Furthermore, it will target some of these subgroups of patients by providing specific interventions for optimizing the benefits of case management strategy.