A systematic review of regulatory and educational interventions to reduce the burden associated with the prescriptions of sedative-hypnotics in adults treated for sleep disorders.

Abstract

The burden of Sedative-Hypnotics (SHs) has been known since the 1980s. Yet, their consumption remains high. A systematic review of the literature should help to assess efficient interventions to improve the appropriate use of SHs in sleep disorders.To identify and assess regulatory and educational interventions designed to improve the appropriate use of SHs for insomnia treatment.We conducted a systematic review of the literature according to PRISMA guidelines. A systematic search covering the period 1980-2015 was carried out in Medline, Web of Science, Embase and PsycInfo. We included studies reporting the implementation of regulatory or educational strategies directed towards patients and/or healthcare professionals to improve the appropriate use of SHs to treat insomnia in the community, hospitals and nursing homes.Thirty-one studies were included: 23 assessed educational interventions (recommendations by mail/email, computer alerts, meetings, mass media campaigns, prescription profile), 8 assessed regulatory interventions (prescription rule restriction, end of reimbursement). The most recent was implemented in 2009. Restrictive prescription rules were effective to reduce the consumption of targeted SHs but led to a switch to other non-recommended SHs. Among educational interventions, only 3 studies out of 7 reported positive results of mono-faceted interventions; whereas, 13 out of the 16 multi-faceted interventions were reported as efficient: particularly, the active involvement of healthcare professionals and patients and the spread of information through mass media were successful. The risk of bias was high for 24 studies (mainly due to the design), moderate for 3 studies and weak for 4 studies.Educational multifaceted studies are presented as the most efficient. But further better designed studies are needed to make evidence-based results more generalizable.