The development of a sleep disorder screening program in Australian community pharmacies

To develop, pilot and determine the feasibility of a sleep-specific screening and awareness program in community pharmacies.

The screening was piloted in five Australian community pharmacies.

The Pharmacy Tool for Assessment of Sleep Health was constructed by drawing on known relationships between sleep disorders, and lifestyle factors, medical conditions and medications. Four validated instruments were used in the screening tool: the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Multivariable Apnea Prediction Index (MAPI) and International Restless Legs Syndrome Study Group Screening Criteria (IRLS). These instruments were used to predict the participant's risk of a sleep disorder and the results were compared with reported lifestyle, medical and medication factors. On-site training of consenting pharmacists was provided, followed by an eight week client recruiting and screening period. Feedback was elicited from participating pharmacists and clients.

The feasibility of, and trends found from, the developed screening tool and protocol.

Of 167 clients who requested or were invited to participate by pharmacists, 84 (50.3%) were screened. Analysis of collected data indicated that 33.3%, 21.4% and 27.4% of participants were at risk of having or developing insomnia, obstructive sleep apnea (OSA) and restless legs syndrome (RLS) respectively, while 38.1% were not at risk of any of the screened disorders. OSA odds increased 12.8 times (95% CI: 3.2-50.4) with diabetes and 4.9 times (1.2-20.9) with opioid use, while shift workers were 8.4 times (1.6-43.2) more likely to have insomnia. Participants and pharmacists reported the screening protocol and instrument was user friendly and feasible.

The development and pilot of this screening tool was successful. The prevalence of sleep disorders in the sampled population was high but generally consistent with previous studies on the general population. Furthermore, associations found may form a foundation for a clinical algorithm to identify those at a higher risk of having or developing a sleep disorder. Further work is required to validate this screening tool in the community pharmacy context.