An Effective Structured Out-patient Sleep Triage System Can Provide Early Treatment for High Risk Sleep Apneic Patients

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Abstract Description
Abstract ID :
HAC5798
Submission Type
Authors (including presenting author) :
Tang WK(1), Ling SO(1), Mok T(1), Poon YN(1), Yim CW(1), Kwan HY(1), Yau A(1), Ng PK(1), Ma O(1), Man LS(1), Woo FY(1), Ho HW(1), Fong SY(1)
Affiliation :
(1)Department of Respiratory Medicine, Kowloon Hospital
Introduction :
Long waiting time for sleep study remains as a common agenda item in most of public sleep service centres. However, studies showed that obstructive sleep apnea (OSA) represents an important risk factor for motor vehicle accidents, which is reversed by successful therapy with continuous positive airway pressure (Sleep Med 2008). In order to provide timely service for these high risk OSA patients such as driver, the Out-patient Sleep Clinic of Department of Respiratory Medicine (RMD), Kowloon Hospital (KH) has been enhanced since early 2017. Triage of the referrals was conducted by Associate Consultant of RMD. High risk patient groups such as commercial drivers, workers of high altitude, operators of heavy machinery or patients with past history of traffic accidents or near miss accidents due to excessive sleepiness would be triaged into Priority Urgent (P) category with the first appointment scheduled within 2 weeks whereas patients without these conditions would be triaged into Routine (R) category with appointment following the normal queue.
Objectives :
To evaluate the efficacy of the enhanced Structured Out-patient Sleep Triage System implemented since January 2017.
Methodology :
New sleep patients referred to KH Sleep Clinic during the period from 01/01/2017 to 31/12/2017 were included in this study. A triage questionnaire was designed to identify the high risk patients. Data on occupation such as commercial drivers, workers of high altitude, operators of heavy machinery or patients with past history of traffic accidents or near miss accidents due to excessive sleepiness were collected. The degree of daytime sleepiness was measured by Epworth Sleepiness Scale (ESS) and the severity of sleep apnea was determined by the frequency of apneas and hypopneas per hour of sleep i.e. apnea-hypopnea index (AHI) (Eur Respir Rev 2015).
Result & Outcome :
A total of 249 patients (mean age 50.8) completed the questionnaire (175 male and 74 female) achieving 98.4% response rate. Majority of patients: 211 (84.7%) were referred from Kowloon Central Cluster and the most common referring specialties included Ear, Nose and Throat (ENT): 151 (60.6%) and General Out-patient Clinic: 60 (24.1%). Among 249 patients, 20.5% (51) of patients were triaged into P category and 79.5% (198) of patients were triaged into R category group. From the referral letters, only 10 patients were identified as high risk patients. But with the completion of the triage questionnaire, 51 patients were considered as high risk representing a 5-fold increase in detection rate. The average waiting time for sleep study were 35 days and 1168 days for the P and R category groups respectively. The P category group had a higher mean ESS score (13.3) compared with the R category group which contributes to an increased accident risk. In addition, the P category group got a higher mean AHI (34.4±22.1 versus 21.9±20.8, p=0.002) and the prevalence of moderate and severe OSA was significantly higher in the P category group compared with the R category group (82.4% versus 44.3%, p< 0.0005). After treatment such as CPAP therapy, there was a significant difference in ESS scores (13.25±4.66 versus 7.57±2.11, p< 0.001) with 42.9% decrease in the mean ESS scores. Treated patients became less sleepy and their risk of having accident such as traffic accident was reduced. In conclusion, early identification, early diagnosis and early treatment of sleep apnea are extremely important for the high risk patients and the community as a whole since OSA is the risk factor for accidents. The findings demonstrated that a structured triage questionnaire was useful to obtain early diagnosis and treatment for OSA patients at risk of accidents. This tool is proven to be a good indicator to identify high risk OSA patient in sleep clinic.

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