Alcohol Use Disorders amongst Inpatients in a General Hospital in Singapore: Estimated Prevalence, Rates of Identification and Intervention

Autor: Andre Ts, Tay, Andrew Lh, Peh, Sheng Neng, Tan, Herng Nieng, Chan, Song, Guo, Yiong Huak, Chan
Rok vydání: 2016
Předmět:
Zdroj: Annals of the Academy of Medicine, Singapore. 45:138-147
ISSN: 0304-4602
Popis: Introduction: Many alcohol-related problems often go undetected and untreated. In Singapore, no epidemiological studies have been done in general hospitals on alcohol use disorders (AUD), i.e. alcohol dependence and abuse (DSM-IV-TR). Such findings are useful in planning AUD liaison services. In this study, we aim to estimate the prevalence of AUD among non-psychiatric inpatients and to determine the rates of identification and intervention rendered by medical staff. Materials and Methods: Non-psychiatric medical and surgical wards inpatients aged 21 years and above were recruited over a 3-month period. The Alcohol Use Disorders Identification Test (AUDIT) was used to screen for AUD and the MINI International Neuropsychiatric Interview (MINI English Version 5.0.0) was administered to diagnose AUD if the AUDIT score was 8 or above. Case notes were independently reviewed for AUD identification and if interventions were offered during admissions. Results: A total of 5599 inpatients were screened, of which 673 (12%) completed the screening using the AUDIT, and of these, 154 (2.8% of total sample) were positive for AUDIT. In this group, 107 were diagnosed with AUD. The estimated prevalence was 1.9% (approximately 400 cases per year per hospital). The medical staff identified only 25 (23.4%) cases of AUD, out of which, majority of them (76%) were rendered interventions. Conclusion: The rate of AUD identification by medical staff was low. Of those identified, majority were given interventions. Thus, the training of health care staff to identify AUD together with the implementation of brief interventions should be considered. Key words: Alcoholism, Consultation liaison, Epidemiology
Databáze: OpenAIRE