A systematic review of the economic evidence surrounding the management of alcohol withdrawal

对酒精戒断管理相关的经济学证据进行系统性回顾

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Abstract

ISSUES: Alcohol withdrawal syndrome (AWS) is a medical emergency associated with lengthy hospital stays and an increased frequency of alcohol-related hospital admissions. Rising numbers of alcohol-related health presentations and limited resources of alcohol treatment services necessitate the implementation of both cost-effective and clinically effective interventions. APPROACH: A systematic literature search was conducted to review the economic evidence base for AWS interventions. A search of PubMed, Medline, Embase, Web-of-Science and Proquest identified 6347 articles. Following duplicate removal, 5250 English language papers were screened; 58 papers met eligibility criteria. Fifty papers were excluded at full-text screening; 8 papers were included. A novel logic model describing factors impacting clinical and cost-effectiveness of AWS management was developed. KEY FINDINGS: The United States (3), the United Kingdom (3), France (1) and Switzerland (1) based studies took primarily a health sector perspective, with most reporting on cost savings, rather than full health economic evaluations. Both patient- or symptom-specific guidelines and outpatient treatment reduce service costs in select patient populations, without impacting on treatment outcomes. Additional psychological outpatient support may also be a cost-effective addition to treatment. IMPLICATIONS: Where clinically suitable, early transition of AWS treatment to outpatient settings, alongside implementation of patient- or symptom-specific treatment guidelines, both may improve the cost-effectiveness of alcohol treatment services. Significant heterogeneity among current study methodology, patient population and poor-quality economic evidence means further studies are required. CONCLUSION: To develop a more robust understanding of cost and clinical-effectiveness, we propose a transdisciplinary research agenda between health economics, academic expertise and AWS services to address the current evidence gap in this area.

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