Does Emergency Department Use for Alcohol and Other Drug Use Cluster Geographically? A Population-Based Retrospective Cohort Study

ABSTRACT

Purpose: To identify geographic areas in Alberta, Canada with higher numbers of adolescents with an emergency department (ED) presentation for a mental or behavioral disorder secondary to alcohol and other drug use. Methods: A population-based cohort analysis of ED visits (n = 7787) by adolescents aged 15–17 years (n = 7238) during 2002–2011. We calculated sex-adjusted directly standardized rates (DSRs) and identified space-time clusters in health zones (North, Edmonton, Calgary, Central, and South). Results: The North zone had higher DSRs compared to other areas. Clusters were identified in: (1) North, Edmonton, and northwest Central zones [relative risk (RR: 1.54; from 2004 to 2008); (2) western South and southern Calgary zones (RR: 1.58; from 2007 to 2011); and (3) northern South zone (RR: 2.38; from 2006 to 2007). Conclusions: The spatial scan can identify geographic areas of high health care use for specific health conditions. These results, in turn, can be used to inform health resource planning.

KEYWORDS:

• Emergency department
• alcohol and other drug use
• cluster detection

Glossary

• ACCS: Ambulatory Care Classification System

• AOD: Alcohol and other drug

• CI: Confidence interval

• DSR: Directly standardized rate

• ED: Emergency department

• Kulldorff-Nagarwalla spatial scan test: A spatial scan statistic used for cluster detection

• Mental and behavioral disorders secondary to AOD use: In this study, these disorders were identified through the International Classification of Diseases diagnostic codes: F10 (mental and behavioral disorders due to use of alcohol), F11 (mental and behavioral disorders due to use of opioids), F12 (mental and behavioral disorders due to use of cannabinoids), F13 (mental and behavioral disorders due to use of sedatives or hypnotics), F14 (mental and behavioral disorders due to use of cocaine), F15 (mental and behavioral disorders due to use of other stimulants), F16 (mental and behavioral disorders due to use of hallucinogens), F17 (mental and behavioral disorders due to use of tobacco), F18 (mental and behavioral disorders due to use of volatile solvents), and F19 (mental and behavioral disorders due to use of other psychoactive substances)

• Monte Carlo method: A method that relies on repeated random generation of data to obtain numerical results

• RR: Relative risk

• Screening, SBIRT: The approach recommended by the World Health Organization to reduce problematic alcohol use

• sRHA: Sub-Regional Health Authority

Acknowledgments

The authors thank Xiaoqing Niu, PhD and Jingbin Zhang, MSc for assistance with the data analysis. This study is based in part on data provided by Alberta Health. The interpretation and conclusions contained herein are those of the researchers and do not necessarily represent the views of the Government of Alberta. Neither the Government of Alberta nor Alberta Health expresses any opinion in relation to this study.

Declaration of interest

Dr. Newton holds a New Investigator Award from the Canadian Institutes of Health Research. Dr. Rosychuk is salary supported by the Alberta Heritage Foundation for Medical Research as a Health Scholar.

Funding

The study reported in this article was supported by a research grant from the MSI Foundation (Grant No. 860).

Additional information

Notes on contributors

Amanda S. Newton

Amanda S. Newton, Ph.D., is an Associate Professor and Clinician Scientist at the University of Alberta and Stollery Children's Hospital (Edmonton, Alberta, Canada). Her research focuses on child and adolescent mental health.

Kassi Shave

Kassi Shave holds a Bachelor of Community Rehabilitation and is currently a graduate student in the Department of Pediatrics at the University of Alberta.

Rhonda J. Rosychuk

Rhonda J. Rosychuk, Ph.D., P.Stat., PStat (ASA), is a Professor and accredited Professional Statistician at the University of Alberta. Her research includes the development and application of statistical methodology for disease cluster detection.