Citation

Deyoung K, Chen Y, Beum R, Askenazi M, Zimmerman C, Davidson AJ. Public Health Rep. (1974) 2017; 132(4): 471-479.

Affiliation

1 Denver Public Health, Denver, CO, USA.

Copyright

(Copyright © 2017, Association of Schools of Public Health)

DOI

10.1177/0033354917708987

PMID

28586627

Abstract

OBJECTIVES: Reliable methods are needed to monitor the public health impact of changing laws and perceptions about marijuana. Structured and free-text emergency department (ED) visit data offer an opportunity to monitor the impact of these changes in near-real time. Our objectives were to (1) generate and validate a syndromic case definition for ED visits potentially related to marijuana and (2) describe a method for doing so that was less resource intensive than traditional methods.

METHODS: We developed a syndromic case definition for ED visits potentially related to marijuana, applied it to BioSense 2.0 data from 15 hospitals in the Denver, Colorado, metropolitan area for the period September through October 2015, and manually reviewed each case to determine true positives and false positives. We used the number of visits identified by and the positive predictive value (PPV) for each search term and field to refine the definition for the second round of validation on data from February through March 2016.

RESULTS: Of 126 646 ED visits during the first period, terms in 524 ED visit records matched ≥1 search term in the initial case definition (PPV, 92.7%). Of 140 932 ED visits during the second period, terms in 698 ED visit records matched ≥1 search term in the revised case definition (PPV, 95.7%). After another revision, the final case definition contained 6 keywords for marijuana or derivatives and 5 diagnosis codes for cannabis use, abuse, dependence, poisoning, and lung disease.

CONCLUSIONS: Our syndromic case definition and validation method for ED visits potentially related to marijuana could be used by other public health jurisdictions to monitor local trends and for other emerging concerns.

Language: en

Keywords

binning algorithm; marijuana; syndromic surveillance