Denver researchers created a 95.7% accurate system for tracking marijuana-related ER visits in real time
A syndromic surveillance definition using 6 keywords and 5 diagnosis codes identified marijuana-related ER visits with 95.7% accuracy in Denver hospitals, providing a scalable method for real-time public health monitoring.
Quick Facts
What This Study Found
Researchers developed and validated a case definition for identifying marijuana-related ER visits using structured and free-text data from 15 Denver hospitals. The initial definition achieved 92.7% positive predictive value (PPV) in a validation period of 126,646 ER visits.
After refinement, the final case definition achieved 95.7% PPV in a second validation period of 140,932 visits. The final definition contained just 6 keywords for marijuana or derivatives and 5 diagnosis codes for cannabis use, abuse, dependence, poisoning, and lung disease.
This tool enables near-real-time monitoring of marijuana-related ER visits, which is critical for tracking the public health impact of legalization.
Key Numbers
Round 1: 524 matches from 126,646 visits, PPV 92.7%. Round 2: 698 matches from 140,932 visits, PPV 95.7%. Final definition: 6 keywords + 5 diagnosis codes. 15 Denver hospitals.
How They Did This
Applied a syndromic case definition to BioSense 2.0 data from 15 Denver hospitals. Two rounds of validation with manual record review to determine true and false positives. Iterative refinement between rounds improved the PPV from 92.7% to 95.7%.
Why This Research Matters
As marijuana policies change rapidly, public health systems need reliable, efficient ways to monitor health impacts. This tool demonstrates that existing ER data systems can be leveraged for near-real-time marijuana surveillance with high accuracy, without requiring new data collection infrastructure.
The Bigger Picture
The ability to monitor marijuana-related health events in near-real time is essential for evidence-based policy. Without reliable surveillance, debates about legalization's health impact rely on anecdote and outdated data. This methodology can be adopted by any jurisdiction with syndromic surveillance infrastructure.
What This Study Doesn't Tell Us
Validated in one metropolitan area (Denver). The PPV measures accuracy of identified cases but does not capture sensitivity (cases missed). Free-text data quality varies across hospitals. The system identifies "marijuana-related" visits, not necessarily visits caused by marijuana.
Questions This Raises
- ?What is the sensitivity of this definition (how many marijuana-related visits does it miss)?
- ?Would the same keywords and codes work in other cities?
- ?Can this approach distinguish between recreational and medical cannabis-related visits?
Trust & Context
- Key Stat:
- 95.7% accuracy for identifying marijuana-related ER visits in Denver hospitals
- Evidence Grade:
- Validated surveillance methodology with two rounds of testing. Demonstrates high accuracy but validated in a single metro area.
- Study Age:
- Published in 2017. Syndromic surveillance of cannabis-related health events has been adopted by additional jurisdictions since.
- Original Title:
- Validation of a Syndromic Case Definition for Detecting Emergency Department Visits Potentially Related to Marijuana.
- Published In:
- Public health reports (Washington, D.C. : 1974), 132(4), 471-479 (2017)
- Authors:
- DeYoung, Kathryn, Chen, Yushiuan(2), Beum, Robert, Askenazi, Michele, Zimmerman, Cali, Davidson, Arthur J
- Database ID:
- RTHC-01368
Evidence Hierarchy
A snapshot of a population at one point in time.
What do these levels mean? →Frequently Asked Questions
Why do we need to track marijuana ER visits?
As marijuana policies change, public health systems need data on whether legalization increases health-related emergencies. Real-time tracking allows officials to identify trends, emerging problems (like edible overconsumption), and vulnerable populations.
How does the system work?
It searches ER records for specific marijuana-related keywords and diagnosis codes. When a match is found, it flags that visit as potentially marijuana-related. Manual review confirmed the system correctly identifies relevant visits about 96% of the time.
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Cite This Study
https://rethinkthc.com/research/RTHC-01368APA
DeYoung, Kathryn; Chen, Yushiuan; Beum, Robert; Askenazi, Michele; Zimmerman, Cali; Davidson, Arthur J. (2017). Validation of a Syndromic Case Definition for Detecting Emergency Department Visits Potentially Related to Marijuana.. Public health reports (Washington, D.C. : 1974), 132(4), 471-479. https://doi.org/10.1177/0033354917708987
MLA
DeYoung, Kathryn, et al. "Validation of a Syndromic Case Definition for Detecting Emergency Department Visits Potentially Related to Marijuana.." Public health reports (Washington, 2017. https://doi.org/10.1177/0033354917708987
RethinkTHC
RethinkTHC Research Database. "Validation of a Syndromic Case Definition for Detecting Emer..." RTHC-01368. Retrieved from https://rethinkthc.com/research/deyoung-2017-validation-of-a-syndromic
Access the Original Study
Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.
This study breakdown was produced by the RethinkTHC research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.