ArticleJournal of medical systems2018
Development of an Algorithm to Identify Cannabis Urine Drug Test Results within a Multi-Site Electronic Health Record System.
Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Developing and validating a natural language processing algorithm to extract preoperative cannabis use status documentation from unstructured narrative clinical notes.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- A national population-based study of cannabis use and correlates among U.S. veterans prescribed opioids in primary care.BMC psychiatry · 2023Article
- Cannabis Use and Risk of Acute Kidney Injury in Patients with Advanced Chronic Kidney Disease Transitioning to Dialysis.Cannabis and cannabinoid research · 2023Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
With the rapid changes in the legalization of cannabis in the U.S., there is an urgent need to understand clinical outcomes and processes of care among patients who use cannabis, particularly among patients with chronic pain who are high utilizers of cannabis. Electronic health records (EHRs) are a common and convenient mechanism for examining processes of care; however, there is not an indication for cannabis use that does not meet criteria for a diagnostic disorder. We used urine drug test (UDT) results identified through EHRs to identify patients with confirmed cannabis use. We developed and tested an algorithm to identify outcomes of UDT results for cannabis because there is wide variability in reporting methodology, including in multi-site health systems. Among all patients receiving care in the Department of Veterans Affairs (VA) who were prescribed long-term opioid therapy for chronic pain, we identified a random sample who completed UDT for cannabis. Through an iterative process, we developed an algorithm to identify UDT cannabis results. Manual review of EHR data was conducted to verify accuracy of UDT results. The final UDT algorithm correctly identified 99% of cannabis positive UDT results and 100% of cannabis negative UDT results among 200 randomly sampled patients. Study findings suggest a high degree of accuracy for using an algorithm to identify samples of patients with positive cannabis UDT results across multiple institutions with disparate UDT reporting practices. The methodology for testing this algorithm is feasible and may be applied to other multi-site health systems.
Indexed as
Identifiers
30043122What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.