Characterizing trends in methamphetamine-related health care use when there is no ICD code for "methamphetamine use disorder"
- PMID: 34134872
- PMCID: PMC8217729
- DOI: 10.1016/j.jsat.2021.108369
Characterizing trends in methamphetamine-related health care use when there is no ICD code for "methamphetamine use disorder"
Abstract
Background and aims: The recent surge in methamphetamine use highlights the need for timely data on its health effects and healthcare service use impact. However, there is no ICD code for methamphetamine use. This study quantifies the positive predictive value of ICD-9-CM and ICD-10-CM psychostimulant codes for methamphetamine use.
Methods: A retrospective chart review of 220 adults aged 18 and older who had an inpatient admission with a psychostimulant-associated billing diagnosis at an urban safety-net hospital. Diagnoses were categorized as either methamphetamine-related or involving another specific psychostimulant. The positive predictive value of both ICD-9-CM or ICD-10-CM psychostimulant diagnosis codes for methamphetamine use was calculated.
Results: ICD-9-CM and ICD-10-CM psychostimulant codes had high positive predictive values of 78.2% (95% CI 70.3%-86.0%) and 85.5% (95% CI 78.8%-92.1%), respectively, for methamphetamine use. The most common non-methamphetamine psychostimulant in our cohort was khat, a cathinone-containing plant native to East Africa, accounting for psychostimulant-related diagnosis in 16 of the 220 hospitalizations.
Conclusions: The high predictive values of psychostimulant codes for methamphetamine use support the application of administrative data in measuring methamphetamine-related healthcare use, as well as co-morbid health conditions and treatment patterns.
Keywords: Administrative data; ICD codes; Methamphetamine; Psychostimulants.
Copyright © 2021 Elsevier Inc. All rights reserved.
Conflict of interest statement
Declarations of Interest: None.
References
-
- Drug Enforcement Administration. (2018). 2018 National Drug Threat Assessment. U.S. Department of Justice. https://www.dea.gov/sites/default/files/2018-11/DIR-032-18%202018%20NDTA...
-
- Green CA, Perrin NA, Janoff SL, Campbell CI, Chilcoat HD, & Coplan PM (2017). Assessing the accuracy of opioid overdose and poisoning codes in diagnostic information from electronic health records, claims data, and death records. Pharmacoepidemiology and Drug Safety, 26(5), 509–517. 10.1002/pds.4157 - DOI - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
