Substance Use Disorder Detection Rates Among Providers of General Medical Inpatients

Abstract

BACKGROUND:The prevalence of substance use disorders is higher among medical inpatients than in the general population, placing inpatient providers in a prime position to detect these patients and intervene. OBJECTIVE: To assess provider detection rates of substance use disorders among medical inpatients and to identify patient characteristics associated with detection. DESIGN: Data drawn from a cluster randomized controlled trial that tested the effectiveness of three distinct implementation strategies for providers to screen patients for substance use disorders and deliver a brief intervention (Clinical Trials.gov: NCT01825057). PARTICIPANTS: A total of 1076 patients receiving care from 13 general medical inpatient units in a large teaching hospital participated in this study. MAIN MEASURES: Data sources included patient selfreported questionnaires, a diagnostic interview for substance use disorders, and patient medical records. Provider detection was determined by diagnoses documented in medical records. KEY RESULTS: Provider detection rates were highest for nicotine use disorder (72.2%) and lowest for cannabis use disorder (26.4%). Detection of alcohol use disorder was more likely among male compared to female patients (OR (95% CI) = 4.0 (1.9, 4.8)). When compared to White patients, alcohol (OR (95% CI) = 0.4 (0.2, 0.6)) and opioid (OR (95% CI) = 0.2 (0.1, 0.7)) use disorders were less likely to be detected among Black patients, while alcohol (OR (95% CI) = 0.3 (0.0, 2.0)) and cocaine (OR (95% CI) = 0.3 (0.1, 0.9)) use disorders were less likely to be detected among Hispanic patients. Providers were more likely to detect nicotine, alcohol, opioid, and other drug use disorders among patients with higher addiction severity (OR (95% CI)

Trends in Cannabis-positive Urine Toxicology Test Results: US Veterans Health Administration Emergency Department Patients, 2008 to 2019

“…Second, given highly unbalanced numbers of VHA patients by age, trends in cannabis-positive UDS were calculated overall and stratified by age group (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34), and 65-75 years). We tested the degree of change (ie, trends) in cannabis-positive UDS over time using logistic regression models that included study year, age category, year by age category, sex, and race and ethnicity as adjustment variables.…”

“…EHR and claims data can provide more timely information on CUD diagnosis trends but rely on providers consistently screening or diagnosing substance use disorders (SUDs), a practice that is not often done in a consistent manner, 17 leading to an underdiagnosis of SUDs in clinical settings, with CUD detection rates being lower than that of all other SUDs. 18 Moreover, concerns about legality or social stigma around drug use may lead to underreporting and underestimating the prevalence of cannabis use in survey data and CUD diagnosis in EHR data. [19][20][21] However, the effect of legal concerns and social stigma on reporting is difficult to quantify and may vary across populations and over time.…”

“…Although self-report measures are relatively quick and easy to administer, national surveys that collect these data are costly and can take years to analyze. EHR and claims data can provide more timely information on CUD diagnosis trends but rely on providers consistently screening or diagnosing substance use disorders (SUDs), a practice that is not often done in a consistent manner, 17 leading to an underdiagnosis of SUDs in clinical settings, with CUD detection rates being lower than that of all other SUDs 18 . Moreover, concerns about legality or social stigma around drug use may lead to underreporting and underestimating the prevalence of cannabis use in survey data and CUD diagnosis in EHR data 19–21 .…”

Comparing COVID-19-related Morbidity and Mortality Between Patients With and Without Substance Use Disorders: A Retrospective Cohort Study

“…Prescribed opioid, benzodiazepine, and amphetamine use was classified as SUD if there was documentation of concern for a use disorder in the electronic medical record. We did not include cannabis use disorder in our definition of SUD because of substantial under-detection of cannabis use disorder by ICD-10 codes 24 - 26 and inconsistent language describing cannabis consumption which limits identification of use disorders with free text documentation. 26 , 27 We also did not include other substances such as inhalants and hallucinogens as they were rarely reported in the charts.…”

The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design

“…The number of substance use–related hospital visits outpaces visits for heart disease and respiratory failure [ 2 ]. Despite the recommendations from the US Preventive Services Task Force for Unhealthy Drug Use Screening [ 3 ], hospital screening rates remain low, with detection rates around 50% [ 4 ]. Manual screening efforts within busy hospital settings impose staffing requirements and administrative burdens, with the corresponding missed opportunities to prioritize care for the most vulnerable patients.…”