Condition, diagnosis, or reason for seeking medical attention.

Data Element
Alcohol Use Disorder
Description

This data element captures the Alcohol Use Disorder (AUD) diagnosis, which reflects the current nosology for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).
Submitted By: Laura Kwako / National Institute on Alcohol Abuse and Alcoholism
Data Element Information
Use Case Description(s)
Use Case Description Each year, an estimated 88,000 people (approximately 62,000 men and 26,000 women) die from alcohol-related causes annually, making alcohol the third leading preventable cause of death in the United States, behind tobacco and diet/physical inactivity. According to the 2019 National Survey on Drug Use and Health (NSDUH), 85.6 percent of people ages 18 or older reported that they drank alcohol at some point in their lifetime; 69.5 percent reported that they drank in the past year; 54.9 percent reported that they drank in the past month. From this same survey, 14.1 million adults ages 18 and older (5.6 percent of this age group) had alcohol use disorder (AUD). This includes 8.9 million men (7.3 percent of men in this age group) and 5.2 million women (4.0 percent of women in this age group).
Estimate the breadth of applicability of the use case(s) for this data element The U.S. Preventive Services Task Force (USPSTF) recommends screening for unhealthy alcohol use in adults aged 18 years and older, including pregnant women, with a Grade B recommendation:
https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/unhealthy-alcohol-use-in-adolescents-and-adults-screening-and-behavioral-counseling-interventions

These data elements are relevant for virtually all health care practitioners, across settings, given that nearly 70% of adults in the U.S. report consuming alcohol within the past year. In 2018, the Kaiser Family Foundation estimated that 16.9 million individuals work in the healthcare sector.
Most importantly, the AUDIT-C has been required by the ONC as of the 2015 rule – so it is critical that it also be a part of USCDI.
Link to use case project page https://www.samhsa.gov/data/release/2019-national-survey-drug-use-and-health-nsduh-releases (Sections 2 and 5)
Healthcare Aims
  • Improving the health of populations
Maturity of Use and Technical Specifications for Data Element
Applicable Standard(s) Most of the requested data elements are in LOINC, as per the codes below. We have requested the addition of the NIAAA Single-Item Screener and the diagnosis of Alcohol Use Disorder to LOINC.
AUDIT-C : 72109-2
Ethanol in blood: 5640-8
Ever drink alcohol: 69721-9
Average daily alcohol intake: 74013-4
Alcohol binge episodes/month: 11286-2
Alcohol abuse or dependence: 74043-1
Alcohol help during pregnancy: 64718-0
https://loinc.org/72109-2/ https://loinc.org/5640-8/ https://loinc.org/69721-9/ https://loinc.org/74013-4/ https://loinc.org/11286-2/ https://loinc.org/74043-1/ https://loinc.org/64718-0/
Additional Specifications N/A
Current Use This data element has been used at scale between multiple different production environments to support the majority of anticipated stakeholders
Supporting Artifacts Healthcare organizations routinely screen for alcohol use across settings including primary care, emergency departments, specialty care (OB/GYN), etc. These data are largely captured and, as such, should be included within the USCDI data elements. The AUDIT-C is widely used in the research community and in the VA system. The NIAAA Single-Item Screener is largely applicable for primary care settings, although it may be extended to other settings requiring a quick screen for unhealthy alcohol use. AUD as a diagnostic category has been used since 2013, when the current nosology was updated to DSM-5.
Extent of exchange 5 or more. This data element has been tested at scale between multiple different production environments to support the majority of anticipated stakeholders.
Supporting Artifacts As these data are routinely captured in existing electronic health records, they may be electronically exchanged across systems and with patients. As described above, both the AUDIT-C and NIAAA Single-Item Screener are widely used in research and clinical care settings, as is the AUD diagnosis.
Potential Challenges
Restrictions on Standardization (e.g. proprietary code) Data elements around quantity of alcohol consumed may be measured in different units, or entered in different locations within electronic health records. However, these are minimal, as they do not involve access to proprietary code.
Restrictions on Use (e.g. licensing, user fees) None
Privacy and Security Concerns If data are aggregated and not linked to personal identifiers, concerns are minimal. Alcohol use disorder is widely stigmatized, thus, care must be taken to ensure privacy and security.
Estimate of Overall Burden Overall burden to implement should be minimal to moderate, as most of these data will already be captured within existing health records. The primary use case affects virtually all healthcare workers, thus, the relatively small burden of implementation will have a substantial positive impact on our ability to study the economic, health, and societal costs of alcohol use.
Other Implementation Challenges None

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