The x-axis shows each calendar year during the study period, and the y-axis shows the number of claims for the respective outcome. Bars show the rate of primary AUD claims per 100 000 total NIS claims. The orange line shows the mortality rate in primary AUD hospitalizations per 100 000 primary AUD claims. The dark blue line shows the comparative mortality rate in nonprimary AUD hospitalizations per 100 000 nonprimary AUD hospitalization claims. NIS indicates US National Inpatient Sample.
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Singh JA, Cleveland JD. Trends in Hospitalizations for Alcohol Use Disorder in the US From 1998 to 2016: . JAMA Netw Open. 2020;3(9):e2016580. doi:10.1001/jamanetworkopen.2020.16580
Alcohol use disorder (AUD) is among the most prevalent mental disorders worldwide. An estimated 14.5 million people in the US (5%) had an AUD in 2017.1 The published US national estimates for AUD hospitalizations are from 2003,2 with a lack of contemporary data. Our study objectives were to assess time trends in AUD hospitalizations and associated in-hospital mortality in the US over time. We hypothesized that AUD hospitalizations would increase and associated mortality would decrease over time.
This cross-sectional study used data from the US National Inpatient Sample (NIS) database. The NIS is a 20% stratified sample of all US community hospital discharges regardless of the payer type and the largest publicly available all-payer inpatient database in the US.3 The University of Alabama at Birmingham’s institutional review board approved this study and waived the need for informed consent because the data are anonymous and publicly available. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
This study examined NIS data from the years 1998 to 2016. In 2012, sampling changed from a sample of hospitals to a sample of discharges from all hospitals that participate in the Healthcare Cost and Utilization Project, so new definitions of hospitals and discharges were supplied.
We used the diagnostic codes for AUD in the primary position for hospitalization, excluding codes corresponding to drug or alcohol counseling and rehabilitation or detoxification, as described previously.4 We examined time trends in the number and rate of AUD hospitalizations and in-hospital mortality rates during the study period, 1998 to 2016, expressed as per 100 000 NIS claims. Significance of time trend was assessed with the Cochrane-Mantel-Haenszel test. We used the provided set of trend weights up to 2011 and discharge weights from 2012 to 2016 to allow analyses across multiple years, which include the period of design change. We calculated the 95% CI for estimates. A 2-sided P < .05 was considered statistically significant. Statistical analysis was performed using SAS statistical software version 9.4 (SAS Institute) from May to December 2019.
There were a total of 5 590 952 patients with primary AUD hospitalizations. The mean (SE) age was 48.7 (0.04) years. Of these patients, 4 078 733 (73.3%) were men, 3 284 699 (58.9%) were White, 3 155 516 (56.6%) had a comorbidity score (Deyo-Charlson Index score) of 0, and 106 419 (1.9%) died during hospitalization (Table).
We found a 3.5% increase in the AUD hospitalizations from 274 652 hospitalizations (95% CI, 243 587-305 717 hospitalizations) in 1998 to 284 275 hospitalizations (95% CI, 275 403-293 146 hospitalizations) in 2016; claims decreased first until 2005, and then increased to 2015 (Figure). There was a 25% and 28% decrease in the number of AUD hospitalization deaths and mortality rate per 100 000 total NIS claims, respectively (Figure; lowest in 2012). In-hospital mortality for AUD hospitalizations decreased by 25% (from 7305 [95% CI, 6757-7852] deaths per 100 000 claims in 1998 to 5475 [95% CI, 5088-5861] deaths per 100 000 claims in 2016) compared with a 20% decrease (from 842 386 [95% CI, 808 314-876 458] deaths per 100 000 claims in 1998 to 675 114 [95% CI, 659 158-691 071] deaths per 100 000 claims in 2016) for all other NIS claims.
In this cross-sectional study, we found a 28% decrease in in-hospital mortality rate per 100 000 total NIS claims from 1998 to 2016 among people with AUD hospitalizations. AUD hospitalization mortality reduction might be attributable to prompt recognition and treatment of AUD-associated medical complications5 and an integrated care model for mental health services6 in the more recent years. There was 3.5% increase in the rate of AUD hospitalizations from 1998 to 2016, showing a decline first until 2005 then an increase through 2015. Although AUD hospitalizations increased minimally, the overall health care impact of AUD is substantial.1 Both of these findings were consistent with our a priori hypotheses.
This study had some limitations that need to be addressed. We only examined hospitalizations with a primary diagnosis of AUD. NIS counts hospitalizations, not people, and excludes military or Veterans Affairs hospitals. Misclassification bias is possible because of the use of diagnostic codes for AUD.
From 1998 to 2016 in the US, AUD hospitalizations increased slightly while in-hospital mortality for patients hospitalized with AUD decreased significantly. A better understanding of what causes these time trends could help further improve AUD hospitalization outcomes and reduce mortality.
Accepted for Publication: June 30, 2020.
Published: September 21, 2020. doi:10.1001/jamanetworkopen.2020.16580
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Singh JA et al. JAMA Network Open.
Corresponding Author: Jasvinder A. Singh, MBBS, MPH, Division of Rheumatology, Department of Medicine, University of Alabama at Birmingham, 510 20th St S, Faculty Office Tower 805B, Birmingham, AL 35294 (email@example.com).
Author Contributions: Mr Cleveland had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Singh.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Cleveland.
Administrative, technical, or material support: Singh.
Conflict of Interest Disclosures: Dr Singh reported receiving consultant fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio Health, Medscape, WebMD, Clinical Care Options, Clearview Healthcare Partners, Putnam Associates, Spherix, Practice Point Communications, the National Institutes of Health, and the American College of Rheumatology. Dr Singh reported owning stock options in Amarin Pharmaceuticals and Viking Therapeutics. Dr Singh also reported being on the speaker’s bureau of Simply Speaking; a member of the executive board of Outcome Measures in Rheumatology (OMERACT), an organization that develops outcome measures in rheumatology and receives arms-length funding from 12 companies; on the US Food and Drug Administration Arthritis Advisory Committee; a member of the Veterans Affairs Rheumatology Field Advisory Committee; the editor and the director of the University of Alabama at Birmingham Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis; and previously served as a member of the following committees: member, the American College of Rheumatology’s (ACR) Annual Meeting Planning Committee and Quality of Care Committees, the Chair of the ACR Meet-the-Professor, Workshop and Study Group Subcommittee, and the co-chair of the ACR Criteria and Response Criteria subcommittee. No other disclosures were reported.
Funding/Support: This article is the result of work supported by research funds from the Division of Rheumatology at the University of Alabama at Birmingham and the resources and use of facilities at the Birmingham VA Medical Center, Birmingham, Alabama.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Information: These data are available from the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project (HCUP) and can be obtained after completing an online Data Use Agreement training session and signing a Data Use Agreement. Individuals are not allowed to distribute these data. The contact information for requesting the data is as follows: HCUP Central Distributor (firstname.lastname@example.org).