Background
In the United States, 29 million adults have alcohol use disorder (AUD), and alcohol contributes to over 140,000 annual deaths.1 Hospitalizations provide an opportunity to promote behavior change by initiating medications for AUD (MAUD) including naltrexone, acamprosate, and disulfiram, which have been approved by the Food and Drug Administration for decades.2 Low prescribing rates for hospitalized patients have been observed in single center studies, but there is a lack of nationwide data on post-hospitalization MAUD initiation.3
Objective
Characterize MAUD initiation following AUD hospitalizations using the 20% national sample of Medicare Part D claims from 2015-2017.
Methods
Our sample included Medicare Parts A, B and D beneficiaries with continuous enrollment 12 months prior and following cohort entry (or until death if within 12 months) and excluded Medicare Advantage beneficiaries. We identified acute care hospitalizations in 2016 with a discharge diagnosis of AUD, defined using either primary or secondary (i.e. non-primary) International Classification of Disease – 10th Edition (ICD-10) discharge diagnosis codes.4 We excluded patients with recent MAUD fills or contraindications to both naltrexone and acamprosate.
Discharge MAUD initiation was defined as pharmacy claims for naltrexone, acamprosate, or disulfiram between the day before discharge and 2 days after. The secondary outcome was MAUD initiation up to 30 days post-discharge. We used mixed effect logistic regressions with clustering of repeat hospitalizations to identify predictors of discharge and 30-day MAUD initiation adjusted for sociodemographics, clinical characteristics, and hospitalization factors.
Findings
The cohort included 28,601 AUD hospitalizations representing 20,401 unique patients (Table). Overall, 206 patients (0.7%) initiated MAUD within 2 days of discharge, and 364 patients (1.3%) initiated MAUD within 30 days (Figure). Among patients with a primary AUD discharge diagnosis, 70 (2.3%) initiated MAUD within 2 days of discharge.
Table:
Characteristics of alcohol-related hospitalizations and predictors of medication initiation
| Characteristics | No. (%) (N = 28,601)A |
MAUD initiationB aOR (95% CI) | |
|---|---|---|---|
| Within 2 days of discharge |
Within 30 days of discharge |
||
| Age category, years | |||
| 18-39 | 2,183 (7.6) | 3.87 (1.34-11.16) | 5.53 (2.52-4.75) |
| 40-54 | 6,915 (24.2) | 2.82 (1.06-7.50) | 3.90 (1.88-8.10) |
| 55-64 | 7,398 (25.9) | 3.29 (1.25-8.61) | 3.59 (1.75-7.38) |
| 65-74 | 8,605 (30.1) | 1.91 (0.75-4.84) | 2.89 (1.44-5.78) |
| 75+ | 3,500 (12.2) | Ref | Ref |
| Female | 8,335 (29.1) | 1.49 (1.02-2.18) | 1.61 (1.25-2.08) |
| Race/ethnicityC | |||
| Non-Hispanic Black | 4,999 (17.5) | Ref | Ref |
| Non-Hispanic White | 20,554 (71.9) | 1.78 (0.995-3.18) | 1.48 (1.01-2.16) |
| Hispanic | 1,989 (7.0) | 1.47 (0.59-3.67) | 0.98 (0.51-1.89) |
| Other | 1,059 (3.7) | 1.61 (0.53-4.94) | 1.49 (0.72-3.08) |
| RegionD | |||
| Northeast | 6,806 (23.8) | Ref | Ref |
| Midwest | 6,770 (23.7) | 0.88 (0.53-1.46) | 0.76 (0.55-1.07) |
| South | 10,381 (36.3) | 0.90 (0.57-1.43) | 0.71 (0.52-0.96) |
| West | 4,644 (16.2) | 0.91 (0.49-1.71) | 0.62 (0.40-0.97) |
| Non-Medicaid dual-eligible | 10,690 (37.4) | 1.52 (0.96-2.41) | 1.39 (1.01-1.89) |
| Primary AUD discharge diagnosisE | 3,072 (10.7) | 4.75 (2.91-7.74) | 3.46 (2.52-4.75) |
| Elixhauser readmission index,F | NA | 0.98 (0.96-0.99) | 0.98 (0.97-0.99) |
| Psychiatric disorderG | 21,000 (73.4) | 2.41 (1.12-5.16) | 2.11 (1.31-3.41) |
| Absence of opioid use disorderH | 23,522 (82.2) | 1.39 (0.88-2.21) | 1.33 (0.97-1.82) |
| Inpatient addiction medicine or psychiatryI | |||
| None | 21,657 (75.7) | Ref | Ref |
| Psychiatric hospital | 3,416 (11.9) | 9.80 (5.54-17.34) | 3.87 (2.74-5.47) |
| Psychiatry/addiction medicine at general hospital | 3,528 (12.3) | 6.23 (3.68-10.57) | 2.90 (2.09-4.02) |
| Medical hospitalization (vs surgical)J | 24,994 (87.4) | 5.44 (1.20-24.64) | 2.57 (1.27-5.23) |
| Past year primary care visitK | 16,844 (58.9) | 1.18 (0.82-1.72) | 1.08 (0.84-1.40) |
| Past year mental health visitL | 3,243 (11.3) | 0.78 (0.49-1.25) | 1.04 (0.76-1.43) |
| Absence of self-directed dischargeM | 27,119 (94.8) | 18.48 (2.11-162.13) | 2.86 (1.36-6.02) |
| Remote prior MAUD treatmentN | 294 (1.0) | 11.41 (4.92-26.48) | 13.09 (7.15-23.94) |
Cohort included patients with a primary or secondary discharge diagnosis of AUD who were discharged home and excluded those with MAUD fills in the 3 months prior to hospitalization or contraindications to both naltrexone and acamprosate (liver disease defined by Elixhauser ICD-10 codes and renal failure defined by either Elixhauser ICD-10 codes, inpatient hemodialysis, or qualification for Medicare due to end stage renal disease)
Defined as any pharmacy claim for naltrexone, acamprosate, or disulfiram
Self-reported and imputed race and ethnicity were determined using the Research Triangle Institute race code
Defined by US census bureau. US territories excluded (n=8)
Defined by discharge ICD codes (F10.1, F10.2, and F10.9) excluding “in remission” specifiers (F10.11, F10.21, F10.91)4
Index score using discharge co-morbidity variables. Median 24, IQR 15, 36
Includes anxiety, depression, post-traumatic stress disorder, psychosis, or bipolar disorder, as defined by the Chronic Conditions Data Warehouse (CCW)
Defined by CCW
Psychiatric hospital defined by CMS special unit codes. Psychiatry/addiction medicine at general hospital defined as non-psychiatric hospital with involvement either as primary service or consult defined using inpatient billing by provider specialty codes 26, 27, or 79
Defined using diagnosis-related groups
Defined using CPT and provider specialty codes for primary care (1, 8, 11, 12, 38, 84) or any advanced practice clinician (50 and 97 which are not associated with a specialty)
Defined using CPT and provider specialty codes for psychiatry or addiction medicine (26, 27, 79)
Defined by administrative claims for “discharge against medical advice”
Includes MAUD dispensing in the year prior to hospitalization but not during 3 months leading to hospitalization
Figure: Initiation of medications for alcohol use disorder following alcohol-related hospitalizations.

AUD = alcohol use disorder
MAUD = medications for alcohol use disorder
The most predictive demographic factor for discharge MAUD initiation was younger age (age 18-39 versus 75+ aOR 3.87; 95% CI 1.34-11.16) (Table). The strongest hospitalization predictors included absence of self-directed discharge (aOR 18.48; 95% CI 2.11-162.13), psychiatric hospital or psychiatry/addiction medicine inpatient care (aOR 9.80; 95% CI 5.54-17.34 and aOR 6.23; 95% CI 3.68-1-.57, respectively) compared to no addiction medicine or psychiatry, and a primary discharge diagnosis of AUD (aOR 4.75; 95% CI 2.91-7.74). Additional predictors included remote MAUD use, female sex, psychiatric disorders, and lower Elixhauser index.
Predictors were similar for the 30-day MAUD initiation outcome, though the south and west geographic regions were associated with reduced likelihood of initiation compared to the northeast (aOR 0.71; 95% CI 0.52-0.96 and aOR 0.62; 95% CI 0.40-0.97, respectively).
Discussion
In this national sample of eligible non-recently treated Medicare Part D beneficiaries hospitalized for AUD in 2016, MAUD was rarely initiated during hospital discharge or follow-up care and was more likely among patients who were younger and with involvement of psychiatry or addiction medicine.
Hospitalizations allow for engagement with healthcare resources such as clinicians and social workers which may be otherwise difficult to access, and health vulnerability experienced by patients during hospitalizations may provide motivation for behavior change. MAUD initiation should involve a long-term treatment plan, and if this is not feasible during hospitalization then referral for outpatient treatment may be a preferred alternative.2 However, the low rate of MAUD initiation within 30 days of discharge indicates that initiation on follow-up rarely occurs. Even patients engaged with longer-term care are infrequently prescribed MAUD.5 Hospitalizations should be leveraged for interventions to initiate MAUD as a part of a comprehensive treatment plan.
Generalizability of our results to patients enrolled in other insurance plans may be limited. In addition, ICD-10 codes for AUD are unable to discern severity of AUD or severity of withdrawal. We were unable to identify rates of long-acting injectable naltrexone that was initiated during hospitalization, rates of unfilled MAUD prescriptions, or rates of patients declining MAUD. Lastly, prescribing rates in 2016 may not reflect current practice given growth of addiction medicine consult services in this time period.
Our findings highlight missed opportunities for MAUD initiation among the high-risk group of patients with AUD who are hospitalized. Increased access to psychiatry or addiction medicine presents one potential solution, but interventions to increase prescribing by generalists and non-addiction specialists are needed to bridge the MAUD initiation gap.
Acknowledgements
Funding/Support: Dr. Bernstein received funding support from an Institutional National Research Service Award (T32HP32715) and by the Massachusetts General Hospital Division of General Internal Medicine. Dr. Herzig was supported by a grant from the Agency for Healthcare Research and Quality (R01HS026215). Dr. Anderson was supported by grant (K76AG074878) from the National Institute on Aging. Dr. Baggett is supported by the Massachusetts General Hospital Research Scholars Program.
Role of the Funder/Sponsor:
The Agency for Healthcare Research and Quality and the National Institute on Aging 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.
Footnotes
Publisher's Disclaimer: This is the prepublication, author-produced version of a manuscript accepted for publication in Annals of Internal Medicine. This version does not include postacceptance editing and formatting. The American College of Physicians, the publisher of Annals of Internal Medicine, is not responsible for the content or presentation of the author-produced, accepted version of the manuscript or any version that a third party derives from it. Readers who wish to access the definitive published version of this manuscript and any ancillary material related to this manuscript (e.g., correspondence, corrections, editorials, linked articles) should go to Annals.org) or to the issue in which the article appears. Those who cite this manuscript should cite the published version, as it is the official version of record.
Conflict of Interest Disclosures: Dr. Anderson reported receiving grants from the American Heart Association, American College of Cardiology, Boston OAIC Pepper Center, and US Deprescribing Research Network outside the submitted work.
Disclaimer: The research reported in this publication was supported by the Agency for Healthcare Research and Quality and National Institute on Aging of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality or the National Institutes of Health.
Prior presentations: Presented as oral abstract at the 2023 Society of General Internal Medicine Annual Meeting (May, 2023).
Availability of items:
Protocol: not available
Statistical Code: available upon reasonable request of corresponding author
Data: not available
References
- 1.Alcohol Facts and Statistics ∣ National Institute on Alcohol Abuse and Alcoholism (NIAAA). Accessed August 3, 2022. https://www.niaaa.nih.gov/publications/brochures-and-fact-sheets/alcohol-facts-and-statistics
- 2.The American Psychiatric Association Practice Guideline for the Pharmacological Treatment of Patients With Alcohol Use Disorder ∣ American Journal of Psychiatry. Accessed September 19, 2022. https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.2017.1750101 [DOI] [PubMed]
- 3.Martin M, Clement J, Defries T, Makam AN, Nguyen OK. Prevalence and Characteristics of Hospitalizations with Unhealthy Alcohol Use in a Safety-Net Hospital from 2016 to 2018. J GEN INTERN MED. 2022;37(12):3211–3213. doi: 10.1007/s11606-021-07357-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kim HM, Smith EG, Stano CM, et al. Validation of key behaviourally based mental health diagnoses in administrative data: suicide attempt, alcohol abuse, illicit drug abuse and tobacco use. BMC Health Services Research. 2012;12(1):18. doi: 10.1186/1472-6963-12-18 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Bernstein E, Guo N, Goto T, Rothberg MB. Characterizing the Variation of Alcohol Cessation Pharmacotherapy in Primary Care. J Gen Intern Med. 2021;36(7):1989–1996. doi: 10.1007/s11606-020-06454-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
